Journal of Intelligent & Fuzzy Systems - Volume 37, issue 6

Authors: Akram, Muhammad | Adeel, Arooj

Article Type: Research Article

Abstract:  Hesitant fuzzy sets (HFSs) present a general structure to express the uncertain concepts and data that have been served as in most of the generalizations of fuzzy sets. In this research article, we introduce a novel hybrid model called hesitant m -polar fuzzy sets (Hm F-sets), which is a reasonable combination of HFSs with m -polar fuzzy sets (m F sets). It is the generalization of the concept HFSs, in which the membership degrees of an element of given set deals the m different numeric and fuzzy values that enables to deal the hesitancy of multipolar information. Hesitancy integrates …the conformity for the analysis of given data, and an m F format concedes to severalize the sources of multi-polar information. We highlight and explore some useful properties, construct fundamental operations and investigate comparison laws of Hm F-sets. Moreover, we develop the hesitant m -polar fuzzy TOPSIS approach for multi-criteria group decision-making (MCGDM), which is the natural extension of TOPSIS method and used to rank and choose the best alternative under Hm F positive and negative ideal solutions to this framework. We describe applications of Hm F-sets in group decision-making and apply our proposed method in real life examples to show its efficiency. Finally, we develop an algorithm that implements our decision-making procedure by using computer programming. Show more

Keywords: Hesitant fuzzy set, m-polar fuzzy set, hesitant m-polar fuzzy set, decision-making, TOPSIS

DOI: 10.3233/JIFS-190551

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 8077-8096, 2019

Authors: Cao, Hongfei | Zhang, Runtong | Wang, Jun

Article Type: Research Article

Abstract: This paper aims to propose a new tool to express decision makers’ preference information in multi-attribute decision making (MADM) producers. By taking advantages of spherical fuzzy sets (SFSs) and linguistic variables (LVs), we give the definition of spherical linguistic sets (SLSs) and provide operations of spherical linguistic numbers (SLNs). Based on the proposed operations, we incorporate Muirhead mean (MM) into SLSs and introduce novel spherical linguistic aggregation operators. These proposed operators adsorb the inherent advantages of MM, i.e., taking the interrelationship among any numbers of aggregated inputs into account and producing flexible information fusion process. Furthermore, we apply the proposed …method in MADM and present the main steps of a new method. In order to show its effectiveness, we use the method to solve an actual MADM problem. The advantages and superiorities of the proposed method are also studied. Show more

Keywords: Spherical fuzzy set, spherical linguistic set, spherical linguistic muirhead mean, multi-attribute decision making

DOI: 10.3233/JIFS-190566

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 8097-8111, 2019

Authors: Deng, Xue | Fang, Wen

Article Type: Research Article

Abstract: In this paper, a novel framework is proposed for fuzzy portfolio selection based on a combination between Data Envelopment Analysis (DEA) prospect cross-efficiency approach and the maverick index. Although DEA cross-efficiency evaluation is used to an effective tool for portfolio selection, no researcher has yet attempted to combine DEA cross-efficiency method with investors’ psychology in fuzzy portfolio selection. To address this problem, two novel prospect cross-efficiency models termed PCE (I) and PCE (II) are developed as the foundations for the construction of a novel fuzzy portfolio model. Because of the uncertain environment of financial market, the returns of assets are …characterized as triangular fuzzy numbers. To make our models more comprehensive and practical, five criteria including mean, variance, semi-variance, skewness and entropy are employed in PCE models. Furthermore, based on the PCE evaluation, a novel mean-variance-maverick (MVM) framework is designed for fuzzy portfolio selection, in which the prospect cross-efficiency is viewed as return characteristic, maverick index and variance are considered as risk characteristics. The maverick index, as a novel risk measure, can be used as a good indicator for sensitivity to environment volatility in portfolio selection. Finally, a numerical example is provided to illustrate the effectiveness of our proposed models. The results show that our proposed approach can not only capture the risk attitudes of investors, but also permit well-diversified portfolios and higher risk-adjusted returns than other benchmark portfolios. Show more

Keywords: Fuzzy portfolio selection, data envelopment analysis (DEA), risk attitude, prospect cross-efficiency, mean-variance-maverick model

DOI: 10.3233/JIFS-190568

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 8113-8130, 2019

Authors: Pekkaya, Mehmet | Erol, Figen

Article Type: Research Article

Abstract: The AHP technique application is usually for determining criteria priorities according to respondents, but no statistical query exists for instance, whether the experts’ views significantly change with respect to some characteristics, the criteria priorities significantly differentiate with each other. This research objective is along with determining the priorities of subcriteria in the evaluation of bank failure/bankruptcy risk, to show generating priority series from experts’ views for each criteria for carrying out statistical tests with respect to expert subgroups, and then produce information for researchers/decision makers. The research utilises the usage of conducting statistical hypothesis testing on generated priority series and …CAMELS approach to bank failure. This study investigates and determines the subcriteria priorities of CAMELS dimensions, and uses the data of study Pekkaya & Erol (2016) for statistical tests by generating priority series of CAMELS dimensions. Since no similar academic study, which uses statistical tests and generates priority series in bank failure/bankruptcy literature via similar approach, is observed; this study can be accepted as paving the way of the usage of AHP technique. The obtained priority values of subcriteria with main criteria of CAMELS dimensions can be used to improve the early warning system for bank failure. Show more

Keywords: AHP, bank’s bankruptcy risk, CAMELS, liquidity, asset, capital

DOI: 10.3233/JIFS-190574

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 8131-8146, 2019

Authors: Sharma, Poonam | Singh, Akansha | Raheja, Supriya | Singh, Krishna Kant

Article Type: Research Article

Abstract: This paper presents an automated vehicle identification and classification method from traffic videos. The proposed method unlike other traditional methods combines the multiple time spatial frames to detect moving objects. These moving objects are the potential vehicles however there may be some other moving objects also. Therefore to further improve the accuracy of the proposed method, the moving objects are classified using object oriented classification scheme. The identification of vehicles from traffic videos plays an important role in Intelligent Transport systems (ITS). A virtual line is placed on each frame such that the objects crossing this line are the desired …moving objects. The object based classifier makes use of fuzzy rules based on features like area, perimeter, and elongation and so on. These fuzzy rules are used to classify them into vehicle and non-vehicle classes. The second level of classification further classifies the vehicles into two wheeler, four wheeler and six wheeler vehicles. The method can be appropriately used for traffic surveillance as it also computes the speed of vehicles using the time spatial frames. The proposed method is applied on traffic videos of multiple time lengths. A comparative study of the proposed method with the existing methods reveals that the proposed work has higher accuracy. The motion detection, vehicle classification and speed of computation make this method best suited for many ITS applications like traffic surveillance and other similar applications. Show more

Keywords: Vehicle detection, multiple spatial time frames, object oriented classification, rule based method, motion detection

DOI: 10.3233/JIFS-190593

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 8147-8157, 2019

Authors: Dündar, Erdinç | Akın, Nimet Pancaroğlu

Article Type: Research Article

Abstract:  In this paper, we introduce the notions of regularly ( I W 2 , I W ) -convergence, regularly ( I W 2 * , I W * ) -convergence, regularly ( I W 2 , I W ) -Cauchy and regularly ( I W 2 * , I W * ) -Cauchy double sequence of sets and investigate the relationship among them.

Keywords: Regularly ideal convergence, double sequence of sets, Wijsman convergence

DOI: 10.3233/JIFS-190626

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 8159-8166, 2019

Authors: Muneiah, Janapati Naga | Subba Rao, Ch D. V.

Article Type: Research Article

Abstract: Telecom sector is hugely losing profits in different degrees due to various undesired classes of its customers. Churners, a certain class of customers shifting to the competitors, are the most undesired class of customers who are the predominant reason for the losses. Still, there are other classes of customers in this business who stay with the enterprise, but they are inactive in using the services and leading to uncertainty and an insignificant amount of profits. When data mining techniques are applied to such applications they produce customer models in the form of decision trees, etc. and provide customer’s class label …only such as churner/non-churner. Furthermore, they only focus on improving the technical interestingness measures of prediction models. Thus, very limited research has been carried out on turning the prediction results into useful decision making actions. Consequently, some manual work by domain expert has to be done to postprocess the model to obtain the actionable knowledge for changing the customer from undesired class to the desired one. However, some of the existing works are suggesting the actions to convert the class of the customer from one category to another, but they have limitations in that they do not generalize to more than two classes. In this paper, a novel algorithm, which aptly fits the multi-class setting of Telecom sector, is presented that suggest actions to change the customer from an undesired class to a desirable one with maximum net profit. We explain our proposed method with the help of a case study of the Telecom sector. Empirical tests are conducted on the case study problem and also on UCI benchmark data and shown that our method is effective and scalable. With the help of comparison with state-of-the-art methods and substantial experiments, we demonstrate the efficiency of the proposed method. Show more

Keywords: Data mining, probability estimation decision trees, actionable knowledge discovery, decision making, profit maximization, Telecom sector

DOI: 10.3233/JIFS-190628

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 8167-8197, 2019

Authors: Yavuz, Enes

Article Type: Research Article

Abstract:  We introduce semicontinuous summation methods for series of fuzzy numbers and give Tauberian conditions under which summation of a series of fuzzy numbers via generalized Dirichlet series and via generalized factorial series implies its convergence. Besides, we define the concept of level Fourier series of fuzzy valued functions and obtain results concerning the summation of level Fourier series.

Keywords: series of fuzzy numbers, Tauberian theorems, fuzzy Fourier series, 03E72, 40A05, 40E05

DOI: 10.3233/JIFS-190632

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 8199-8206, 2019

Authors: Khan, Izaz Ullah | Karam, Fazal Wahab

Article Type: Research Article

Abstract: The study presents Proposed Data Envelopment Analysis (DEA) approaches for intelligent business analytics of the US Airline industry to gain more knowledge, control, flexibility and trade-off among various inputs to the system/industry. Three new proposed DEA models are presented. The results obtained provide credible data analytics and intelligent business suggestions. Firstly the proposed input oriented and the proposed output oriented DEA models are formulated. The proposed input oriented DEA model suggests how resource utilization can be minimized while operating in with the same output level. Further, the proposed output oriented model suggests how output efficiency can be increased to a …benchmark level while keeping the input at the same level. Then the proposed Slack Based DEA model SBM is formulated. The proposed models are then solved with the DEA Excel Solver for finding the efficient points in the Pareto Frontier. Representing the Pareto Frontier as a function of total system revenue gives necessary information about the inputs growth and their trade-off with the output. Furthermore, the proposed Slack Based DEA model (SBM) intelligently measures the technical efficiency of each airline. The results show that three airlines namely American, United and Jet Blue are weakly efficient operating below the proposed SBM efficient frontier. Furthermore, the results intelligently suggest the possible inputs reduction and outputs increases to get to the efficient frontier for the management of the concerned airlines. The proposed SBM slacks suggest the possible areas of improvement for future planning and optimal operating input/output levels for the top management of the weakly efficient airlines. Show more

Keywords: Performance evaluation, date envelopment analysis (DEA), slack based DEA model (SBM), airline industry

DOI: 10.3233/JIFS-190641

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 8207-8217, 2019

Authors: Motepe, Sibonelo | Hasan, Ali N. | Twala, Bhekisipho | Stopforth, Riaan

Article Type: Research Article

Abstract: The study of South African distribution (Dx.) network’s load forecasting using recent and state of the art AI (machine learning, deep learning and ensemble deep learning) techniques, is limited. The impact of weather parameters on load forecasting performance of AI techniques in forecasting South African large power users is not well understood. This paper proposes a novel distribution network load forecasting system. The paper further introduces deep learning and ensemble deep learning techniques in forecasting the power consumption of large South African power users. The paper introduces these techniques through an investigation of their performance against that off state of …the art machine learning techniques, ANFIS and OP-ELM. The impact of temperature on the performance of these techniques is also investigated. This investigation was conducted on three case studies, with three different industrial large power consumer loads. LSTM-RNN proved to be a more efficient load forecasting technique for the proposed load forecasting system, achieving the lowest load forecasting error in all three case studies. Ensembles of LSTM were found to overall achieve lower errors than the individual techniques’ models. This improvement was less than 1%. The inclusion of temperature was found to generally improve the load forecasting performance of ML and DL techniques’ models. Show more

Keywords: Distribution networks, load forecasting, deep learning, machine learning, LSTM-RNN

DOI: 10.3233/JIFS-190658

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 8219-8235, 2019