Journal of Intelligent & Fuzzy Systems - Volume 39, issue 5

Authors: Ercan-Teksen, Hatice | Anagün, Ahmet Sermet

Article Type: Research Article

Abstract: Control chart is one of the statistical methods to analyze the process. The use of fuzzy sets in control charts, which are divided into qualitative and quantitative data, has been applied in many studies recently. Especially for qualitative control charts, data collection is more difficult and more subjective. Therefore, fuzzy sets are used to reduce losses in data. There are many control chart studies created by type-1 fuzzy sets available in the literature. In recent years, examples of fuzzy control charts with extensions of fuzzy sets have been found. The aim of this study is to obtain c-control chart for …intuitionistic fuzzy sets. For this purpose, defuzzification and likelihood methods are used. In particular, with the application of the likelihood method to intuitionistic fuzzy control charts, this will be considered as a pioneering study in the literature. In addition, a novel likelihood method was developed for intuitionistic fuzzy sets and used here to provide flexibility. Show more

Keywords: Intuitionistic fuzzy sets, fuzzy control charts, intuitionistic fuzzy comparison methods

DOI: 10.3233/JIFS-189110

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6465-6473, 2020

Authors: Karadayi-Usta, Saliha | Bozdag, Cafer Erhan

Article Type: Research Article

Abstract: Medical tourism service offers a professional healthcare opportunity by travelling abroad with the chance of touristic and cultural activities at the destination country. Medical travelers prefer a foreign country for treatment due to long waiting periods, high costs, excessive number of patients, inadequate number of healthcare professionals and inadequate cutting-edge technological equipment at their country of residence. An assistance company (AC) is a legal requirement to support medical tourists in Turkey during the treatment period, and offers alternative healthcare service providers (HSPs) that are public hospitals, private hospitals and private clinics at the first phase of the medical tourism service. …Moreover, there are specific HSPs certificated by the government, and a few number of public hospitals authenticated for medical tourism. By taking the whole above statements into consideration, HSP selection is a key decision-making point differentiating from a traditional hospital selection of a patient. Medical tourists must evaluate various criteria in order to select a proper HSP. Additionally, these decision criteria are often vague, complex, indeterminate and inconsistent information in the HSP type decision. Hence, in this study, a decision making model based on neutrosophic fuzzy sets considering HSP selection in every aspect (truthiness, indeterminacy and falsity) is suggested. Show more

Keywords: Neutrosophic fuzzy sets, decision making, medical tourists, healthcare service provider type selection

DOI: 10.3233/JIFS-189111

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6475-6485, 2020

Authors: Kalaycı, Tolga Ahmet | Asan, Umut

Article Type: Research Article

Abstract: A frequently encountered case in developing a classification model is the presence of embedded clusters, formed by data used for training. A good example for this case may be the differences in purchasing styles of e-commerce customers in a purchase propensity modelling problem. While some customers prefer a detailed research about prices, functionalities and comments, some others may need a shorter examination to make a purchase decision. Although feeding such cluster information into the classification model has been shown by recent studies to improve the prediction performance, this valuable information has been largely ignored in classical modeling techniques in general …and neural networks in particular. This paper proposes a feedforward neural network regularization method which incorporates cluster information into networks’hidden nodes. Within the forward propagation and backpropagation calculations of the network, a non-randomized matrix is used to assign hidden nodes to different observation clusters. This matrix manipulates the activation value of a hidden node for each observation in line with the observation’s membership degree to the cluster that the node is assigned to. Also, through the alternating use of randomized binary and non-randomized matrices within iterations, the proposed method successfully fulfills the regularization task. Experiments were performed for different settings and network architectures. Empirical results demonstrate that the proposed method works well in practice and performs statistically significantly better than existing alternatives. Show more

Keywords: Neural networks, fuzzy clustering, classification, regularization, machine learning

DOI: 10.3233/JIFS-189112

Citation: Journal of Intelligent &Fuzzy Systems, vol. 39, no. 5, pp. 6487-6496, 2020

Authors: Goker, Nazli | Dursun, Mehtap | Albayrak, Esra

Article Type: Research Article

Abstract: Supply chain agility is an indispensable way for the companies to quickly response to the demands of the customers. For this reason, agility of supply chain is indispensable in dynamic markets that have high scale of diversity and subjective needs. Supply chain agility needs a systemic procedure that gives priority to feedbacks of customers and follows the changes of competitors in the sector. An efficient supplier evaluation procedure is indispensable for reaching supply chain agility. Agile supplier selection needs to take into account various criteria that incorporate vagueness and uncertainty, obtaining general a multiple level hierarchical system that allows conducting …a more efficient decision analysis. Thus, in this paper an integrated fuzzy multi-criteria group decision making procedure based on quantifier-guided ordered weighted average (OWA) method and fuzzy integral, which allows incorporating uncertain data expressed as linguistic terms into the analysis, is proposed for identifying the most suitable agile supplier alternative. In group decision making issues, aggregating experts’opinions is vital to achieve more robust results. As quantifier-guided OWA method is appropriate for decision making problems under uncertain environments, it is employed for the aggregation of experts’evaluations. The developed decision procedure is illustrated via a case study performed in a dye producer in Turkish dye sector. Show more

Keywords: Imprecise data, agile supplier selection, fuzzy measure, quantifier-guided OWA, fuzzy integral

DOI: 10.3233/JIFS-189113

Citation: Journal of Intelligent &Fuzzy Systems, vol. 39, no. 5, pp. 6497-6505, 2020

Authors: Kahraman, Cengiz | Boltürk, Eda | Onar, Sezi Cevik | Oztaysi, Basar

Article Type: Research Article

Abstract: Pythagorean fuzzy sets (PFS) are an extension of intuitionistic fuzzy sets introduced by Atanassov [1 ]. PFSs have the advantage of providing larger domains for assigning membership and non-membership degrees satisfying that their squared sum is at most equal to one. PFS have been often used in modeling the problems under vagueness and impreciseness in order to better define the problems together with the hesitancy of decision makers. Different human emotions and behaviors can be modeled in humanoid robots (HR) by fuzzy sets. In this paper, facial expressions of a humanoid robot are modeled depending on the degrees of the …emotions. Larger degree of emotion causes a stronger indicator of the facial mimic. Show more

Keywords: Fuzzy sets, extensions, intuitionistic fuzzy sets, Pythagorean fuzzy sets, picture fuzzy sets, q-rung orthopair fuzzy sets, spherical fuzzy sets

DOI: 10.3233/JIFS-189114

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6507-6515, 2020

Authors: Caglayan, Nadide | Satoglu, Sule Itir | Kapukaya, E. Nisa

Article Type: Research Article

Abstract: Sales forecasting with high accuracy is crucial in many industries. Especially, in fast-moving consumer goods, retail and apparel industries, the products are not tailor-made and must be produced and made available in chain stores to the customers, in advance. Therefore, for sales and operations planning, forecast information is required. However, traditionally, time series based forecasting techniques are used that merely consider the seasonality, trend, auto-regressive and cyclic factors. This type of forecasting is not suitable especially in cases where many other factors involved and affect the product sales. In apparel retail industry, special factors such as promotions, special days, weather …(temperature), and location of the store may affect the product demands of the chain stores. The unique aspect of this study is that the sales of a product family of the fashion retail chain stores were estimated by means of artificial neural networks, for the first time in the literature. Besides, in this study, new significant factors in forecasting were explored that influence the demand of the chain stores. So, in this study, artificial neural networks are developed and used for sales forecasting of a product family of a real chain store, in Turkey. The stores exist in many cities, and some of the cities have much more stores than the other cities. The city with the highest number of stores was selected and some of the stores in this city chosen among them. The past sales, sales price and promotion data of selected stores are used. In addition, store information, number of customers visiting the store, and weather temperature data are included in the model. Sales are estimated by artificial neural networks. Besides, Regression Analysis was used for forecasting and the results of both techniques were compared. As a result of the study, the most appropriate network structure has been obtained, and a high sales forecasting performance has been reached. Show more

Keywords: Artificial neural networks, data analysis, demand forecasting, retail sectors

DOI: 10.3233/JIFS-189115

Citation: Journal of Intelligent &Fuzzy Systems, vol. 39, no. 5, pp. 6517-6528, 2020

Authors: Dogan, Onur | Oztaysi, Basar

Article Type: Research Article

Abstract: Customer-based practices enable benefits to organizations in a contentious business. Offering individualized proposals increase customer loyalty to be able to afloat. Understanding customers is a vital difficulty to perform personalized recommendations. As a demographic feature, gender information essentially cannot be captured by human tracking technologies. Hence, several procedures are improved to predict undiscovered gender information. In the research, the followed indoor paths in a shopping mall are used to predict customer genders using fuzzy c-medoids, one of the soft clustering techniques. A Levenshtein-based fuzzy classification methodology is proposed the followed paths as string data. Although some studies focused on gender …prediction, no research has centered on path-oriented. The novelty of the investigation is to analyze customer path data for the gender classes. Show more

Keywords: Gender prediction, string classification, soft clustering, path classification, levenshtein, fuzzy c-medoids

DOI: 10.3233/JIFS-189116

Citation: Journal of Intelligent &Fuzzy Systems, vol. 39, no. 5, pp. 6529-6538, 2020

Authors: Ömerali, Mete | Kaya, Tolga

Article Type: Research Article

Abstract: Since decades managers and scientists have been investigating the vertical boundaries of the firms to understand when to buy goods and services or make them internally. Since there are number of pros and cons on making or buying, the decision is very complex. Firms not only focus on the tangible terms like transaction costs and economies of scale but also consider other factors like information asymmetry, know-how protection and data source quality to keep or gain competitive advantage. Yet this isn’t simple enough, with the rapid growth of technology, the fourth industry revolution and digitalization challenge firms even further. Deciding …on digitalization strategy isn’t anywhere different than the existing make buy decision that firms have faced in the past, however this time with an increased complexity. In this article, we are aiming to understand what strategies firms should apply during their journey in industry 4.0 and a verification with an industrial case study. The purpose of this study is to suggest a Type-2 Fuzzy COPRAS methodology to aid the buy or implement decisions of firms in IOT domain. Show more

Keywords: Internet of Things, Type-2 Fuzzy COPRAS, Digitalization, Industry 4.0, Make or Buy

DOI: 10.3233/JIFS-189117

Citation: Journal of Intelligent &Fuzzy Systems, vol. 39, no. 5, pp. 6539-6552, 2020

Authors: Bolturk, Eda | Gülbay, Murat | Kahraman, Cengiz

Article Type: Research Article

Abstract: Sustainable energy selection has been a very popular problem among the researchers and various models including deterministic, probabilistic and fuzzy approaches have been developed for the solution of this problem. Fuzzy approaches to sustainable energy selection problems have been often handled in the literature. Aggregation operators for multi-expert decision making problems are an alternative solution technique for multi criteria decision making problems. Since neutrosophic and intuitionistic fuzzy aggregation operators are comparable extensions of ordinary fuzzy sets, they have been employed to aggregate multi-expert judgments. An illustrative energy selection problem is presented, solved by two approaches, and results are compared. The …same linguistic data have been used for the comparison purpose. Show more

Keywords: Fuzzy aggregation operator, multi-attribute decision making, intuitionistic fuzzy set, neutrosophic fuzzy sets, sustainable energy selection

DOI: 10.3233/JIFS-189118

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6553-6563, 2020

Authors: Jahanandish, Roya | Khosravifard, Amir | Vatankhah, Ramin

Article Type: Research Article

Abstract: This paper proposes a new method to improve fuzzy control performance accuracy in the stabilization of the two-axis gimbal system. To this end, due to the fact that the knowledge of the accurate behavior of the system plays a substantial role in fuzzy control performance, all the uncertain parameters of the dynamic model such as friction, mass imbalance and moments of inertia are estimated prior to the controller design and without imposing any computational burden on the control scheme. To estimate the uncertainties and disturbances which exist in the dynamic equations, an identification process formulated as an inverse problem is …utilized, and the Gauss– Newton method is adopted for the optimization process. Regarding the severe sensitivity of inverse problems to measurement errors, this undesirable effect is reduced by using a proper smoothing technique. In order to increase the accuracy of the final results, a novel procedure for calculation of the sensitivity coefficients of the inverse problem is proposed. This procedure is based on the direct differentiation of the governing equations with respect to the unknown parameters. At the end, simulation results are presented to confirm the effectiveness of the proposed scheme. Show more

Keywords: Fuzzy control, parameter estimation, two-axis gimbal

DOI: 10.3233/JIFS-189119

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6565-6577, 2020