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