Designing a general type-2 fuzzy expert system for diagnosis of depression
طراحی سیستم تخصصی فازی نوع 2 برای تشخیص افسردگی-2019
Depression is a common and important mental disorder that affects the quality of human life. Since people with depression are not aware of their disorder and sometimes suffer from physical symptoms such as chronic pain, refer to a physician instead of a psychologist. Hence, physician’s diagnosis is not always correct in all patients. In the other words, misdiagnosis may occur by mislabeling their mental disorder as physical diseases. Delay in depression diagnosis may have irrecoverable outcomes such as suicide. Therefore, the most challenging aspect of depression diagnosis is to limit time loss and preserve accuracy. In this paper, a novel general type-2 fuzzy expert system for depression diagnosis, considering two main objectives, was developed. These objectives include accuracy of the system and diagnosis time. The proposed system might be a helpful guideline for the physician to lead patients toward psychologist by asking 15 questions from patients. The proposed general Type-2 expert system has five steps. In the first step, we generate general type-2 membership function by using zSlices method and interval agreement approach (IAA). Then fuzzy rules are extracted out of data gathered from hospital and we extend Mendel method briefly in the second step. Approximate reasoning is applied in the third step. In the fourth step, we solve a multi-objective problem to minimize time and maximize accuracy by using MOEA/D method. Accordingly, in order to minimize time, feature selection is applied. In this process, we use MIFS (Mutual Information Feature Selection) method and briefly, we extend it. In the final step, we choose an appropriate solution from achieved Pareto Front (PF). The proposed general type-2 expert system has been tested and evaluated to show its performance. This Intelligent system is able to diagnose depression accurately at a suitable time.
Keywords: Depression Computing with words (CWW) | General type-2 fuzzy sets | zSlices | MOEA/D algorithm | Feature selection | Beck Depression Inventory-II test (BDI-II) | Adaptive system | Expert system
Design and implementation of an expert system for periodic and emergency control under uncertainty: A case study of city gate stations
طراحی و اجرای سیستم خبره برای کنترل دوره ای و اضطراری تحت عدم اطمینان: مطالعه موردی ایستگاه های دروازه شهر-2019
Safety analysis is essential in the natural gas transmission industry to guarantee effective hazard identification and to prevent the failure of components in advance. The overall aim of this research is to introduce a new hybrid expert system and fuzzy logic to monitor city gate stations as one of the most vital installations of gas distribution networks. The proposed model utilizes fuzzy if-then rules based on multiple experts opinions to study the compound interrelations between the mechanical and physical elements of city gate stations. The presented expert system accounts for uncertainty associated with the experts’ judgments by fuzzy sets theory. The expert system is implemented in an object-oriented platform and is programmed with C#. The validity of the expert system is confirmed using simulation experiments through a case study of city gate stations.
Keywords: City gate stations | Fuzzy expert system | Gas industry | Decision tree Uncertainty | Inference chain
Analysis of balanced scorecard-based SERVQUAL criteria based on hesitant decision-making approaches
تجزیه و تحلیل معیارهای SERVQUAL مبتنی بر کارت امتیازی متعادل بر اساس رویکردهای تصمیم گیری مردد-2019
The measurement of quality of services has an important influence in the companies’ competence, being even more relevant in the banking sector because of the high competition to keep and attract customers. Due to this fact, this paper proposes a balanced scorecard based SERVQUAL to rank competitors in the banking sector. The analysis will deal with hesitant fuzzy information that models the hesitancy of the experts involved. This analysis will be applied for weighting criteria and dimensions, ranking alternatives and different results that will define the Turkish banking sector. Its main goal is to show that banks should be more willing to help and support their customers to increase the quality of their services. Therefor the analysis aims at showing which is the most relevant factor in the balanced scorecard based-SERVQUAL dimensions according to the correlation coefficient? It also aims at providing a clear view about what type of actions should take banks to be closer to the customers. Additionally, it will be identified which is the importance of the different dimensions of the approach? Eventually the main conclusions obtained from the analysis will be detailed regarding the quality services offered by banks in Turkey and different recommendations will be elicited to increase the banks performance in service quality according to the criteria and dimensions emphasized in this study.
Keywords: Multi-criteria decision making | SERVQUAL | Hesitant fuzzy sets | DEMATEL | VIKOR
An integrated stochastic fuzzy MCDM approach to the balanced scorecard-based service evaluation
یک رویکرد MCDM فازی تصادفی یکپارچه برای ارزیابی خدمات مبتنی بر کارت امتیازی متعادل-2019
The purpose of the study is to analyse the balanced scorecard (BSC)-based evaluation of the new service development (NSD) in Turkish banking sector. The proposed model includes fuzzy ANP (FANP), Monte Carlo Simulation, fuzzy TOPSIS (FTOPSIS), and fuzzy VIKOR (FVIKOR) respectively. FANP has been used for weighting the criteria, Monte Carlo Simulation has been applied to provide the stochastic values of BSC-based dimensions of NSD in banking sector. FTOPSIS and FVIKOR have been considered to rank the banks by their dimension performances. The novelty of the study is to provide an integrated model including FANP, FTOPSIS, FVIKOR, and Monte Carlo Simulation respectively. Additionally, BSC-based analysis of NSD has been applied for evaluating Turkish banking sector. The results demonstrate that the comparative analysis is coherent for ranking the alternatives and the stochastic values facilitate to obtain the immense expert evaluations under the fuzzy environment. It is identified that the performance of the foreign banks is lower than private and state banks. Hence, it can be said that especially foreign banks should develop new services to attract the attention of their customers. Within this framework, customer expectations should be defined by conducting a detailed analysis. As a result, it can be possible to increase comparative advantage in comparison with the other banks.
Keywords: Balanced scorecard | New service development | Turkey | Banking | Monte Carlo simulation | Fuzzy sets
Survey on fuzzy TOPSIS state-of-the-art between 2007 and 2017
مرور وضعیت TOPSIS فازی بین سالهای 2007 و 2017-2019
A crucial topic in expert system and operations research is fuzzy multi-criteria decision making (FM- CDM), which is used in different fields. Existing options and gaps in this topic must be understood to prepare valuable knowledge on FMCDM environments and assist scholars. This study maps the research landscape to provide a clear taxonomy. The authors focus on searching for articles related to (i) technique for order of preference by similarity to ideal solution (TOPSIS); (ii) development; and (iii) fuzzy sets in four primary databases, namely, IEEE Xplore, Web of Science, Elsevier ScienceDirect and Springer. These databases include literature that focuses on FMCDM. The resulting final set after the filtering process in- cludes 170 articles, which are classified into four categories. The first, second, third and fourth categories include articles that used a type-1 fuzzy set with the TOPSIS method, a type-2 fuzzy set with the TOPSIS method, two fuzzy membership functions and a survey paper, respectively. The basic attributes of this topic include motivations for utilising FMCDM, open challenges and limitations that obstruct utilisation and recommendations to researchers for increasing the approval and application of FMCDM.
Keywords: Multi-criteria decision making | Fuzzy set | FMCDM | Fuzzy-TOPSIS
An intuitionistic fuzzy set based hybrid similarity model for recommender system
مدل شباهت ترکیبی مبتنی بر مجموعه فازی شهودی برای سیستم توصیه گر-2019
In general, a practical online recommendation system does not rely on only one algorithm but adopts dif- ferent types of algorithms to predict user preferences. Although most of similarity measures can rapidly calculate the similarity on the basis of co-rated items, their prediction accuracy is not satisfactory in the case of sparse datasets. Making full use of all the rating information can effectively im prove the rec- ommendation quality, but it reduces the system efficiency because all the ratings need to be calculated. To recommend items for target users rapidly and accurately, this paper designs a hybrid item similarity model that achieves a trade-offbetween prediction accuracy and efficiency by combining the advantages of the two above-mentioned methods. First, we introduce an adjusted Google similarity to rapidly and precisely calculate the item similarity in the condition of enough co-rated items. Subsequently, an intu- itionistic fuzzy set (IFS) based Kullback–Leibler (KL) similarity is presented from the perspective of user preference probability to effectively compute the item similarity in the condition of rare co-rated items. Finally, the two proposed schemes are integrated by an adjusted variable to comprehensively evaluate the similarity values when the number of co-rated items lies in a certain range of value. The proposed model is implemented and tested on some benchmark datasets with different thresholds of co-rated items. The experimental results indication that the proposed system has a favorable efficiency and guarantees the quality of recommendations
Keywords: Recommender system | Collaborative filtering | Normalized Google distance | Intuitionistic fuzzy set | Kullback–Leibler divergence
Introducing a new method for the fusion of fraud evidence in banking transactions with regards to uncertainty
معرفی یک روش جدید برای ادغام شواهد کلاهبرداری در معاملات بانکی با توجه به عدم اطمینان-2019
Detection of fraudulent transactions is a vital factor for financial institutions, and finding more effective and accurate methods is of tremendous importance. The use of supervised data mining techniques is not feasible in many cases due to the lack of access to labeled data. Fraud detection is a complex task, and unsupervised methods like clustering and outlier detection techniques employed alone do not yield sat- isfactory results. Another issue is epistemic uncertainty due to the absence of sufficient information on the behavioral aspects of different customers, which also leads to poorer results for fraud detection and makes the fraud detection system inapplicable in real world environment. In this paper, using multi cri- teria decision method, intuitionistic fuzzy set, and evidential reasoning, a new method for detection of fraud was introduced, which infuses several behavioral evidence of a transaction concerning the effect of uncertainty for them. Transactional behavior was modeled by considering the trends of different main and aggregated variables at different periods and the extent of deviation of the new arrived transaction from each of these trends were considered as behavioral evidence. The final belief, which is the result of the combination of much evidence using the proposed method, will determine the originality of a newly arrived transaction. Finally, using a real world dataset, the results of the new method were compared with the results of Dempster–Shafer method in terms of the number of frauds discovered and the num- ber of erroneous alerts they issued. The findings showed that the method introduced in this study has higher accuracy and lower false alarms compared to Dempster–Shafer method while the computational complexity of this method makes its implementation time longer.
Keywords: Fraud detection | IFS | DST | Uncertainty | Evidential reasoning
A hybrid multi-criteria decision making model for elective admission control in a Chinese public hospital
یک مدل تصمیم گیری چند معیار ترکیبی برای کنترل پذیرش انتخابی در یک بیمارستان عمومی چین-2019
In healthcare service systems, patients are not always served in the order they arrive, but are ranked with respect to their relative ‘‘importance’’ and ‘‘urgency’’ to the service system. We consider such a system where elective admission requests backlogged on a list wait to be assigned inpatient beds. To consolidate the performance of Classified Diagnose and Treatment in China, determining an optimal admission priority assignment policy for all waiting patients is vital. It is a complicated multi-criteria decision making (MCDM) problem involving both qualitative and quantitative criteria. Evaluating the admission priority of each patient is based on vague information or uncertain data in which significant dependence and feedback between the evaluation dimensions and criteria may exist. This paper applies a hybrid MCDM model that integrates the 2-tuple DEMATEL technique and the fuzzy VIKOR method to the elective admission control problem. It makes use of the modified 2-tuple DEMATEL to determine the relative weights of the evaluation criteria and the fuzzy VIKOR method to assess the alternatives (waiting patients) over the criteria. An empirical case in West China Hospital is presented to demonstrate the applicability of the proposed approach. Sensitivity analysis of the results by the proposed hybrid MCDM model and comparative analysis with other different approaches are presented. The results show that the proposed model is effective and provides insightful implications for hospital managers to refer.
Keywords: Fuzzy sets | Fuzzy systems | Medical decision-making | Medical expert systems | Medical services
Pythagorean fuzzy VIKOR approaches based on TODIM for evaluating internet banking website quality of Ghanaian banking industry
رویکردهای VIKOR فازی Pythagorean مبتنی بر TODIM برای ارزیابی کیفیت وب سایت بانکی اینترنتی صنعت بانکی غنا-2019
With the rapid development of Internet banking technology in Ghana, the website quality evaluation is the essential core of the customer, which is regarded as a multi-criteria decision making (MCDM) problem. Due to the uncertainty of Internet banking, the evaluation of criteria may be measured by Pythagorean fuzzy numbers (PFNs). In addition, the customer usually does not exhibit complete rationality in the decision procedure. Based on the traditional VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje) method of MCDM, this paper provides a new perspective of a compromised solution, which can handle the decision maker’s psychological behavior by inducing TODIM (a Portuguese acronym meaning Interactive Multi-Criteria Decision Making). By defining Pythagorean fuzzy entropy and cross-entropy measures, we study the determination of the weights of the criteria in advance. Then, considering the psychological behavior of the customer, we design two types of strategies for the combination between TODIM and VIKOR. Meanwhile, the corresponding methods have been developed, i.e., Approaches I and II. After that, a simulated example of ranking Internet banking websites in the Ghanaian banking industry is given to illustrate the validity and applicability of our proposed approaches. Finally, we utilize the Wilcoxon signed-rank test and then discuss the differences among VIKOR, TODIM and our proposed methods.
Keywords: Pythagorean fuzzy sets | VIKOR | TODIM | Multi-criteria decision making | Internet banking
Modelling firms’ interventions in ISO 9001 certification: A configurational approach
مدسازی مداخلات شرکتها در گواهی نامه ایزو 9001: یک دیدگاه پیکربندی-2018
Firms are subject to various external audits and certifications, which provide an external assessment of firms’ operational practices. The literature has focused so far on immediate effects of external certifications overlooking the patterns of activities and interventions that firms pursue to maintain their certifications. In this paper, we employ the configurational approach to empirically test a theory on firms’ intervention in the maintenance stages of ISO 9001 certification. The theory is causally asymmetric in nature and examines causal configurations of antecedent conditions (firms size, year certified, institutional pressure, board pressure, motivation and complexity of firm’s operations) that result in firms’ pursuit of more (or less) complex interventions and firms’ high (or low) intensity of interventions. Using a fuzzy set Qualitative Comparative Analysis (fsQCA) and in-depth data from 15 cases, the study reveals strong support for causal asymmetry, complexity and equifinality and provides nine models to explain complexity and intensity of firms’ interventions. The study addresses two gaps in the literature – maintenance stages of certification are poorly understood and a configurational approach is largely lacking in studies on voluntary certification.
keywords: ISO 9001 |Third party certification |Qualitative comparative analysis |Intervention