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

Authors: Uzun, Ibrahim Mert | Cebi, Selcuk

Article Type: Research Article

Abstract: Risk identification and risk assessment are the most important issues among the occupational health and safety practices. In the industry, the identification of hazards and the risk assessment are often carried out by using subjective risk assessment methods. These methods usually do not provide a perspective on the nature of the measures to be taken. In order to keep sector-specific risks under control, as important as the assessment of risks is to take effective measures against these risks and to continuously monitor the effectiveness of these measures. Therefore, the main objective of this paper is to classify protective and preventive …occupational health and safety measures implemented in the construction sector based on their efficiency by using Fuzzy Kano Model Approach. For this purpose, it is the first time, the feature classes defined by the conventional Kano Model and the Kano Model questionnaire have been reinterpreted in terms of occupational health and safety. Then, the proposed approach has been applied to classify the safety measures utilized in occupational health and safety in terms of their efficiency by using fuzzy Kano Model. According to obtain results, approximately 10% of the control measures which are effectively used at construction site are in Trusting Measure Class. The main contribution of this paper is to provide a new method for analysis of effectiveness of the occupational health and safety measures. Show more

Keywords: Safety measures, fuzzy kano model, accident prevention, construction accidents

DOI: 10.3233/JIFS-179432

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 589-600, 2020

Authors: Ohta, Robison | Salomon, Valerio A.P. | Silva, Messias B.

Article Type: Research Article

Abstract: A multi-criteria problem involves the consideration of two or more criteria in the prioritization of alternative solutions. The Analytic Hierarchy Process (AHP) is a leading multi-criteria method. Consistency checking is a great advantage of AHP. Since in AHP priorities come from pairwise comparisons, it is possible to check the consistency of these comparisons. However, a problem occurs when comparisons fail the consistency check. Then, the excluding options are to review some comparisons (Option 1) or to keep the comparisons (Option 2). This paper presents an AHP application in the maintenance management of an industrial plant. Industrial maintenance is not in …the core business of an organization. However, maintenance costs can account over 50% of production costs. One of the first maintenance management decisions is on the maintenance strategy. Shall maintenance anticipate the occurrence of failure? Or shall maintenance be performed after an equipment breakdown? Answering those questions with classical AHP resulted in inconsistent comparison matrices. In that case, Fuzzy AHP (FAHP) were applied, avoiding this situation. Therefore, the purpose of this paper is to present the applications of four AHP models: Classical AHP and three models of FAHP, including hesitant fuzzy sets and intuitionistic fuzzy sets. The application of Hesitant FAHP (HFAHP) and Intuitionistic FAHP (IFAHP) are the novelty of this paper. The four AHP models were also applied in the same case of maintenance management of an industrial plant. Results were very similar, but experts could express their preferred model. Show more

Keywords: Analytic hierarchy process, hesitant fuzzy sets, intuitionistic fuzzy sets, maintenance management

DOI: 10.3233/JIFS-179433

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 601-608, 2020

Authors: Türkşen, Özlem

Article Type: Research Article

Abstract: Obtaining interval estimates of nonlinear model parameters is as important as point estimates of model parameters. Because the estimated value of the parameters cannot always be expressed as a single numerical quantity exactly. In this study, it is aimed to propose an interval estimation procedure for nonlinear model parameters with combining soft computing methods instead of using probabilistic assumptions. For this purpose, response and model parameters were presented as triangular fuzzy numbers (TFNs) in nonlinear regression model. The errors were defined as intervals through alpha-cut operations and minimized according to the least absolute deviation (LAD) metric. The novelty of the …study is achieving the minimization in a multi-objective framework in which the objective functions are lower and upper bound of interval type error functions. The NSGA-II (Non-dominated Sorting Genetic Algorithm-II) and the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods were used for multi-objective optimization (MOO) and multi-criteria decision making (MCDM) stages, respectively. Innovatively, in order to obtain reasonable interval estimates, predefined sized compromise solution set was composed and the fuzzy C-means (FCM) clustering algorithm was applied to the compromise set of interval estimates according to the predicted alpha-cut values. The proposed interval estimation approach is applied on a synthetic and a real data sets for application purpose. Show more

Keywords: Interval estimates of nonlinear model parameters, fuzzy nonlinear regression, fuzzy alpha-cut, NSGA-II, TOPSIS, FCM

DOI: 10.3233/JIFS-179434

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 609-618, 2020

Authors: Vij, Sonakshi | Jain, Amita | Tayal, Devendra | Castillo, Oscar

Article Type: Research Article

Abstract: The concept of Hesitant Fuzzy Sets (HFS) came into picture where a set is created of the possible membership values that are willing to participate for contribution to the fuzzy sets. HFS has recently become very popular between researchers who are working on variants of fuzzy logic. This paper highlights the research queries related to the Scientometric analysis of HFS by studying 410 research publications from the Web of Science (v.5.31) database (from inception of Web of Science online data till 2017). This paper answers questions pertaining to the important terms and concepts for HFS, co-authorship patterns in HFS, dominating …research areas of HFS, and countries with maximum research paper contribution, co-citation patterns for first authors and bibliographical coupling for organizations. A brief outline of the citation analysis is also made in the form of a sub-section. Show more

Keywords: Fuzzy logic, hesitant fuzzy sets, HFS, Scientometric analysis

DOI: 10.3233/JIFS-179435

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 619-626, 2020

Authors: Aydın, Serhat | Kabak, Mehmet

Article Type: Research Article

Abstract: Investment analysis is a process of choosing the best alternative among investment alternatives that provide the best fit for a company. The process contains uncertainty, vagueness, fuzziness and insufficient data; therefore, this evaluating process needs experts’ knowledge and judgments. Fuzzy set theory is a useful technique to capture experts’ evaluations. This paper proposes the new present worth and future worth analysis techniques with single valued neutrosophic set. The proposed techniques allow using possible values of alternatives’ data and membership function of alternatives assigned by experts. The techniques provide the literature with a new multiplication operator and a new term under …the name “neutrosophic equivalent”. An illustrative example shows the applicability of the techniques. Comparison analyses are realized with classical and simplified neutrosophic present and future worth techniques. The comparison results show that the proposed techniques overcome investment analysis problems effectively and efficiently. Show more

Keywords: Investment analysis, present worth analysis, future worth analysis, neutrosophic sets, fuzzy sets

DOI: 10.3233/JIFS-179436

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 627-637, 2020

Authors: Nguyen, Hoang

Article Type: Research Article

Abstract: The arithmetic operations on intuitionistic fuzzy sets defined by Atanassov are the most popular in the intuitionistic fuzzy set theory. Based on these operations, many commonly used methods for solving the decision-making (DM) problems under intuitionistic fuzzy environment have been developed and various aggregation operators have been proposed. However, there have been revealed some undesirable properties of these operators, such as the inconsistency with the operations on the ordinary fuzzy sets (FSs), the non-monotonicity of the addition and multiplication operations or non-monotonicity under multiplication by a scalar. We show in this paper that these drawbacks pertain to also the recently …proposed combined aggregations operators such as intuitionistic fuzzy Heronian mean (IFHM), intuitionistic fuzzy interaction partitioned Bonferroni mean (IFIPBM), intuitionistic fuzzy Dombi Bonferroni mean (IFDBM), intuitionistic fuzzy Maclaurin symmetric mean (IFMSM), Pythagorean fuzzy Maclaurin symmetric mean (PFMSM), q-rung orthopair fuzzy power Maclaurin symmetric mean (q-ROFPMSM), Muirhead mean (IFWMM) and intuitionistic fuzzy hybrid weighted arithmetic and geometric aggregation operators (IFHWAGA).This paper proposes some new arithmetic operations on Atanassov’s intuitionistic fuzzy sets that have good algebraic properties, such as idempotency, commutativity, monotonicity and monotonicity under multiplication by a scalar. Based on the proposed operations, the intuitionistic fuzzy weighted arithmetic mean and intuitionistic fuzzy weighted geometric mean operators with the acceptable properties are developed. Some illustrative examples are performed to demonstrate effectiveness and reliability of our method. Finally, in order to verify the validity of the proposed method in solving real-life DM problems, an application example is conducted with a comparative analysis with other existing methods. Show more

Keywords: Intuitionistic fuzzy sets, operations, aggregation operator, decision making

DOI: 10.3233/JIFS-179437

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 639-651, 2020

Authors: Goker, Nazli | Dursun, Mehtap | Cedolin, Michele

Article Type: Research Article

Abstract: Companies should cope with uncertain and unpredictable changes while improving responsiveness capability to survive in dynamic market conditions. In recent years, agility concept becomes more and more popular to meet these requirements in management as well as manufacturing. From supply chain viewpoint, collaborating with agile suppliers is principal for constructing an agile supply chain, which is flexible, quick, and responsive. This paper aims to identify the most suitable agile supplier alternative by introducing a novel distance based hierarchical intuitionistic decision making procedure. The proposed methodology, which deals with uncertain and vague data, allows to represent hesitation by using intuitionistic fuzzy …numbers rather than fuzzy numbers that fail to take into account hesitancy. The causal links among evaluation criteria are expressed with intuitionistic fuzzy cognitive map tool that enables to yield the importance degree of each criterion. Moreover, the hierarchical representation of the decision making problem provides an effective analysis with the presence of numerous criteria that are to be considered. The distance based framework is to minimize the distance to the ideal solution while maximizing the distance from the anti-ideal solution in order to determine the most appropriate agile supplier alternative. The case study is conducted in a dye manufacturer that performs in Turkish dye industry. Show more

Keywords: Intuitionistic fuzzy sets, intuitionistic fuzzy cognitive map, hierarchical decision making, agile supplier selection

DOI: 10.3233/JIFS-179438

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 653-662, 2020

Authors: Faizi, Shahzad | Rashid, Tabasam | Zafar, Sohail

Article Type: Research Article

Abstract:  The hesitant 2-tuple linguistic set (H2TLS) as an important extension of the 2-tuple linguistic model, can effectively express the judgments of the decision makers (DMs) not only in qualitative aspects but also reflect the vagueness and hesitancy by assigning more than one translation parameters to every linguistic variable of the linguistic term set (LTS). The aim of this study is to extend the TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) method, to solve multi-criteria group decision making (MCGDM) problems in the context of H2TLSs with completely unknown criteria weights. The TODIM method is developed on the …basis of prospect theory which can effectively capture the psychological behavior of DMs during the decision analysis. In order to enhance the suitability and applicability of H2TLSs, this paper investigates first the generalized distance measure between hesitant 2-tuple linguistic elements (H2TLEs). Furthermore, a score function for H2TLEs is proposed and the dominance relations are defined by using this function. A TODIM method is established that can greatly help in solving MCGDM problems in which alternatives are assessed in the form of H2TLEs in the presence of certain criteria. A procedure for determining the criteria weights is also established as a follow up. Finally, a numerical example is offered and a comparison analysis of proposed extended TODIM method is made with other methods to check the validity and practicality of the proposed study. Show more

Keywords: Hesitant 2-tuple linguistic set, score function, generalized distance measure, multi-criteria group decision making, TODIM method

DOI: 10.3233/JIFS-179439

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 663-673, 2020

Authors: Dogan, Onur | Oztaysi, Basar | Fernandez-Llatas, Carlos

Article Type: Research Article

Abstract:  There are some studies and methods in the literature to understand customer needs and behaviors from the path. However, path analysis has a complex structure because the many customers can follow many different paths. Therefore, clustering methods facilitate the analysis of the customer location data to evaluate customer behaviors. Therefore, we aim to understand customer behavior by clustering their paths. We use an intuitionistic fuzzy c-means clustering (IFCM) algorithm for two-dimensional indoor customer data; case durations and the number of visited locations. Customer location data was collected by Bluetooth-based technology devices from one of the major shopping malls in Istanbul. …Firstly, we create customer paths from customer location data by using process mining that is a technique that can be used to increase the understandability of the IFCM results. Moreover, we show with this study that fuzzy methods and process mining technique can be used together to analyze customer paths and gives more understandable results. We also present behavioral changes of some customers who have a different visit by inspecting their clustered paths. Show more

Keywords: Fuzzy c-means clustering, intuitionistic fuzzy sets, process mining, customer behaviors, indoor locations

DOI: 10.3233/JIFS-179440

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 675-684, 2020

Authors: Luo, Minxia | Wu, Lixian | Fu, Li

Article Type: Research Article

Abstract: A new distance metric between interval-valued fuzzy sets is proposed. The four special logic metric spaces based on the distance are structured. we analysis and compare the structures of the four logic metric spaces. It is shown that the Łukasiewicz logic metric space and Goguen logic metric space are more suitable for interval-valued fuzzy reasoning. Moreover, the robustness of interval-valued fuzzy reasoning triple I methods are studied in the two logic metric spaces. We prove that fuzzy reasoning triple I methods based on the interval-valued Łukasiewicz residuated implication and interval-valued Goguen residuated implication are robust.

Keywords: Interval-valued fuzzy sets, distance metric, fuzzy metric spaces, triple I method, robustness

DOI: 10.3233/JIFS-179441

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 685-696, 2020