Journal of Intelligent & Fuzzy Systems - Volume 40, issue 6

Authors: Yavuz, Enes

Article Type: Research Article

Abstract: We define statistical Cesàro and statistical logarithmic summability methods of sequences in intuitionistic fuzzy normed spaces(IFNS ) and give slowly oscillating type and Hardy type Tauberian conditions under which statistical Cesàro summability and statistical logarithmic summability imply convergence in IFNS . Besides, we obtain analogous results for the higher order summability methods as corollaries. Also, two theorems concerning the convergence of statistically convergent sequences in IFNS are proved in the paper.

Keywords: Intuitionistic fuzzy normed space, tauberian theorem, cesàro and logarithmic summability methods, statistical convergence, slow oscillation, 03E72, 40A05, 40G05, 40G15, 40E05

DOI: 10.3233/JIFS-210596

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 12433-12442, 2021

Authors: Wang, Fang | Li, Hai-Mei | Li, Yan-Lai | Wu, Ai-Ping

Article Type: Research Article

Abstract: Quality function deployment (QFD) is a customer-oriented tool for developing products. Based on the idea of the best-worst method (BWM), a novel model is developed to determine the relative importance ratings (RIRs) of customer requirements (CRs) with interval grey linguistic (IGL) information, which plays a significant role in QFD. CRs are rated with IGL variables, and the degree of greyness degree function that can be used to handle the IGL variables is defined based on the power utility function. Then, considering customer heterogeneity, a model is constructed to derive the RIRs of CRs by following the logic of the BWM. …Finally, a case study of 5 G smartphone development is provided to verify the validity and the feasibility of the proposed method. Show more

Keywords: Customer requirements, QFD, interval grey linguistic, best-worst method, utility function

DOI: 10.3233/JIFS-210799

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 12443-12458, 2021

Authors: Lu, Hanchuan | Khalil, Ahmed Mostafa | Alharbi, W. | El-Gayar, M. A.

Article Type: Research Article

Abstract:  In this article, we propose a novel concept of the generalized picture fuzzy soft set by combining the picture fuzzy soft set and the fuzzy parameter set. For possible applications, we explain five kinds of operations (e.g., subset, equal, union, intersection, and complement) based on generalized picture fuzzy soft sets. Then, we establish several theoretical operations of generalized picture fuzzy soft sets. In addition, we present the new type by using the AND operation of the generalized picture fuzzy soft set for fuzzy decision-making and clarify its applicability with a numerical example. Finally, we give a comparison between the picture …fuzzy soft set theory and the generalized picture fuzzy soft set theory. It is shown that our proposed (i.e., generalized picture fuzzy soft set theory) is viable and provide decision makers a more mathematical insight before making decisions on their options. Show more

Keywords: Picture fuzzy set, soft set, generalized picture fuzzy soft set, Algorithm 1, Algorithm 2, decision-making

DOI: 10.3233/JIFS-201706

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 12459-12475, 2021

Authors: Hamdoun, Hala | Sagheer, Alaa | Youness, Hassan

Article Type: Research Article

Abstract: Machine learning methods have been adopted in the literature as contenders to conventional methods to solve the energy time series forecasting (TSF) problems. Recently, deep learning methods have been emerged in the artificial intelligence field attaining astonishing performance in a wide range of applications. Yet, the evidence about their performance in to solve the energy TSF problems, in terms of accuracy and computational requirements, is scanty. Most of the review articles that handle the energy TSF problem are systematic reviews, however, a qualitative and quantitative study for the energy TSF problem is not yet available in the literature. The purpose …of this paper is twofold, first it provides a comprehensive analytical assessment for conventional, machine learning, and deep learning methods that can be utilized to solve various energy TSF problems. Second, the paper carries out an empirical assessment for many selected methods through three real-world datasets. These datasets related to electrical energy consumption problem, natural gas problem, and electric power consumption of an individual household problem. The first two problems are univariate TSF and the third problem is a multivariate TSF. Compared to both conventional and machine learning contenders, the deep learning methods attain a significant improvement in terms of accuracy and forecasting horizons examined. In the meantime, their computational requirements are notably greater than other contenders. Eventually, the paper identifies a number of challenges, potential research directions, and recommendations to the research community may serve as a basis for further research in the energy forecasting domain. Show more

Keywords: Energy time series forecasting, conventional forecasting methods, machine learning, deep learning, energy management systems

DOI: 10.3233/JIFS-201717

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 12477-12502, 2021

Authors: Zhang, Na | Yan, Shuli | Fang, Zhigeng | Yang, Baohua

Article Type: Research Article

Abstract: In view of the situation that tasks or activities in the GERT model may have multiple realizations, this paper explores the time dependence of each repeated execution node under the condition of fuzzy information, and studies the characteristics of the z-tag fuzzy GERT model and its analytic algorithm. Firstly, the F-GERT model related to the number of executions of activities is defined, and the simplified rules, related properties and theorems of the network model are examined. Secondly, solving algorithm, conditional moment generating function and process arrival time of the F-GERT model for repeated execution time are studied. Finally, the application …of F-GERT queuing system based on element execution time in weapon equipment management is discussed. The feasibility and effectiveness of the model and algorithm are verified by the practical application of the project. Show more

Keywords: Project management, GERT model, fuzzy information, z-tag, moment generating function, network structure

DOI: 10.3233/JIFS-201731

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 12503-12519, 2021