Rana Muhammad Zulqarnain¹, Hafiz Khalil ur Rehman², Imran Siddique³, Hijaz Ahmad^4,5, Sameh Askar⁶, Shahid Hussain Gurmani^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1863-1892, 2024, DOI:10.32604/cmes.2023.031480 - 29 January 2024

Abstract This research is devoted to diagnosing water-borne infectious diseases caused by floods employing a novel diagnosis approach, the Einstein hybrid structure of q-rung orthopair fuzzy soft set. This approach integrates parts of fuzzy logic and soft set theory to develop a robust alternative for disease detection in stressful situations, especially in areas affected by floods. Compared to the traditional intuitionistic fuzzy soft set and Pythagorean fuzzy soft set, the q-rung orthopair fuzzy soft set (q-ROFSS) adequately incorporates unclear and indeterminate facts. The major objective of this investigation is to formulate the q-rung orthopair fuzzy soft… More >

Rana Muhammad Zulqarnain¹, Wen-Xiu Ma^1,2,3,*, Imran Siddique⁴, Hijaz Ahmad^5,6, Sameh Askar⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1829-1862, 2024, DOI:10.32604/cmes.2023.030687 - 29 January 2024

Abstract Green supplier selection is an important debate in green supply chain management (GSCM), attracting global attention from scholars, especially companies and policymakers. Companies frequently search for new ideas and strategies to assist them in realizing sustainable development. Because of the speculative character of human opinions, supplier selection frequently includes unreliable data, and the interval-valued Pythagorean fuzzy soft set (IVPFSS) provides an exceptional capacity to cope with excessive fuzziness, inconsistency, and inexactness through the decision-making procedure. The main goal of this study is to come up with new operational laws for interval-valued Pythagorean fuzzy soft numbers More >

Xiaoyan Wang¹, Ahmed Mostafa Khalil^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2861-2871, 2023, DOI:10.32604/cmes.2023.026021 - 09 March 2023

Abstract The aim of this paper is to introduce the concept of a generalized Pythagorean fuzzy soft set (GPFSS), which is a combination of the generalized fuzzy soft sets and Pythagorean fuzzy sets. Several of important operations of GPFSS including complement, restricted union, and extended intersection are discussed. The basic properties of GPFSS are presented. Further, an algorithm of GPFSSs is given to solve the fuzzy soft decision-making. Finally, a comparative analysis between the GPFSS approach and some existing approaches is provided to show their reliability over them. More >

Rana Muhammad Zulqarnain¹, Imran Siddique², Rifaqat Ali³, Fahd Jarad^4,5,6,*, Aiyared Iampan⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2557-2583, 2023, DOI:10.32604/cmes.2023.023040 - 23 November 2022

Abstract Hypersoft set theory is a most advanced form of soft set theory and an innovative mathematical tool for dealing with unclear complications. Pythagorean fuzzy hypersoft set (PFHSS) is the most influential and capable leeway of the hypersoft set (HSS) and Pythagorean fuzzy soft set (PFSS). It is also a general form of the intuitionistic fuzzy hypersoft set (IFHSS), which provides a better and more perfect assessment of the decision-making (DM) process. The fundamental objective of this work is to enrich the precision of decision-making. A novel mixed aggregation operator called Pythagorean fuzzy hypersoft Einstein weighted… More >

S. A. Al blowi¹, M. El Sayed², M. A. El Safty^3,*

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 961-972, 2021, DOI:10.32604/iasc.2021.018242 - 20 August 2021

Abstract Real-world applications are now dealing with a huge amount of data, especially in the area of high-dimensional features. Trait reduction is one of the major steps in decision making problems. It refers to the determination of a minimum subset of attributes which preserves the final decision based on the entire set of attributes. Unfortunately, most of the current features are irrelevant or redundant, which makes these systems unreliable and imprecise. This paper proposes a new paradigm based on fuzzy soft relationship and level fuzzy soft relationship, called Union - Intersection decision making method. Using these More >

Rahmat Hidayat^1,2,*, Iwan Tri Riyadi Yanto^1,3, Azizul Azhar Ramli¹, Mohd Farhan Md. Fudzee¹, Ansari Saleh Ahmar⁴

Computer Systems Science and Engineering, Vol.38, No.1, pp. 119-130, 2021, DOI:10.32604/csse.2021.015628 - 01 April 2021

Abstract

Classification is one of the data mining processes used to predict predetermined target classes with data learning accurately. This study discusses data classification using a fuzzy soft set method to predict target classes accurately. This study aims to form a data classification algorithm using the fuzzy soft set method. In this study, the fuzzy soft set was calculated based on the normalized Hamming distance. Each parameter in this method is mapped to a power set from a subset of the fuzzy set using a fuzzy approximation function. In the classification step, a generalized normalized Euclidean

… More >