Article
Automation & Control Systems
Jawad Ali, Harish Garg
Summary: The paper presents a novel decision-making algorithm called MCDM-TAOV, which uses matrix norms to define new distance measures and solves the problems of existing distance measures. The superiority of the proposed measures is demonstrated by providing several counter-intuitive examples. Furthermore, the paper introduces the Total Area based on Orthogonal Vector (TAOV) methodology to solve multi-criteria decision-making (MCDM) problems and presents a distance-based criteria weight determination method. The practical applicability, comparative analysis, and advantages of the study are demonstrated by assessing the third-party reverse logistics provider problem.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Brindaban Gohain, Rituparna Chutia, Palash Dutta
Summary: Decision-making in uncertain conditions is challenging, and intuitionistic fuzzy sets play a crucial role in managing uncertainty. Distance measures of IFSs are used in various decision-making problems, and a new symmetric distance formula has been proposed for effectively determining the distance between information held by IFSs. The proposed measure follows axiomatic definitions of a distance measure and can be applied in diverse decision-making problems.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Engineering, Aerospace
Zhanhao Zhang, Fuyuan Xiao
Summary: D-S evidence theory is a general framework for reasoning with uncertainty, which combines evidence from different information sources to derive a degree of belief function. However, the disordered mass assignments from unknown sources raise the question of how to measure the difference between them. This paper proposes a novel distance-based measure called Information Volume Distance (IVD) inspired by the information volume, which not only meets the properties of distance but also proves its superiority through simulation experiments. Based on IVD, a new multi-source information algorithm is proposed for information fusion, and its effectiveness is verified by comparing it with other methods in decision-making.
CHINESE JOURNAL OF AERONAUTICS
(2023)
Article
Computer Science, Artificial Intelligence
Zhinan Hao, Zeshui Xu, Hua Zhao, Ren Zhang
Summary: This paper proposes a context-based distance measure for intuitionistic fuzzy sets and defines a new similarity measure to enhance discrimination capability. The effectiveness of these methods is validated through a practical case study, demonstrating their fine discrimination ability and effectiveness.
APPLIED SOFT COMPUTING
(2021)
Article
Mathematics, Applied
Muhammad Naeem, Muhammad Qiyas, Lazim Abdullah, Neelam Khan, Salman Khan
Summary: Aggregation operators are effective mathematical tools for combining multiple variables into a single result. Spherical fuzzy sets and rough sets are common mathematical tools for handling incomplete and ambiguous information. We introduce the concepts of spherical fuzzy rough Hamacher averaging and geometric operators, and provide a detailed description of their key characteristics. We also propose an algorithm for solving multi-criteria group decision making problems.
Article
Mathematics, Applied
Changlin Xu, Yaqing Wen
Summary: This paper firstly defines a new distance measure for circular intuitionistic fuzzy sets based on the theory of circular intuitionistic fuzzy sets, considering the information of four aspects: membership degree, non-membership degree, radius and the assignment of hesitation degree, and proves that the new distance satisfies the distance measure conditions. Secondly, by constructing a manual testing framework, the new distance is analyzed in comparison with the existing distance metric to show the rationality of the new method. Finally, the method is applied to fuzzy multi-criteria decision making to further demonstrate the effectiveness and practicality of the method.
Article
Computer Science, Artificial Intelligence
Iman Mohamad Sharaf
Summary: Pythagorean fuzzy sets (PFSs) have proven to be effective in handling uncertainty and vagueness in multi-criteria group decision-making (MCGDM). This study introduces a new approach called the differential measure (DFM) for comparing PFSs, aiming to eliminate unfair arguments resulting from the equal treatment of contradicting parameters. The study also proposes a novel method for MCGDM based on the introduced DFM, along with a technique for computing expert weights. The applicability and validity of the method are demonstrated through two applications and comparison with existing methods.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Kiran Zahid, Muhammad Akram, Cengiz Kahraman
Summary: This study extends the complex spherical fuzzy set theory using the ELECTRE method, and proposes a multi-purpose complex spherical fuzzy ELECTRE II approach. The effectiveness of the proposed method is demonstrated through a case study.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Muhammad Akram, Ghous Ali, Xindong Peng, Muhammad Zain Ul Abidin
Summary: This paper introduces a new hybrid model for multinary data evaluation and multi-attribute group decision-making, discussing fundamental properties and illustrating the proposed concepts with detailed examples.
ARTIFICIAL INTELLIGENCE REVIEW
(2022)
Article
Multidisciplinary Sciences
Xiang Li, Zhe Liu, Xue Han, Nan Liu, Weihua Yuan
Summary: In this paper, a new distance measure called D-IFS is proposed to measure the similarities or differences between intuitionistic fuzzy sets (IFSs). Numerical examples show that D-IFS can obtain more reasonable and superior results. Moreover, a new decision-making method based on D-IFS is developed and its performance is evaluated in two applications.
Article
Engineering, Multidisciplinary
A. Guleria, R. K. Bajaj
Summary: The study introduces the concept of eigen spherical fuzzy set and proposes two algorithms to determine the greatest and least eigen spherical fuzzy sets. Numerical examples are provided to illustrate the methodology, and future work includes research in image information retrieval and genetic algorithms.
Article
Physics, Multidisciplinary
Xuan Wu, Yafei Song, Yifei Wang
Summary: A new distance-based knowledge measure is proposed in this study to quantify the knowledge amount of Atanassov's intuitionistic fuzzy set (AIFS). The method calculates the distance from an AIFS to the AIFS with maximum uncertainty, and is effectively applied to multi-attribute group decision-making problems, demonstrating its effectiveness.
Article
Computer Science, Artificial Intelligence
Adem Pinar, Fatih Emre Boran
Summary: Different higher order fuzzy sets have been introduced to handle uncertainty in decision making and data mining. This paper introduces a novel distance measure for q-RPFS and applies it in group decision making and classification in q-RPF environment. The proposed classification algorithm shows the highest average accuracy compared to other algorithms.
ARTIFICIAL INTELLIGENCE REVIEW
(2022)
Article
Computer Science, Artificial Intelligence
Muhammad Akram, Cengiz Kahraman, Kiran Zahid
Summary: This study establishes a complex spherical fuzzy (CSF) model and develops new aggregation operators, as well as introduces a complex spherical fuzzy VIKOR (CSF-VIKOR) method to address two-dimensional data representation and decision-making.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Mathematics
Emili Vizuete-Luciano, Sefa Boria-Reverter, Jose M. Merigo-Lindahl, Anna Maria Gil-Lafuente, Maria Luisa Sole-Moro
Summary: This paper introduces a new assignment algorithm using the OWA operator and its extensions in the Branch-and-bound algorithm, providing more detailed information. The algorithm is applied in a consumer decision-making model in Barcelona, aiding in selecting grocery districts that best suit their needs, while considering different sources of information independently.
Article
Automation & Control Systems
Attaullah, Shahzaib Ashraf, Noor Rehman, Asghar Khan
Summary: The core contribution of this study is to develop a novel generalized idea of q-rung orthopair probabilistic hesitant fuzzy rough set (q-ROPHFRS) which is hybrid structure of the q-rung orthopair fuzzy set, probabilistic hesitant fuzzy set, and rough set. It addresses the uncertainties in real-world decision-making problems and proposes a list of novel q-rung orthopair probabilistic hesitant fuzzy rough averaging/geometric aggregation operators. Furthermore, a novel multi-attribute decision-making approach based on the proposed aggregation information is presented.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2023)
Article
Multidisciplinary Sciences
Shahzaib Ashraf, Muhammad Sohail, Adan Fatima, Sayed M. Eldin
Summary: Zadeh's Z-numbers are powerful in characterizing uncertain information and expressing human knowledge when combined with constraint and reliability. However, the existing research on Z-numbers is limited and fails to adequately convey their benefits and properties. This study explores the randomness and fuzziness of Z-numbers using Spherical fuzzy sets, and develops operational laws, aggregation operators, and algorithms to handle uncertain information represented by spherical fuzzy Z-numbers. The suggested operators and approach demonstrate practicality and efficacy.
Retraction
Computer Science, Artificial Intelligence
Shahzaib Ashraf, Saleem Abdullah, Alaa O. O. Almagrabi
Article
Computer Science, Artificial Intelligence
Shahzaib Ashraf, Muneeba Kousar, Muhammad Shazib Hameed
Summary: This paper addresses the challenges faced by medical professionals in caring for infectious diseases in Pakistan, where public health is a major concern. The main issue lies in the resemblance of clinical symptoms among different infectious diseases, making early detection and diagnosis difficult. The study introduces a new concept of complex probabilistic hesitant fuzzy N-soft set and develops algorithms for decision-making in disease identification using this concept. Numerical case studies and a comparative analysis are provided for illustration and evaluation.
Article
Mathematics
Saleem Abdullah, Alaa O. Almagrabi, Ihsan Ullah
Summary: In this study, a new approach to artificial intelligent three-way decision making via double hierarchy linguistic variable (DHLV) was developed and applied to S-box image encryption. The Einstein operational laws, score function, and Einstein aggregation operators were defined. The unknown weight vector for decision experts was determined using aggregation operators and entropy measures, and the weight vector for criteria was found using the distance measure. The minimum-loss decision rules were applied to select S-box for image encryption.
Article
Mathematics
Shahzaib Ashraf, Muhammad Ijaz, Muhammad Naeem, Saleem Abdullah, Lula Babole Alphonse-Roger
Summary: The objective of this study is to evaluate the multicriteria group decision-making problem in risk management for technological innovation projects under dual-probabilistic linguistic information. An enhanced dual probabilistic linguistic-vise kriterijumska optimizacija kompromisno resenje (DPL-VIKOR) technique is proposed to assess risk management in TIP employing probabilistic linguistic information. The proposed method is demonstrated to be more reliable and effective for evaluating the best alternative in risk management problems for TIP.
JOURNAL OF MATHEMATICS
(2023)
Article
Automation & Control Systems
Shahzaib Ashraf, Harish Garg, Muneeba Kousar
Summary: Emergency decision-making is crucial for nations or communities in order to enhance emergency management's effectiveness and legitimacy, leading to a significant reduction in environmental damage, fatalities, and economic loss. However, current methodologies fail to consider the psychological behavior of decision makers and the diverse emergency situations and responses. This paper proposes a new method based on Complex Probabilistic Hesitant Fuzzy Soft Set (CPHFSS) to address these issues and provides a novel score function and hybrid operators for CPHFSS to improve comparability and decision-making accuracy.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Physics, Multidisciplinary
Manzoor Ali Shah, Humaira Yasmin, Fazal Ghani, Saleem Abdullah, Imran Khan, Rasool Shah
Summary: This article investigates and computes solutions to fuzzy fractional-order Cahn-Hilliard and Gardner equations. It hybridizes the fuzzy Gardner and Cahn-Hilliard equation using hybrid techniques and parametric fuzzy numbers. A novel iterative approach and the Shehu transformation are employed to explore these equations. The article presents detailed procedures for computing solutions to the fractional-order Cahn-Hilliard and Gardner problem and validates the proposed theoretical solution through examples.
FRONTIERS IN PHYSICS
(2023)
Article
Mathematics
Saleem Abdullah, Mijanur Rahaman Saifullah, Alaa O. Almagrabi
Summary: This article discusses the importance of AI cloud platform analysis, introduces a multiple criteria group decision-making (MCGDM) process, and proposes a novel evaluation method that can provide more accurate decision results.
Article
Mathematics
Saleem Abdullah, Alaa O. Almagrabi, Nawab Ali
Summary: A neural network, also known as an artificial neural network (ANN), is a powerful tool in AI with various real-life applications. Its feed-forward structure and layer-wise calculations enable effective information transmission. This study introduces a novel fuzzy neural network system called feed-forward double-hierarchy linguistic neural network system (FFDHLNNS) using Yager-Dombi aggregation operators. It also explores the properties of these operators and discusses double-hierarchy linguistic term sets (DHLTSs) and their score function and distance calculation. The study applies a FFDHLNN to select the best water purification method on a large scale, and validates the approach using extended TOPSIS and GRA. The proposed models are compared with existing decision support systems and found to be reliable and accurate for selecting water purification methods.
Article
Computer Science, Information Systems
Irfan Ullah, Fazal Ghani, Saleem Abdullah, Faisal Khan, Saifullah Khan
Summary: Finding appropriate recycling methods for plastic materials is a critical research issue, and the effectiveness of a new method is being tested. Decision-making under conditions of ambiguity can be difficult due to the lack of understanding and incomplete information. This study proposes using MAGDM approaches with 2-tuple linguistic confidence level complex q-rung orthopair fuzzy sets (2TLCLCq-ROFSs) to enhance the process of selecting the most suitable recycling method. The CODAS method is extended to 2TLCLCq-ROFSs to tackle MAGDM issues, and the proposed method is shown to be efficient through comparative sensitivity analysis.
Article
Mathematics, Applied
Jia-Bao Liu, Rashad Ismail, Muhammad Kamran, Esmail Hassan Abdullatif Al-Sabri, Shahzaib Ashraf, Ismail Naci Cangul
Summary: The single valued neutrosophic probabilistic hesitant fuzzy rough Einstein aggregation operator (SV-NPHFRE-AO) is an extension of the neutrosophic probabilistic hesitant fuzzy rough set theory. It combines various concepts and can be applied in livestock decision making to assist decision-makers in integrating and evaluating diverse criteria, resulting in more informed choices.
Article
Engineering, Multidisciplinary
Shahzad Noor Abbasi, Shahzaib Ashraf, M. Shazib Hameed, Sayed M. Eldin
Summary: The primary goal of this research is to determine the optimal agricultural field selection that would most effectively support manufacturing producers in manufacturing production while taking into account unpredictability and reliability in decision-making. The research introduces the concept of PFZN, a graded structure that combines Pythagorean fuzzy sets and ZN to deal with uncertainty in decision-aid problems. The proposed methodology of PFZN is more precise and effective in real-life problems compared to other existing methodologies.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Article
Mathematics, Applied
Aziz Khan, Shahzaib Ashraf, Saleem Abdullah, Muhammad Ayaz, Thongchai Botmart
Summary: This research focuses on an innovative multi-criteria group decision-making technique for handling spherical hesitant fuzzy (SHF) situations. By exploring SHF Aczel Alsina operational laws and their desirable characteristics, SHF Aczel-Alsina geometric aggregation operators are developed to address complex hesitant uncertain information. A decision aid methodology based on these operators is also developed and demonstrated using a case study on breast cancer treatment. Comprehensive parameter analysis and a systematic comparative study are carried out to ensure the dependability and validity of the proposed methodology.
Article
Mathematics, Applied
Shougi S. Abosuliman, Abbas Qadir, Saleem Abdullah
Summary: In real life, choosing a third-party logistics (3PL) provider has become a necessary choice for shippers due to the trend of outsourcing logistics activities. However, selecting the most suitable 3PL provider is a difficult decision for logistics consumers. This article proposes a new multi criteria group decision making method (MCGDM) based on Pythagorean fuzzy rough (PyFR) set, which includes new PyFR Einstein weighted averaging aggregation operators and a PyFR entropy measure. The proposed algorithm helps solve issues with ambiguous or insufficient data to obtain reliable and preferable results.
