Journal of Intelligent & Fuzzy Systems - Volume 37, issue 4

Authors: Akhtar, Iram | Kirmani, Sheeraz

Article Type: Research Article

Abstract: To achieve superior harmonic reduction using hybrid energy generation high power devices interfaces, an advanced fuzzy current and voltage controlled technique is proposed in this paper. It proves that the proposed fuzzy controlled way could decrease the numbers of active and passive filters in the micro grid hybrid energy system. Furthermore, a closed control loop for wind system connected rectifier is not essential as the wind voltage and speed variation can be automatically recognized by the advanced control loop. Therefore, the advanced control architecture decreases the system complexity without affecting the system performance. Control and design of both the dc/dc …converter and three-phase inverter are presented. Moreover, the proposed scheme offers outstanding performance for overcoming the voltage and current distortions. The simulation model of the proposed system is developed in MATLAB Simulink environment and tested for the proposed control technique performance. Further, experimental results revealed the power and viability of the proposed method. Show more

Keywords: Solar energy system, wind energy system, fuzzy system, inverter, boost converter

DOI: 10.3233/JIFS-190504

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5335-5350, 2019

Authors: Guo, Zixue | Sun, Fangfang

Article Type: Research Article

Abstract: In the multi-attribute decision-making problems, uncertain information can be well-represented by single-valued neutrosophic linguistic sets (SVNLSs); Decision makers’ risk attitudes toward gains and losses can be solved by prospect theory (PT). Based on both, a novel integrated fuzzy decision method is proposed which combines SVNLS and PT (SVNLS-PT). In this method, we extend linguistic scale function to adapt the single-valued neutrosophic linguistic environment. Following that, we introduce the operational laws, some aggregation operators and the distance calculating method of SVNLS. Besides, PT is employed to rank the alternatives. In order to reflect both subjective considerations of decision makers and objective …information, weights of attributes are combined by objective weights and subjective weights which objective weights are obtained by mean-squared deviation method and subjective weights by establishing the liner programing model. Finally, a case study concerning investment project of Internet of Vehicles is provided to illustrate the applicability of the proposed method. Show more

Keywords: Single-valued neutrosophic linguistic set, prospect theory, combined weight, multi-attribute decision making

DOI: 10.3233/JIFS-190509

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5351-5362, 2019

Authors: Li, Zhiming

Article Type: Research Article

Abstract: Uncertain differential equation has become an important tool to deal with uncertain dynamic systems such as finance, control and medical fields. The paper aims to study the problem of estimating unknown parameters in uncertain differential equations (UDEs). Least-square method is introduced to estimate unknown parameters of a class of simple UDEs. Further, two least-square estimators of a simple UDE are obtained. The simulation results show that the proposed method is feasible for estimating unknown parameters of some UDEs.

Keywords: Uncertain measure, uncertain differential equation, parameter estimation, least-square method

DOI: 10.3233/JIFS-190521

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5363-5372, 2019

Authors: Farias, Missilene S. | Mendes, Willians R. | Araújo, Fábio M.U.

Article Type: Research Article

Abstract: Many researches use T-S fuzzy models to accurately represent nonlinear dynamic systems. However, T-S fuzzy makes the implementation of fuzzy controller more complex as system order and nonlinearities increase. Thus, the present work is aimed to overcome these limitations by using an Interval Type-2 Fuzzy Rule-Based System in which the membership functions and the number of rules can be freely chosen simplifying the implementation of the technique. To this end, it is established a direct state feedback control with reference tracking to generate the nonlinear control action using parallel distributed compensation techniques with no need to include T-S fuzzy models …to describe the dynamic system. The proposed strategy is applied to a synchronous generator and also to a magnetic levitation system. From the results, it was verified that IT2FRBSs are able to stabilize the systems analyzed at different equilibrium points with higher performance and less settling times, given the uncertainties in the linearized model. In fact, the IT2FRBS proved to be a proper way to accomplish this task, because fuzzy logic control itself does not depend on an accurate model. Show more

Keywords: Type-2 fuzzy, nonlinear systems, state feedback, reference tracking

DOI: 10.3233/JIFS-190537

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5373-5389, 2019

Authors: Saleh, Hayel N. | Khan, Idrees A. | Imdad, Mohammad | Alfaqih, Waleed M.

Article Type: Research Article

Abstract:  In this paper, we introduce a new class of fuzzy contractive mappings under the name of ‘ ( F Z , F , φ ) -contractive mappings’ and utilize the same to prove fuzzy φ -fixed point results. Some illustrative examples are also given to support our results besides deriving several consequences. As an application, we prove an existence and uniqueness result on the solution of first order periodic differential equation. Interestingly, this newly introduced class unifies several known contractions such as: fuzzy contractive, fuzzy ψ -contractive, fuzzy H -contractive and fuzzy …F Z -contractive mappings. Show more

Keywords: Fixed point, φ-fixed point, FZ, F, φ-contractive mapping, fuzzy metric space

DOI: 10.3233/JIFS-190543

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5391-5402, 2019

Authors: Peng, Wei | Xu, Liwen | Li, Chengdong | Xie, Xiuying | Zhang, Guiqing

Article Type: Research Article

Abstract: Electrical load prediction plays an important role in power system management and economic development. However, because electrical load has non-linear relationships with several factors such as the political environment, the economic policy, the human activities, the irregular behaviors and the other factors, it is quite difficult to predict power load accurately. In order to further improve the electrical load forecasting performance, a hybrid model is proposed in this paper. The proposed hybrid model combines the Stacked AutoEncoders (SAE) and extreme learning machines (ELMs) to learn the characteristics of the time series data of electrical load. In this proposed method, in …order to utilize the characteristics of the electrical load in different depths, the outputs of each layer of the SAE are taken as the inputs of one specific ELM. Then, the obtained results from the constructed different ELMs are integrated by the linear regression to obtain the final output. The linear regression part is trained by the least square estimation method. In addition, the hybrid model is applied to predict two real-world electrical load time series. And, detailed comparisons with the SAE, ELM, the back propagation neural network (BPNN), the multiple linear regression (MLR) and the support vector regression (SVR) are done to show the advantages of the proposed forecasting model. Experimental and comparison results demonstrate that the proposed hybrid model can achieve much better performance than the comparative methods in electrical load forecasting application. Show more

Keywords: electrical load prediction, hybrid model, stacked autoencoder, extreme learning machine

DOI: 10.3233/JIFS-190548

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5403-5416, 2019

Authors: Riaz, Muhammad | Hashmi, Masooma Raza

Article Type: Research Article

Abstract:  The prevailing concepts of intuitionistic fuzzy sets (IFSs), Pythagorean fuzzy sets (PFSs) and q-rung orthopair fuzzy sets (q-ROFSs) have numerous applications in various fields from real life. Unfortunately, these theories have their own limitations related to the membership and non-membership grades. To eradicate these restrictions, we introduce the novel concept of linear Diophantine fuzzy set (LDFS) with the addition of reference parameters. This idea removes the restrictions of existing methodologies and the decision maker (DM) can freely choose the grades without any limitations. This structure also categorizes the problem by changing the physical sense of reference parameters. We present some …fundamental operations on linear Diophantine fuzzy sets (LDFSs). We present geometrical interpretation for different operations of LDFSs. We also introduce the novel concepts of linear Diophantine fuzzy topological space (LDFTS) and linear Diophantine fuzzy weighted geometric aggregation (LDFWGA) operator. We discuss several properties of LDFTS with the help of examples. We introduce score functions and accuracy functions with different orders for the comparison of linear Diophantine fuzzy numbers (LDFNs). We propose two algorithms for solving multi-attribute decision-making (MADM) problem accompanied by an interesting application employing LDFTSs and LDFWGA operator. Show more

Keywords: Linear Diophantine fuzzy set (LDFS), geometrical interpretation of LDFS, linear Diophantine fuzzy topological space (LDFTS), linear Diophantine fuzzy weighted geometric aggregation (LDFWGA) operator, MADM

DOI: 10.3233/JIFS-190550

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5417-5439, 2019

Authors: Qu, Weibin | Yan, Hongyan | Zhu, Yuanguo | Chen, Xin

Article Type: Research Article

Abstract: The uncertainty theory is a branch of mathematics for studying subjective uncertainty phenomenon, and its role in subjective uncertain problems helps people make better decisions. But in real life, there is not a standard method to deal with multiple experts’ data problem. A simple method is to average all experts’ data to get a result. The other is to use the Delphi method to collect data many times and then get a normal result. This paper gives two new methods to handle this problem through conditional distributions. Compared to traditional method, they do not require all experts’ data from the …beginning and the result obtained by these methods can be updated easily when new expert’s data is given. Show more

Keywords: Uncertain statistics, multiple experts model, conditional uncertainty distribution, Delphi

DOI: 10.3233/JIFS-190553

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5441-5453, 2019

Authors: Kuo, R.J. | Cheng, W.C. | Lien, Wan-Ching | Yang, T.J.

Article Type: Research Article

Abstract: Taiwan is an endemic area for chronic hepatitis disease. Since the early 1980’s, liver cancer has become the first cancer mortality causes among other cancers in Taiwan. Besides, liver cirrhosis and chronic liver diseases are the sixth rank and seventh rank in the causes of death, respectively. This is a serious disease affecting people’s health and it brings a lot of medical cost as well. This study develops a medical cost forecasting model for the acute hepatitis patients in the emergency room. In order to consider the uncertainty and hesitation in the human being’s thinking, this study employs the intuitionistic …fuzzy logic (IFL) since it considers membership, non-membership, and hesitation values simultaneously. The proposed model combines the intuitionistic fuzzy neural network (IFNN) with Gaussian membership function and Yager-Generating function to enhance the performance of FNN. Furthermore, a back-propagation learning algorithm and genetic algorithm (GA) are applied in order to optimize the parameters and weights of the proposed IFNN. The proposed IFNN is applied to solve ten benchmark datasets including the nonlinear control and prediction problems. The computational results showed that the GA-IFNN is more efficient than conventional algorithms, such as an artificial neural network (ANN), a fuzzy neural network (FNN), and a support vector regression (SVR). In the real-world problem, the proposed method can really support physicians in planning medical resources and make a good decision to make the most efficient use of limited resources. Show more

Keywords: Fuzzy neural network, intuitionistic fuzzy logic, intuitionistic fuzzy neural network, continuous genetic algorithm, medical cost forecasting

DOI: 10.3233/JIFS-190554

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5455-5469, 2019

Authors: Aaly Kologani, M. | Jun, Y.B. | Xin, X.L. | Roh, E.H. | Borzooei, R.A.

Article Type: Research Article

Abstract: In this paper, we introduce the notion of co-annihilator in hoops and investigate some related properties of them. Then we prove that the set of filters F ( A ) form two pseudo-complemented lattices (with ∗ and ⊤) that if A has (DNP), then the two pseudo-complemented lattices are the same. Moreover, by defining the operation → on the lattice F ( A ) , we prove that F ( A ) is a Heyting algebra and by defining of the product operation, we show …that F ( A ) is a bounded hoop. Finally, we define the C  - Ann  (A ) to be the set of all co-annihilators of A , then we have that it had made a Boolean algebra. Also, we give an extension of a filter, which leads to a useful characterization of α -filters on hoops. For instance, we obtain a series of characterizations of α -filters. In addition, we show that there are no non-trivial α -filters on hoop-chains. That implies the structure of all α -filters contains only trivial α -filters on hoops. On hoops, we prove that the set of all α -filters is a pseudo-complemented lattice. Moreover, the structure of all α -filters can form a Boolean algebra under certain conditions. Show more

Keywords: Hoop, Boolean algebra, Heyting algebra, filter, co-annihilator, pseudo-complement

DOI: 10.3233/JIFS-190565

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5471-5485, 2019

Authors: Ahmad, Jamshaid | Aydi, Hassen | Mlaiki, Nabil

Article Type: Research Article

Abstract: In this manuscript, we study the existence of common α - fuzzy fixed points for fuzzy mappings via F -contractions on a metric space. We obtain some common fixed points of fuzzy (multivalued) mappings satisfying an F -contraction associated with the σ ∞ (Hausdorff) metric. In closing, we provide an application of our results.

Keywords: F-contraction, complete metric space, fixed point, fuzzy mapping, 46S40, 47H10, 54H25

DOI: 10.3233/JIFS-190580

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5487-5493, 2019

Authors: Nair, Shyni P. | Mary Linda, M.

Article Type: Research Article

Abstract: This paper proposes a hybrid strategy based maximum power point tracking (MPPT) control algorithm technique to extricate maximum power from the high infiltrating hybrid renewable energy system. The proposed hybrid strategy is the mix of Modified Dragonfly Algorithm (MDA) and Recurrent Neural Network (RNN) named as MDA-RNN. In the proposed MDA learning based RNN approach, the learning process of the RNN is upgraded by the MDA optimization process dependent on the minimum error objective function. Here, the proposed procedure precisely tracks the duty cycles of the hybrid renewable energy system utilizing Enhanced High Boost (EHB) DC-DC converter to extricate the …maximum power output from the sources. To achieve this MPPT procedure, the proposed technique requires the hybrid renewable energy system power flow parameters varieties like voltage and current at each time interim. This control system additionally consolidates a Particle Swarm Optimization (PSO) and levy flight approaches to deal with minimizing the losses in the generator and subsequently to improve the productivity of the wind and PV system. At long last, the execution of the proposed MPPT control of wind and PV power generation plans is executed in MATLAB/Simulink working stage and the execution is surveyed with the current systems. Show more

Keywords: Hybrid renewable energy system, maximum power point tracking, modified dragonfly algorithm, recurrent neural network, Enhanced High Boost (EHB) DC-DC converter

DOI: 10.3233/JIFS-190591

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5495-5514, 2019

Authors: Liu, Jinjin | Ke, Hua

Article Type: Research Article

Abstract: With the rapid-developing social media, firms increasingly employ social media for different organizational purposes, including operations, marketing and innovation management. Meanwhile, a social media retailing channel as the outcome of integrating social media with online retailing has received increasing attention in a variety of industries and academic fields. Moreover, products update is getting faster and faster with rapid-developing technologies, which usually leads to more indeterminate information on demands and costs, thus the indeterminacy should be taken into account in pricing decisions. Based on this, we explore the impact of introducing this new channel on a traditional distribution channel under uncertain …environment. Specifically, we construct two uncertain bilevel programming models under different channel structures, in which the demand of the social media channel is characterized as sensitive to the intensity of the social relationship. We find introducing the social media channel may either increase or decrease wholesale price and the traditional retailer’s retail price, depending on the expected value of the intensity of the social relationship. When the social media channel is introduced, equilibrium prices will increase with the intensity of social relationship, namely, a stronger social relationship leads to a higher retail price not only in the social media channel but also in the tradition channel. A series of numerical experiments show that a rise in the uncertain degree of the intensity of the social relationship will raise the manufacturer’s expected profit, but has no impact on equilibrium prices and the retailer’s expected profit. Show more

Keywords: Social media retailing, social relationship, dual channel, pricing decision, uncertainty theory

DOI: 10.3233/JIFS-190595

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5515-5529, 2019

Authors: Tehrim, Syeda Tayyba | Riaz, Muhammad

Article Type: Research Article

Abstract: In this paper, we bring out the idea of bipolar neutrosophic soft topology based on bipolar neutrosophic soft set (BNS-set). We study the properties of classical topology under bipolar neutrosophic soft (BNS) vagueness. The BNS-topology is the generalization of the fuzzy topology. We discuss certain properties of BNS-topology including, BNS-closure, BNS-interior, BNS-exterior and BNS-frontier by utilizing BNS-points. We also study the concept of BNS-subspace, BNS-neighborhoods and BNS-base for BNS-topology with the help of detailed examples and theorems. Furthermore, we propose: Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS) method under BNS-topological environment to deal with similarities in …medical diagnosis. We see the importance of BNS-topology in multi criteria group decision making (MCGDM) as well. We present a numerical example with real background to demonstrate the validity of our model. Finally, we make a method-based and set-based comparison analysis of proposed method with some existing methods. Compared with existing MCGDM models, this study provides a flexible framework to form an approximate decision model to real-world MCGDM problems. Show more

Keywords: BNS-topology, BNS-topological properties, BNS-TOPSIS, MCGDM, medical diagnosis

DOI: 10.3233/JIFS-190668

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5531-5549, 2019

Authors: Zhong, Yanru | Guo, Xiuyan | Gao, Hong | Qin, Yuchu | Huang, Meifa | Luo, Xiaonan

Article Type: Research Article

Abstract: To describe the values of criteria and to generate a sort of alternatives are two important issues in multi-criteria decision-making (MCDM). A superior tool for the former issue is Pythagorean hesitant fuzzy number (PHFN) and an effective tool for the latter issue is aggregation operator. So far, a number of aggregation operators of PHFNs have been presented within the academia. Each aggregation operator has its own characteristics and can work well for its specific purpose. But there is not yet an aggregation operator of PHFNs that can provide satisfying generality and flexibility in aggregating the values of criteria and capturing …the interactions of criteria. The Archimedean t-conorm and t-norm (ATT) are well-known for having the capability to generate versatile and flexible operational rules for fuzzy numbers, while the Muirhead mean (MM) operator is an all-in-one aggregation operator for capturing the interrelationships of the aggregated arguments. To this end, the MM operator and the ATT for PHFNs are combined to present a Pythagorean hesitant fuzzy Archimedean MM (PHFAMM) operator and a weighted PHFAMM operator and a new MCDM method based on the presented operators is proposed in this paper. Firstly, the generalised expressions of the presented operators are provided. The properties of the operators are explored and proved and their specific expressions based on Algebraic, Einstein, Hamacher, and Frank ATTs are then constructed. Based on these specific expressions, a new method for solving the MCDM problems based on PHFNs is developed. Finally, the developed MCDM method is demonstrated via an example, a set of experiments and qualitative and quantitative comparisons. Show more

Keywords: Pythagorean hesitant fuzzy set, muirhead mean operator, Archimedean t-conorm and t-norm, aggregation operator, multi-criteria decision-making

DOI: 10.3233/JIFS-190704

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5551-5571, 2019

Authors: Sakr, Nehal A. | Abu-Elkheir, Mervat | Atwan, A. | Soliman, H. H.

Article Type: Research Article

Abstract: Sensor-based human activity recognition gained a lot of research interest within the field of pervasive computing due to its wide range of application domains. Recognition of complex human activities is a challenging task due to the tendency of humans to perform activities in an interleaved and concurrent scenario. In this paper, we address the problem of complex activities recognition using a combination of the discriminative features called Strong Jumping Emerging Patterns (SJEPs) and the fuzzy sets theory. The proposed approach is designed to fit the challenges of multi-label classification, nonlinear separation, and recognition of multiple overlaps of interleaved and concurrent …activities. Besides the need for a training dataset of complex activities that is difficult to obtain. The proposed approach uses a training dataset of simple activities to extract two sets of SJEPs for linear and nonlinear activities. Then, a novel SJEP-based recognition approach is presented to recognize simple and complex activities. We evaluate our approach using two datasets collected from two different labs. Experimental results show the efficiency of our approach in recognizing simple and complex human activities, besides the superiority of our approach against other competing approaches with regard to recognition accuracy. Show more

Keywords: Complex activities recognition, emerging pattern, multi-label classification, nonlinear separation, fuzzy sets

DOI: 10.3233/JIFS-190706

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5573-5588, 2019

Authors: Mousazadeh, Saeed | Darestani, Soroush Avakh

Article Type: Research Article

Abstract: Blood and blood products are vital resources for the surgery and the treatment of certain diseases. As a scarce and perishable resource, they require sophisticated management to minimize waste in order to address this challenge, the present study revolves around the idea of the management of the production, supply and distribution of blood products. In this research, two questions of robust and flexible have been investigated for the production, inventory and routing blood products. The flexibility is incorporated into the problem through introducing the possibility of sharing inventory among network entities by transferring blood products between hospitals and also the …possibility of meeting a blood group’s need with another compatible blood type or replacement. The problem is then solved by heuristic (local search) and meta-heuristic (Adaptive Large Neighborhood Search (ALNS)) algorithms, which are the methods of choice in particular for NP-hard problems. Finally, the results obtained from the two algorithms are compared it is shown that the heuristic algorithm outperforms the Adaptive Large Neighborhood Search (ALNS) in both models, that can lead to reduction is cost and required transitions. Show more

Keywords: Inventory, routing, integrated production, routing, robust optimization, health care optimization, flexibility, uncertainty

DOI: 10.3233/JIFS-190723

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5589-5609, 2019

Authors: Dhawan, Pooja | Kaur, Jatinderdeep | Gupta, Vishal

Article Type: Research Article

Abstract: In the present article, the concept of expansion is extended in a refined manner by introducing P -expansion defined on a family F of bounded functions. Some fixed function theorems using expansive mappings in complete metric spaces are investigated. These results improve and generalize various results existing in literature. The authenticity of obtained results is verified with the help of some comparative examples. In addition, an application has also been presented which is based on the best approximation of dose distribution for a number of patients (at a same time) getting …Tomotherapy. Show more

Keywords: Fixed function, complete metric space, expansive mappings, 47H10, 54H25

DOI: 10.3233/JIFS-190810

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5611-5618, 2019

Authors: Nadeem, Farrukh

Article Type: Research Article

Abstract: Today’s large scale distributed platforms comprise thousands of resources from production, educational, and ad hoc environments including Clouds, Grids, P2P, etc. However, finding suitable resources from such a large pool to store large amounts of data and run multi-resource, long-running data processing applications (usually with few or no fault tolerance capabilities) is restricted by the dynamic availability of distributed resources. In addition to resource failures, the resources may be unavailable due to their owners’ policies for sharing their resources as well as the nature of domain they belong to (e.g. P2P systems, non-dedicated desktop Grids etc.). As a result, the …availability-aware selection of distributed resources has become a challenging problem for data management, resource provisioning and job scheduling services. To this end, we present a novel resource availability characterization and prediction method for dynamic heterogeneous distributed environments. We identified 14 availability attributes that can be effectively used to model resource availability in dynamic distributed environments. Three data mining methods (particularly the neural network) are proposed to model and predict resource availability using our identified availability attributes. The availability of a resource is predicted for an instant of time as well as for a time duration. Our experiments for 28 different resources in Austrian Grid show that the predictions through the proposed approach are 18% and 31% (on average) more accurate than those by so far the best method (Naive Bayes’ Classifier) for instant and duration availability, respectively. Show more

Keywords: Distributed systems, dynamic resource availability, resource availability characterization, resource availability predictions

DOI: 10.3233/JIFS-190749

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5619-5632, 2019

Authors: Chen, Yubing | Wen, Meilin | Wang, Fei

Article Type: Research Article

Abstract: Data envelopment analysis (DEA) has become an accepted tool for assessing efficiency in a wide range of cases since it was first proposed in 1978. However, traditional DEA models need accurate inputs and outputs, which can’t be obtained or measured in many practical cases. This paper will apply DEA into uncertain environment, and propose a new DEA model with uncertain inputs and outputs based on uncertain theory. Furthermore, the uncertainty theory is utilized to convert the new uncertain DEA model into an equivalent deterministic model for simplification. Finally, this new uncertain DEA model is applied to the evaluation of scientific …research personnel to illustrate the effectiveness. Show more

Keywords: Data envelopment analysis, uncertainty theory, uncertain variable, uncertainty distribution, efficiency

DOI: 10.3233/JIFS-190784

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5633-5640, 2019

Authors: Zheng, Qinghe | Tian, Xinyu | Jiang, Nan | Yang, Mingqiang

Article Type: Research Article

Abstract: Nowadays, despite the popularity of deep convolutional neural networks (CNNs), the efficient training of network models remains challenging due to several problems. In this paper, we present a layer-wise learning based stochastic gradient descent method (LLb-SGD) for gradient-based optimization of objective functions in deep learning, which is simple and computationally efficient. By simulating the cross-media propagation mechanism of light in the natural environment, we set an adaptive learning rate for each layer of neural networks. In order to find the proper local optimum quickly, the dynamic learning sequence spanning different layers adaptively adjust the descending speed of objective function in …multi-scale and multi-dimensional environment. To the best of our knowledge, this is the first attempt to introduce an adaptive layer-wise learning schedule with a certain degree of convergence guarantee. Due to its generality and robustness, the method is insensitive to hyper-parameters and therefore can be applied to various network architectures and datasets. Finally, we show promising results compared to other optimization methods on two image classification benchmarks using five standard networks. Show more

Keywords: Deep learning, deep CNNs, non-convex optimization, SGD, layer-wise learning

DOI: 10.3233/JIFS-190861

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5641-5654, 2019

Authors: Han, Yefan | Qu, Shaojian | Wu, Zhong | Huang, Ripeng

Article Type: Research Article

Abstract: In the process of group decision making, perturbation of input data always reduces the quality of the optimal solution or even makes it unfeasible. Hence, the value of the optimal solution is often limited. In this paper, a robust optimization method is proposed to overcome the inherent uncertainty of input data in group decision making (such as experts’ unit adjustment cost). Firstly, the minimum cost consensus model based on norm definition is established. Then, four different forms of uncertainty sets are proposed, and the corresponding robust models of four minimum consensus cost models are established. Finally, in order to evaluate …the robustness of the solutions obtained by the robust consensus model, the results with different parameters are compared. The robust consensus model is also compared with the minimum cost consensus model. A numerical example proves that the result of the minimum cost consensus model is too optimistic, and the robust consensus model is more robust. Show more

Keywords: Group decision making, consensus, uncertain set, robust optimization, marketing plan

DOI: 10.3233/JIFS-190863

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5655-5668, 2019

Authors: Vu, Ho | Hoa, Ngo Van | An, Truong Vinh

Article Type: Research Article

Abstract: The results of this paper is motivated from some recent papers treating the problem of the existence and stability of a solution for Volterra integro-differential equations in fuzzy setting with fractional order derivative (FFVIDEs). By constructing successive approximation method in the space of fuzzy functions, we establish the Ulam-Hyers stability and Ulam-Hyers-Rassias stability for the given problems with two concepts of fuzzy-type fractional derivative.

Keywords: Ulam-hyers stability, ulam-hyers-rassias stability, fuzzy fractional integro-differential equations

DOI: 10.3233/JIFS-190952

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5669-5688, 2019

Authors: Gu, Yujie | Hao, Qingwei | Shen, Jie | Zhang, Xiang | Yu, Liying

Article Type: Research Article

Abstract: Variance in fuzzy set theory, generally applied in investment decision, risk evaluation, and so on, can be described as a measurement that gauges the deviation of a fuzzy number. In this paper, in order to extend the application range and enrich the research area of variance, the concepts of variance bounds and semi-variances are defined and discussed from a theoretical point of view. With respect to some frequently-used fuzzy intervals, four relatively simple calculation formulas for upper and lower bounds of variance, and upside and downside semi-variances are put forward respectively, with the aid of which several correlation inequalities are …subsequently presented and proved. Besides, in order to depict the concepts and inequalities more distinctly, plenty of examples are introduced to make some numerical illustration. Show more

Keywords: Fuzzy interval, bounds of variance, semi-variance, inequalities

DOI: 10.3233/JIFS-181408

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5689-5705, 2019

Authors: She, Kun | Chen, Yumin

Article Type: Research Article

Abstract: Rough set reduction has been used as a momentous preprocessing tool for machine learning, pattern recognition, and big data analysis. It is well known that the traditional rough set theory can only handle features with categorical values. Therefore, a neighborhood rough set model is introduced to deal with numerical data sets. Classical greedy search strategies to neighborhood rough set reduction have often failed to achieve optimal reducts. Many researchers shift to swarm intelligence algorithms, such as particle swarmoptimization, ant colony optimization and fish swarm algorithm, giving a better solution but with a large cost of computational complexity. It is beneficial …for exploring fast and effective feature reduction algorithms. In this paper, we firstly introduce a knowledge representation, named power set tree (PS-tree). It is an order tree enumerating all the subsets of a feature set. Each node of the PS-tree is a possible feature reduct. Furthermore, we develop a tree search framework for reduction question solving by the PS-tree. We present four tree search methods based on PS-tree, which are depth-first, breadth-first, uniform-cost and A * search methods. The effectiveness of these four proposed tree search methods are tested on some UCI data sets. Finally, we compare the A * search with traditional greedy search and swarm intelligence methods. The comparisons show that the selected features by A * search attain good reduction rates and simultaneously maintain the classification accuracy of whole features. Show more

Keywords: Rough sets, neighborhood rough sets, A* search, feature selection, tree search

DOI: 10.3233/JIFS-18784

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5707-5718, 2019

Authors: Xiu, Zhen-Yu | Li, Qing-Guo

Article Type: Research Article

Abstract:  In this paper, the notions of (L , M )-fuzzy concave spaces, (L , M )-fuzzy interior spaces, (L , M )-fuzzy interior relations and (L , M )-fuzzy hull relations are introduced. It is proved that the category of (L , M )-fuzzy concave spaces, the category of (L , M )-fuzzy interior spaces, the category of (L , M )-fuzzy interior relation spaces and the category of (L , M )-fuzzy hull relation spaces are isomorphic. Moreover, it is proved that these categories are all isomorphic to the category of (L , M )-fuzzy convex spaces when L …is a completely distributive lattice with an order-reversing involution. Show more

Keywords: (L, M)-fuzzy concave spaces, (L, M)-fuzzy interior operators, (L, M)-fuzzy interior relations, (L, M)-fuzzy hull relations

DOI: 10.3233/JIFS-181663

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5719-5730, 2019

Authors: Sun, Lin | Wang, Wei | Xu, Jiucheng | Zhang, Shiguang

Article Type: Research Article

Abstract: Gene selection as an important data preprocessing technique for cancer classification is one of the most challenging issues in the field of microarray data analysis. In this paper, to deal with gene expression data more effectively, a locally linear embedding (LLE) and neighborhood rough sets-based gene selection method using Lebesgue measure for cancer classification is proposed. First, to solve the problems that the traditional LLE method cannot effectively identify category information, and is susceptible to noise pollution and other issues, the intra-class neighborhood is defined and a new method of calculating reconstruction weight is proposed by combining with the Euclidean …distance to improve LLE. Then, the Lebesgue measure is introduced into neighborhood rough sets, a δ -neighborhood measure is defined, and the dependency degree and the significance measure are presented in neighborhood decision systems. Finally, an improved LLE and neighborhood rough sets-based gene selection algorithm is designed, where the improved LLE algorithm is used to reduce the initial dimensions of gene expression data and obtain a candidate gene subset, and the Lebesgue measure and dependency degree-based relative reduction for gene expression data is developed to further screen the candidate subset to select the final gene subset. The experimental results under several public gene expression data sets prove that the proposed method is effective for selecting the most relevant genes with high classification accuracy. Show more

Keywords: Rough sets, neighborhood rough sets, gene selection, locally linear embedding, cancer classification

DOI: 10.3233/JIFS-181904

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5731-5742, 2019

Authors: Zhang, Xiaohong | Wu, Xiaoying | Mao, Xiaoyan | Smarandache, Florentin | Park, Choonkil

Article Type: Research Article

Abstract: From the perspective of semigroup theory, the characterizations of a neutrosophic extended triplet group (NETG) and AG-NET-loop (which is both an Abel-Grassmann groupoid and a neutrosophic extended triplet loop) are systematically analyzed and some important results are obtained. In particular, the following conclusions are strictly proved: (1) an algebraic system is neutrosophic extended triplet group if and only if it is a completely regular semigroup; (2) an algebraic system is weak commutative neutrosophic extended triplet group if and only if it is a Clifford semigroup; (3) for any element in an AG-NET-loop, its neutral element is unique and idempotent; (4) …every AG-NET-loop is a completely regular and fully regular Abel-Grassmann groupoid (AG-groupoid), but the inverse is not true. Moreover, the constructing methods of NETGs (completely regular semigroups) are investigated, and the lists of some finite NETGs and AG-NET-loops are given. Show more

Keywords: Semigroup, neutrosophic extended triplet group (NETG), completely regular semigroup, Clifford semigroup, Abel-Grassmann’s groupoid (AG-groupoid)

DOI: 10.3233/JIFS-181742

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5743-5753, 2019

Authors: Gao, Hui | Lu, Mao | Wei, Yu

Article Type: Research Article

Abstract: In this paper, we investigate the multiple attribute decision making problems based on the Hamacher aggregation operators with dual hesitant bipolar fuzzy information. Then, motivated by the idea of Hamacher operations, we have developed some Hamacher aggregation operators for aggregating dual hesitant bipolar fuzzy information: dual hesitant bipolar fuzzy Hamacher weighted average (DHBFHWA) operator, dual hesitant bipolar fuzzy Hamacher weighted geometric (DHBFHWG) operator, dual hesitant bipolar fuzzy Hamacher ordered weighted average (DHBFHOWA) operator, dual hesitant bipolar fuzzy Hamacher ordered weighted geometric (DHBFHOWG) operator, dual hesitant bipolar fuzzy Hamacher hybrid average (DHBFHHA) operator and dual hesitant bipolar fuzzy Hamacher hybrid geometric …(DHBFHHG) operator. Then, we have utilized these operators to develop some approaches to solve the dual hesitant bipolar fuzzy multiple attribute decision making problems. Finally, a real-world example is then analyzed to illustrate the relevance and effectiveness of the proposed methodology. Show more

Keywords: Multiple attribute decision making (MADM), bipolar fuzzy set, dual hesitant bipolar fuzzy set, dual hesitant bipolar fuzzy Hamacherhybrid average (DHBFHHA) operator, dual hesitant bipolar fuzzy Hamacher hybrid geometric (DHBFHHG) operator

DOI: 10.3233/JIFS-18266

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5755-5766, 2019

Authors: Lu, Cheng | Xu, Ting-Xue | Cong, Lin-Hu

Article Type: Research Article

Abstract: As the existing research of condition-based Maintenance (CBM) decision-making neglects the influence of regular detection and maintenance (RDM) on the recovery of equipment performance, it is impossible to accurately describe the state degradation characteristics and life distribution law in this case, which is not helpful to formulate reasonable and effective maintenance strategies. Aimed at this problem, a maintenance strategy combining RDM and CBM is proposed in this paper, and the performance degradation modeling and maintenance optimization model under this strategy are studied deeply. Considering the discontinuous and catastrophic performance degradation characteristics of equipment under this condition, a performance degradation model …is established by using the Inverse Gaussian process from the failure mechanism. On this basis, a combined maintenance decision model constrained by risk function is constructed. The optimal maintenance cycle and preventive maintenance threshold are obtained by optimizing the equipment maintenance cost under long-term operation conditions. The relationship between the cost rate and the maintenance strategy value is obtained through the example analysis of the equipment components, and it is proved that the joint maintenance strategy can not only prolong the service life and maintenance interval of equipment, but also reduce the maintenance risk and cost. Show more

Keywords: Regular detection and maintenance, condition-based maintenance, inverse gaussian process, cost rate, maintenance strategy

DOI: 10.3233/JIFS-181580

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5767-5775, 2019

Authors: Nosrat, Azizollah | Sanei, Masoud | Payan, Ali | Hosseinzadeh Lotfi, Farhad | Razavyan, Shabnam

Article Type: Research Article

Abstract: In this paper, crisp two-stage data envelopment analysis (TSDEA) models are expanded for decision-making problems where inputs, intermediate data, and outputs are expressed with fuzzy numbers. Considering the merits of credibility theory, we propose the use of this theory in the efficiency measurement of fuzzy serially-connected two-stage systems. For determined credibility levels, we transform the fuzzy model into a linear programming problem and then obtain the credibility function and membership function for fuzzy efficiency of two-stage decision-making units (DMUs). We also explore the sensitivity and stability analysis of two-stage DMUs based on the proposed methodology. As a result, the projection …of inefficient fuzzy two-stage DMUs and the stability radius of efficient fuzzy two-stage DMUs, i.e. the region in which efficiency status is preserved, are also determined. We also provide an illustrative example to better explain the method and demonstrate its performance in comparison with other developed methods for fuzzy TSDEA. Show more

Keywords: Two-stage data envelopment analysis, fuzzy input- intermediate -output data, credibility measure, sensitivity and stability analysis

DOI: 10.3233/JIFS-181519

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 5777-5796, 2019