Journal of Intelligent & Fuzzy Systems - Volume 42, issue 1

Authors: Şahin, Bünyamin | Şahin, Abdulgani

Article Type: Research Article

Abstract: In a graph G , a vertex v is dominated by an edge e , if e is incident with v or e is incident with a vertex which is a neighbor of v . An edge-vertex dominating set D is a subset of the edge set of G such that every vertex of G is edge-vertex dominated by an edge of D . The ev -domination number equals to the number of an edge-vertex dominating set of G which has minimum cardinality and it is denoted by γ ev  (G …). We here analyze double edge-vertex domination such that a double edge-vertex dominating set D is a subset of the edge set of G , provided that all vertices in G are ev -dominated by at least two edges of D . The double ev -domination number equals to the number of an double edge-vertex dominating set of G which has minimum cardinality and it is denoted by γ dev  (G ). We demonstrate that the enumeration of the double ev -domination number of chordal graphs is NP-complete. Moreover several results about total domination number and double ev -domination number are obtained for trees. Show more

Keywords: Trees, edge-vertex domination, double edge-vertex domination, total domination, domination

DOI: 10.3233/JIFS-219180

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 121-128, 2022

Authors: Bilgiç, Ceyda Tanyolaç | Bilgiç, Boğaç | Çebi, Ferhan

Article Type: Research Article

Abstract: It is significant that the forecasting models give the closest result to the true value. Forecasting models are widespread in the literature. The grey model gives successful results with limited data. The existing Triangular Fuzzy Grey Model (TFGM (1,1)) in the literature is very useful in that it gives the maximum, minimum and average value directly in the data. A novel combined forecasting model named, Moth Flame Optimization Algorithm optimization of Triangular Fuzzy Grey Model, MFO-TFGM (1,1), is presented in this study. The existing TFGM (1,1) model parameters are optimized by a new nature- inspired heuristic algorithm named Moth-Flame Optimization …algorithm which is inspired by the moths flying path. Unlike the studies in the literature, in order to improve the forecasting accuracy, six parameters (λ L , λ M , λ R , α , β and γ ) were optimized. After the steps of the model is presented, a forecasting implementation has been made with the proposed model. Turkey’s hourly electricity consumption data is utilized to show the success of the prediction model. Prediction results of proposed model is compared with TFGM (1,1). MFO-TFGM (1,1) performs higher forecasting accuracy. Show more

Keywords: Grey forecasting, MFO-TFGM(1, 1), parameter optimization, moth-flame optimization, TFGM (1, 1)

DOI: 10.3233/JIFS-219181

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 129-138, 2022

Authors: Fan, Ching-Lung

Article Type: Research Article

Abstract: Project managers supervise projects to ensure their smooth completion within a stipulated time frame and budget while guaranteeing construction quality. The relationships of various attributes with quality can be quantified and classified to facilitate such supervision. Therefore, this study used a data mining algorithm to analyze the relationships between defects, quality levels, contract sums, project categories, and progress in 1,015 inspection projects. In the first part, association rule mining (ARM), an unsupervised data mining approach, was used to obtain 11 rules relating two defect types (i.e., quality management system and construction quality) and determine the relationships between the four attributes …(i.e., quality level, contract sum, project category, and progress). The resulting association rule may be beneficial for construction management because project managers can use it to determine the correlations between defects and attributes. In the second part, supervised data mining techniques, namely neural network (NN), support vector machine (SVM), and decision tree (C5.0 and QUEST) algorithms, were applied to develop a classification model for quality prediction. The target variable was quality, which was divided into four levels, and the decision variables comprised 499 defects, 3 contract sums, 7 project categories, and 2 progress variables. The results indicated that five defects were important. Finally, the four indicators of gain chart, break-even point (BEP), accuracy, and area under the curve (AUC) were calculated to evaluate the model. For the SVM model, the actual value predicted by the gain chart was 96.04%, the BEP was 0.95, and the AUC was 0.935. The SVM yielded optimal classification efficiency and effectively predicted the quality level. The data mining model developed in this study can serve as a reference for effective construction management. Show more

Keywords: Data mining, association rule, classification, quality level, defect

DOI: 10.3233/JIFS-219182

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 139-153, 2022

Authors: Kuchta, Dorota | Zabor, Adam

Article Type: Research Article

Abstract: An analysis of the scientific literature on project cash flow control and fuzzy modelling shows that project cash flows are modelled using only basic approaches drawn from fuzzy theory, which may distort the credibility of the model. In this paper, we therefore propose to use the whole spectrum of fuzzy arithmetic, and to select operations that suit the nature of the cash flows in question, their dependencies and the preferences of the project manager. An analysis of the literature also shows that in practically all existing models of project costs and cash flow management, project costs and cash flows are …treated at a very high level of generality (without considering the various types of project, factors influencing their variability and signals warning of imminent cash-related problems), and estimations are not updated on an ongoing basis throughout the duration of the project. The results of a survey performed with the participation of 100 project managers show that this simplistic view of project cash flows may be distorting, and cannot guarantee the development of an efficient project cost and cash flow control system. We propose an approach that at least partially compensates for these drawbacks: it differentiates between types of project cash flows and the factors and triggers affecting changes in cash flows. Two case studies are used for a an initial verification of the approach. The paper concludes with suggestions for further research perspectives. Show more

Keywords: Fuzzy cash flow, project cash flow control, project cash flow types

DOI: 10.3233/JIFS-219183

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 155-168, 2022

Authors: Dizbay, İkbal Ece | Öztürkoğlu, Ömer

Article Type: Research Article

Abstract: Reaching a high vaccination coverage level is of vital essence when preventing epidemic diseases. For mandatory vaccines, the demand can be forecasted using some demographics such as birth rates or populations between certain ages. However, it has been difficult to forecast non-mandatory vaccine demands because of vaccine hesitation, alongside other factors such as social norms, literacy rate, or healthcare infrastructure. Consequently, the purpose of this study is to explore the predominant factors that affect the non-mandatory vaccine demand, focusing on the recommended childhood vaccines, which are usually excluded from national immunization programs. For this study, fifty-nine factors were determined and …categorized as system-oriented and human-oriented factors. After a focus group study conducted with ten experts, seven system-oriented and eight human-oriented factors were determined. To reveal the cause and effect relationship between factors, one of the multi-criteria decision-making methods called Fuzzy-DEMATEL was implemented. The results of the analysis showed that “Immunization-related beliefs”, “Media/social media contents/messaging”, and “Social, cultural, religious norms” have a strong influence on non-mandatory childhood vaccine demand. Furthermore, whereas “Availability and access to health care facilities” and “Political/ financial support to health systems” are identified as cause group factors, “Quality of vaccine and service delivery management” is considered an effect group factor. Lastly, a guide was generated for decision-makers to help their forecasting process of non-mandatory vaccine demands to avoid vaccine waste or shortage. Show more

Keywords: Vaccination demand, factor relationship, fuzzy DEMATEL

DOI: 10.3233/JIFS-219184

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 169-180, 2022

Authors: Sarucan, Ahmet | Baysal, Mehmet Emin | Engin, Orhan

Article Type: Research Article

Abstract: The membership functions of the intuitionistic fuzzy sets, Pythagorean fuzzy sets, neutrosophic sets and spherical fuzzy sets are based on three dimensions. The aim is to collect the expert’s judgments. Physicians serve patients in the physician selection problem. It is difficult to measure the service’s quality due to the variability in patients’ preferences. The patients physician preference criteria is differing and uncertainties. Thus, solving this problem with fuzzy method is more appropriate. In this study, we considered the physician selection as a multi-criteria decision-making problem. Solving this problem, we proposed a spherical fuzzy TOPSIS method. We used the five alternatives …and eight criteria. The application was performed in the neurology clinics of Konya city state hospitals. In addition, we solved the same problem by the intuitionistic fuzzy TOPSIS method. We compared the solutions of two methods with each other. We found that the spherical fuzzy TOPSIS method is effective for solving the physician selection problem. Show more

Keywords: Multi-criteria decision-making, spherical fuzzy, intuitionistic fuzzy, TOPSIS, physician selection

DOI: 10.3233/JIFS-219185

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 181-194, 2022

Authors: Ozceylan, Eren | Ozkan, Baris | Kabak, Mehmet | Dagdeviren, Metin

Article Type: Research Article

Abstract: In addition to the well-known fuzzy sets, a novel type of fuzzy set called spherical fuzzy set (SFS) is recently introduced in the literature. SFS is the generalized structure over existing structures of fuzzy sets (intuitionistic fuzzy sets-IFS, Pythagorean fuzzy sets-PFS, and neutrosophic fuzzy sets-NFS) based on three dimensions (truth, falsehood, and indeterminacy) to provide a wider choice for decision-makers (DMs). Although the SFS has been introduced recently, the topic attracts the attention of academicians at a remarkable rate. This study is the expanded version of the authors’ earlier study by Ozceylan et al. [1 ]. A comprehensive literature review …of recent and state-of-the-art papers is studied to draw a framework of the past and to shed light on future directions. Therefore, a systematic review methodology that contains bibliometric and descriptive analysis is followed in this study. 104 scientific papers including SFS in their titles, abstracts and keywords are reviewed. The papers are then analyzed and categorized based on titles, abstracts, and keywords to construct a useful foundation of past research. Finally, trends and gaps in the literature are identified to clarify and to suggest future research opportunities in the fuzzy logic area. Show more

Keywords: Spherical fuzzy sets, fuzzy logic, literature review

DOI: 10.3233/JIFS-219186

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 195-212, 2022

Authors: Türkbayrağí, Mert Girayhan | Dogu, Elif | Esra Albayrak, Y.

Article Type: Research Article

Abstract: Automotive aftermarket industry is possessed of a wide product portfolio range which is in the 4th rank by its worldwide trade volume. The demand characteristic of automotive aftermarket parts is volatile and uncertain. Nevertheless, the cause-and-effect relationship of automotive aftermarket industry has not been defined obviously heretofore. These conditions bring automotive aftermarket sales forecasting into a challenging process. This paper is composed to determine the relevant external factors for automotive aftermarket sales based on expert reviews and to propose a sales forecasting model for automotive aftermarket industry. Since computational intelligence techniques yield a framework to focus on predictive analytics …and prescriptive analytics, an artificial neural network model constructed for Turkey automotive aftermarket industry. Artificial intelligence is a subset of computational intelligence that focused on problems which have complex and nonlinear relationships. The data which have complex and nonlinear relationships could be modelled successfully even though incomplete data in case of implementation of appropriate model. The proposed ANN model for sales forecast is compared with multiple linear regression and revealed a higher prediction performance. Show more

Keywords: Sales forecasting, automotive aftermarket, artificial neural network, ANN, predictive analytics

DOI: 10.3233/JIFS-219187

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 213-225, 2022

Authors: Çakır, Esra | Ulukan, Ziya | Acarman, Tankut

Article Type: Research Article

Abstract: Determining the shortest path and calculating the shortest travel time of complex networks are important for transportation problems. Numerous approaches have been developed to search shortest path on graphs, and one of the well-known is the Dijkstra’s label correcting algorithm. Dijkstra’s approach is capable of determining shortest path of directed or undirected graph with non-negative weighted arcs. To handle with uncertainty in real-life, the Dijkstra’s algorithm should be adapted to fuzzy environment. The weight of arc -which is the vague travel time between two nodes- can be expressed in bipolar neutrosophic fuzzy sets containing positive and negative statements. In addition, …the weights of arcs in bipolar neutrosophic fuzzy graphs can be affected by time. This study proposes the extended Dijkstra’s algorithm to search the shortest path and calculate the shortest travel time on a single source time-dependent network of bipolar neutrosophic fuzzy weighted arcs. The proposed approach is illustrated, and the results demonstrate the validity of the extended algorithm. This article is intended to guide future shortest path algorithms on time-dependent fuzzy graphs. Show more

Keywords: Graph theory, Dijkstra’s algorithm, time-dependent shortest path problem, shortest travel time, fuzzy set theory, bipolar neutrosophic fuzzy number

DOI: 10.3233/JIFS-219188

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 227-236, 2022

Authors: Çakır, Esra | Taş, Mehmet Ali | Ulukan, Ziya

Article Type: Research Article

Abstract: A pandemic was declared in 2020 due to COVID-19. The most important way to deal with the virus is mass vaccination which is a complex task in terms of fast transportation and process management. Hospitals and other health centers are appropriate for vaccination process. In addition, in order to protect other patients from COVID-19 and provide rapid access to vaccines, mobile vaccination clinics can also be considered. In this study, the location assignments of mobile vaccination clinics that can serve some regions of three cities in Turkey are examined. The linear formulation of the problem is given, and the multi-facility …location problem for COVID-19 vaccination is investigated with Lagrange relaxation and modified saving heuristic algorithm. For the proposed fuzzy MCDM integrated saving heuristic, the importance of candidate locations is calculated with the aid of decision makers who give their views in spherical bipolar fuzzy information. The results of different approaches are compared, and it is intended to guide future studies. Show more

Keywords: Spherical bipolar fuzzy set, COVID-19, lagrange relaxation, modified saving heuristic algorithm, multi-facility location problem, mobile vaccination clinics

DOI: 10.3233/JIFS-219189

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 1, pp. 237-250, 2022