Journal of Intelligent & Fuzzy Systems - Volume 38, issue 1

Authors: Otay, İrem | Jaller, Miguel

Article Type: Research Article

Abstract: This study focuses on the evaluation of disaster risk management and response (DRMR) processes and capabilities using a multi-expert multi-criteria decision making (MCDM) framework. The proposed framework considers four sets of evaluation and performance criteria: risk knowledge and organization, risk reduction, disaster response management, and disaster response support; and 22 sub-criteria such as regulating risk management, financial management, energy, and public safety. To contend with random perception and utility, lack of information and subjectivity in the human (expert) judgment processes that could be present in expert-based models, the authors propose an interval-valued intuitionistic fuzzy sets (IVIFSs) approach. IVIFSs can handle …high levels of uncertainty and define appropriate membership functions. Specifically, the proposed approach incorporates score judgement and possibility degree matrices, and estimates the local and global weights for each assessment criteria. And finally, evaluates the overall performances of the alternatives using intuitionistic fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) approach. The authors implemented the framework to the Atlantico State of Colombia, and assessed the disaster risk management and response processes for each for the State’s 23 municipalities. The authors discuss sensitivity analysis that illustrates the robustness of the results. Show more

Keywords: Disaster management, risk management, interval-valued intuitionistic fuzzy sets, MCDM, TOPSIS

DOI: 10.3233/JIFS-179452

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 835-852, 2020

Authors: Parimala, M. | Karthika, M. | Jafari, Saeid | Smarandache, Florentin | El-Atik, A.A.

Article Type: Research Article

Abstract:  Neutrosophic topological space is an extension of intuitionistic topological space and each triplet set in neutrosophic topological space contains membership, indeterminacy and non-membership values. Connected set in intuitionistic topological set contains membership and non-membership values and inderterminacy have not discussed in that set. This motivates the authors to propose this novel concept called neutrosophic αψ -connectedness. So we introduce the new notion of neutrosophic αψ -connectedness in neutrosophic topological spaces and investigate some properties of neutrosophic αψ -connectedness between sets and subsets of two sets. Some properties of this concept presented with numerical quantities to prove the non-existence.

Keywords: Neutrosophic closed set, Neutrosophic αψ-closed set, Neutrosophic αψ-connectedness between neutrosophic sets

DOI: 10.3233/JIFS-179453

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 853-857, 2020

Authors: Büyüközkan, Gülçin | Havle, Celal Alpay | Feyzioğlu, Orhan | Göçer, Fethullah

Article Type: Research Article

Abstract: Transportation becomes increasingly important for global trade, mobility, and economies. Passengers expect speed and quality from transportation services. As a result, the demand for air transportation is steadily rising. Higher demand for flights brings along new expectations and competition. In particular, airline companies are focused on service quality, knowing that it is a necessity to survive in a competitive market by meeting customer expectations. Hence, it is aimed that to analyze Airline Service Quality (ASQ) in Turkey. A SERVQUAL based model is developed and the criteria of the model is analyzed using group decision making (GDM) based intuitionistic fuzzy cognitive …map (IFCM) approach. A real case is conducted in Turkey airline industry. By considering the hesitation, uncertainty and intuition of decision-making processes and the opinions of the decision makers, classical FCM approach is expanded to IF environment. Decision makers who are experts in Turkey airline industry, evaluate the relationship between the criteria. The importance ratings of the criteria are determined. Thanks to dynamic structure of IFCM, scenario analysis is performed to make strategic decisions. Originality of the paper is that it is the first study dealing with GDM based IFCM and SERVQUAL approach for ASQ in Turkey to the best of our knowledge. Show more

Keywords: Airline service quality, group decision making, intuitionistic fuzzy cognitive map, scenario analysis, SERVQUAL

DOI: 10.3233/JIFS-179454

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 859-872, 2020

Authors: Abdullah, Lazim | Goh, Chunmin | Zamri, Nurnadiah | Othman, Mahmod

Article Type: Research Article

Abstract: The technique for order preference by similarity to ideal solution (TOPSIS) has been applied to numerous multi-criteria decision making (MCDM) problems where crisp numbers are utilised in defining linguistic evaluation. The interval valued intuitionistic fuzzy TOPSIS (IVIF TOPSIS) can offer a new decision making method in solving MCDM problems where interval valued intuitionistic fuzzy sets are utilised in defining linguistic terms. Differently from the TOPSIS, which directly utilised crisp numbers, this method introduces upper and lower intervals of memberships to capture wide arrays of uncertain and fuzzy information. In this paper, criteria and alternatives in flood management is investigated where …the best alternative in flood mitigation approach can be identified using the IVIF TOPSIS. Four decision makers in flood management were invited to provide linguistic evaluation of seven alternatives with respect to seven criteria. Computational results indicate that the alternative ‘pumping station’ is identified as the best alternative of flood mitigation project. The findings of this study would benefit authority in suggesting the effective approach in flood mitigation initiatives. Show more

Keywords: TOPSIS, interval valued intuitionistic fuzzy set, linguistic evaluation, decision making, flood management

DOI: 10.3233/JIFS-179455

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 873-881, 2020

Authors: Onar, Sezi Cevik | Oztaysi, Basar | Kahraman, Cengiz | Ozturk, Ersan

Article Type: Research Article

Abstract: Managing the collection of unpaid debts is crucial for the financial survival of the companies. The long term unpaid debts are collected through legal debt collection processes. This legal process should be carried out by qualified lawyers. The companies with many subscribers usually work with legal debt collection offices outside the company rather than allocate internal resources for the management of this process. Evaluating the performances of legal debt collection offices and appropriate distribution of the relevant debtor files to different legal debt collection offices located in different regions are very important for optimizing the debt collection. One of the …biggest GSM operators in Turkey that has millions of customers wants to enhance its legal debt collection process. Due to the high number of customer, the GSM operator works approximately one hundred legal debt collection offices which makes evaluation complex. This complex evaluation process should be objective, transparent, and represent the company vision and strategy. The legal debt collection offices should not only increase the total amount of collected debts but also avoid creating compliance problems and customer dissatisfaction. The evaluation of legal debt collection offices should involve both of these objective and subjective criteria. Yet, the evaluations involve hesitancy and vagueness. In this study, we use hesitant Pythagorean fuzzy sets for evaluating the performances of the legal debt collection offices and apply it the real data. Show more

Keywords: Pythagorean fuzzy sets, Legal debt collection, Pythagorean AHP, Intuitionistic Type 2

DOI: 10.3233/JIFS-179456

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 883-894, 2020

Authors: Diao, Hongyue | Cao, Yiming | Xu, Yingying | Zou, Li | Deng, Ansheng

Article Type: Research Article

Abstract: The group decision-making is a process that multiple experts participate in analysis and decision-making for multiple attributes, which can assist decision makers to set priorities and make the best decision. The linguistic truth-valued intuitionistic fuzzy lattice can better express both comparable and incomparable linguistic information, which can also better to deal with positive and negative linguistic information at the same time. To deal with the decision-making problem with fuzzy linguistic information, we propose an approach for group decision making based on linguistic truth-valued intuitionistic fuzzy lattice. For the comparable fuzzy linguistic information, the linguistic truth-valued intuitionistic fuzzy weighted averaging operator …and the linguistic truth-valued intuitionistic fuzzy ordered weighted averaging operator are presented to aggregate evaluation information of multiple experts. For the incomparable fuzzy linguistic information, positive reference nearness degree and negative reference nearness degree are introduced to deal with incomparable result with different preferences. We discuss an algorithm of group decision making, in which the decision results are alternative according to the decision makers’ preferences. A practical example is provided to illustrate the validity and rationality of the developed approach. Show more

Keywords: Group decision making, linguistic truth-valued intuitionistic fuzzy lattice, linguistic truth-valued aggregation operator

DOI: 10.3233/JIFS-179457

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 895-904, 2020

Authors: Samanlioglu, Funda | Ayağ, Zeki

Article Type: Research Article

Abstract: In this study, an intelligent approach is presented for the evaluation and selection of innovation projects. Selecting the best innovation project is a complicated multiple criteria decision making (MCDM) problem with several potentially competing quantitative and qualitative criteria. In this paper, two hesitant fuzzy MCDM methods; hesitant fuzzy Analytic Hierarchy Process (hesitant F-AHP) and hesitant fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje (hesitant F-VIKOR) are integrated to evaluate and rank innovation projects. In the hesitant fuzzy AHP-VIKOR, hesitant F-AHP is used to find fuzzy evaluation criteria weights and hesitant F-VIKOR is implemented to rank innovation project alternatives. A numerical example is …given where five innovation projects are evaluated based on nine criteria by three decision makers. Show more

Keywords: Innovation project selection, fuzzy, multiple-criteria decision making, AHP, VIKOR

DOI: 10.3233/JIFS-179458

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 905-915, 2020

Authors: Bashir, Kamal | Li, Tianrui | Yohannese, Chubato Wondaferaw | Yahaya, Mahama

Article Type: Research Article

Abstract: The object of Software Defect Prediction (SDP) is to identify modules that are prone to defect. This is achieved by training prediction models with datasets obtained by mining software historical depositories. When one acquires data through this approach, it often includes class imbalance which has an unequal class representation among their example. We hypothesize that the imbalance learning is not a problem in itself and decrease in performance is also influenced by other factors related to class distribution in the data. One of these is the existence of noisy and borderline examples. Thus, the objective of our research is to …propose a novel preprocessing method using Synthetic Minority Over-Sampling Technique (SMOTE), Fuzzy-rough Instance Selection type II (FRIS-II) and Iterative Noise Filter based on the Fusion of Classifiers (INFFC) which can overcome these problems. The experimental results show that the new proposal significantly outperformed all the methods compared in this study. Show more

Keywords: Software defect prediction, data sampling, fuzzy rough set, noise filtering

DOI: 10.3233/JIFS-179459

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 917-933, 2020

Authors: Çolak, Murat | Kaya, İhsan | Özkan, Betül | Budak, Ayşenur | Karaşan, Ali

Article Type: Research Article

Abstract:  Nowadays, more companies are trying to implement blockchain technology (BT) that enables to increase the quality of the products/services to their supply chains in order to improve their performance. BT can be applied to different sectors according to their specific needs. Evaluation of BT with respect to sectors needs considering several factors and it can be considered as a multi criteria decision making (MCDM) problem. In this paper, the appropriateness of BT in Supply Chain Management (SCM) according to different sectors has been evaluated by using a MCDM methodology based on hesitant fuzzy sets (HFSs). The suggested MCDM methodology consists …of Delphi method, hesitant fuzzy Analytic Hierarchy Process (HF-AHP) and Hesitant Fuzzy Technique for Order Preference by Similarity to Ideal Solution (HF-TOPSIS) methods. In the first stage, the criteria and sub-criteria utilized for performance evaluation of BT in supply chain management have been determined by using Delphi method. The weights of main and sub-criteria have been obtained through HF-AHP method and finally, the alternative sectors have been ranked according to results of HF-TOPSIS method. For this aim, a hierarchical MCDM problem that consists of 5 main and 17 sub-criteria has been created and the alternative sectors have been evaluated. As a result, medicine/drug and jewelry sectors have been respectively determined as the most and the least suitable alternatives in order to implement BT by means of the proposed HFSs based methodology. Finally, a sensitivity analysis has been conducted to show the importance of the main criteria weights on ranking of alternatives. Show more

Keywords: Blockchain technology, supply chain management, hesitant fuzzy sets, AHP, TOPSIS

DOI: 10.3233/JIFS-179460

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 935-946, 2020

Authors: Piltan, Farzin | Kim, Jong-Myon

Article Type: Research Article

Abstract: The design of an effective procedure for leak detection, estimation, and leak size classification is necessary to maintain the healthy and safe operations of pipelines for conveying fluids and gas from one place to another. The complexities of nonlinear and uncertain behavior inherent in a pipeline lead to difficulty of detection, estimation, and leak size estimation. Hence, a robust hybrid leak detection and size estimation method based on the back stepping hyperbolic Takagi-Sugeno (T-S) fuzzy sliding mode extended ARX-Laguerre Proportional Integral (PI) observer for pipelines is presented. Because of the effects of gases and fluids in pipelines, accurate physical modeling …of a pipeline is difficult. Consequently, the ARX-Laguerre technique is used for pipeline modeling in this study. Early detection of leaks is important to avoid product loss and other severe damage. To address this issue, the extended ARX-Laguerre PI observer is utilized to detect and estimate a leak. In addition, a T-S fuzzy technique is applied to an extended ARX-Laguerre PI observer to improve leak estimation in the presence of uncertainties. Thus, the T-S fuzzy sliding mode extended ARX-Laguerre PI observer adaptively improves the reliability, robustness, and estimation accuracy of leak detection and estimation. To leak size classification in the presence of uncertainties, the hyperbolic differential equations are governed by the T-S fuzzy extended ARX-Laguerre PI observer to find the exact solution for the kernels of a backstepping-based leak boundary. The leak estimation convergence error shows that the leak size estimation can be calculated independent of the location of the leak, which is the main contribution of this research. It is assumed that pressure and flowmeter sensors are available at the inlet and outlet of the pipeline. The effectiveness of the proposed robust backstepping hyperbolic T-S fuzzy sliding mode extended ARX-Laguerre PI observer was tested over an experimental dataset. According to the results, the proposed technique improved the leak detection, estimation, and size estimation. Show more

Keywords: Pipeline, T-S fuzzy algorithm, sliding mode technique, ARX-Laguerre system estimation, PI observer, leak detection, leak estimation, leak size classification, partial differential equation, backstepping algorithm

DOI: 10.3233/JIFS-179461

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 947-961, 2020