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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
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
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