Article
Mathematics, Applied
Dragisa Stanujkic, Darjan Karabasevic, Gabrijela Popovic, Dragan Pamucar, Zeljko Stevic, Edmundas Kazimieras Zavadskas, Florentin Smarandache
Summary: This manuscript proposes a new extension of the EDAS method for single-valued neutrosophic numbers, allowing for more efficient solving of complex problems with fewer evaluation criteria. The proposed approach's suitability and applicability are demonstrated through three illustrative examples.
Article
Engineering, Multidisciplinary
Muhammad Saqlain, Harish Garg, Poom Kumam, Wiyada Kumam
Summary: This article demonstrates the application of hypersoft set in solving decision-making problems with multiple attributes and introduces similarity measures for multipolar interval-valued neutrosophic hypersoft sets (mPIVNHSs). It discusses the practical value of similarity measurements and the use of the K-Nearest Neighbor algorithm in ranking site selection for a new store.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Article
Computer Science, Artificial Intelligence
Huseyin Kamaci
Summary: This paper introduces linguistic single-valued neutrosophic numbers and discusses their applications in information description and measurement. By introducing new operations and models, the richness of linguistic fusion based on the linguistic single-valued neutrosophic approach is enhanced, and a TOPSIS model based on LSVNS technique is constructed, as well as a game theory model based on this framework.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Bing Huang, Xuan Yang, Guofu Feng, Chunxiang Guo
Summary: This study focuses on ranking single-valued neutrosophic values by proposing two methods based on relative geometric distance and relative similarity degree. The approach extends the ranking method by introducing human attitudes and weights, and can be applied in various generalized fuzzy decision problem solving.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2022)
Article
Computer Science, Artificial Intelligence
Shio Gai Quek, Harish Garg, Ganeshsree Selvachandran, M. Palanikumar, K. Arulmozhi, Florentin Smarandache
Summary: This article introduces the structure of the (t, s)-regulated interval-valued neutrosophic soft set (abbr. (t, s)-INSS) and proposes a novel distance measure for this model. It also presents the TOPSIS and VIKOR algorithms that work on the (t, s)-INSS. These algorithms are consistent with human intuitions and are versatile in handling heterogeneous data. The (t, s)-INSS model is a conclusive generalization of existing structures and the distance measure is a significant improvement over current measures. The practical implementation of these algorithms in artificial intelligence, especially in the context of the COVID-19 pandemic, is highly valuable. Rating: 8 out of 10.
Article
Engineering, Multidisciplinary
Angyan Tu, Jiancheng Chen, Bing Wang
Summary: This paper investigates the use of neutrosophic multi-valued sets and consistent single-valued neutrosophic sets in representing and solving decision-making problems with multi-valued information. The authors propose cotangent similarity measures based on cotangent function and apply them to the selection of potential cars, achieving valid results.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2022)
Article
Engineering, Multidisciplinary
Faisal Al-Sharqi, Abd Ghafur Ahmad, Ashraf Al-Quran
Summary: A novel computing technique based on fuzzy representation, called fuzzy system, is introduced in this paper. An interval form of neutrosophic soft expert system representation based on real and complex numbers is proposed. Basic theoretical operations and properties of interval-valued neutrosophic soft expert set and interval-valued complex neutrosophic soft expert set are studied.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2022)
Article
Computer Science, Information Systems
Yanqiu Zeng, Haiping Ren, Tonghua Yang, Shixiao Xiao, Neal Xiong
Summary: This study proposes a new distance measure and similarity measure for single-valued neutrosophic (SVN) sets based on modified Manhattan distance. The proposed measures are applied in pattern recognition, decision-making methods, and clustering algorithms.
Article
Mathematics
Sonam Sharma, Surender Singh
Summary: This paper introduces a knowledge measure for single-valued neutrosophic sets (SVNS), compares it with existing measures, and reveals that the proposed knowledge measure is more effective in modeling structured linguistic variables. The study also investigates the application of the proposed measure in multi-attribute group decision making (MAGDM).
Article
Computer Science, Artificial Intelligence
Arunodaya Raj Mishra, Pratibha Rani, Abhijit Saha
Summary: Sustainable site selection for electric vehicle charging station is a critical process in promoting the development of electric vehicle system, involving complex assessment and multiple criteria. Single-valued neutrosophic set (SVNS) is a valuable tool for handling uncertain information in decision-making process.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Mathematics, Applied
Muhammad Ihsan, Muhammad Saeed, Atiqe Ur Rahman, Mazin Abed Mohammed, Karrar Hameed Abdulkaree, Abed Saif Alghawli, Mohammed A. A. Al-qaness
Summary: The best way to achieve sustainable construction is to choose materials with a smaller environmental impact. This study offers a framework for selecting the optimal sustainable building material. It proposes a new model based on interval-valued, soft expert, and neutrosophic settings for supply chain management and decision-making in construction projects.
Article
Computer Science, Artificial Intelligence
Gourangajit Borah, Palash Dutta
Summary: This article introduces two new weighted vector similarity measures for single-valued neutrosophic sets and validates their applications in multi-attribute decision-making problems. The results demonstrate the high accuracy and effectiveness of these measures. Furthermore, the newly constructed measures show potential for diverse applications in various fields.
COGNITIVE COMPUTATION
(2021)
Editorial Material
Computer Science, Artificial Intelligence
Yaser Saber, Fahad Alsharari, Florentin Smarandache
Summary: This paper introduces the concepts of single-valued neutrosophic soft sets and single-valued neutrosophic soft topology, and studies their properties and applications. These models provide new approaches for dealing with uncertainty.
Article
Mathematical & Computational Biology
Sundas Shahzadi, Areen Rasool, Gustavo Santos-Garcia
Summary: Neutrosophic soft set theory is a well-developed interdisciplinary research area with various applications in computational intelligence, applied mathematics, social networks, and decision science. In this research article, a powerful framework called single-valued neutrosophic soft competition graphs is introduced by integrating the technique of single-valued neutrosophic soft set with competition graph. New concepts such as single-valued neutrosophic soft k-competition graphs and p-competition single-valued neutrosophic soft graphs are defined to handle different levels of competitive relationships among objects with parametrization. The significance of these concepts is investigated through professional competition application and an algorithm is developed to address decision-making problem.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Jun Ye, Shigui Du, Rui Yong
Summary: The study introduces a new approach with single- and interval-valued hybrid neutrosophic multi-valued sets (SIVHNMVS) and a related multi-attribute group decision-making (MAGDM) method, contributing to a novel way to address group decision-making problems.
COMPLEX & INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Xindong Peng, Jingguo Dai
NEURAL COMPUTING & APPLICATIONS
(2018)
Article
Engineering, Multidisciplinary
Xindong Peng, Jingguo Dai, Lin Liu
INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION
(2018)
Article
Computer Science, Artificial Intelligence
Xindong Peng, Harish Garg
APPLIED INTELLIGENCE
(2019)
Article
Computer Science, Artificial Intelligence
Xindong Peng, Florentin Smarandache
Article
Multidisciplinary Sciences
Jose Carlos R. Alcantud, Gustavo Santos-Garcia, Xindong Peng, Jianming Zhan
Article
Energy & Fuels
Raghunathan Krishankumar, Arunodaya Raj Mishra, Kattur Soundarapandian Ravichandran, Xindong Peng, Edmundas Kazimieras Zavadskas, Fausto Cavallaro, Abbas Mardani
Article
Engineering, Multidisciplinary
Wenquan Li, Xindong Peng
MATHEMATICAL PROBLEMS IN ENGINEERING
(2020)
Article
Computer Science, Artificial Intelligence
Xindong Peng, Haihui Huang, Zhigang Luo
Summary: This study analyzes the information measure based on q-rung orthopair fuzzy set and proposes a comprehensive weight determination method to avoid the negative impact of extreme data on evaluation results. By combining objective weights and subjective weights, and considering both objective data and subjective emotion, the effectiveness of the proposed method is demonstrated.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Hai-Hui Huang, Xin-Dong Peng, Yong Liang
Summary: The study presented a novel SPLSN sparse Cox regression model, which combines self-paced learning and a log-sum absolute network-based penalty for biomarker selection in survival analysis. Results show that SPLSN can identify fewer meaningful biomarkers and achieve the best or equivalent prediction performance compared to other methods.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Tianyi Liang, Long Lan, Xiang Zhang, Xindong Peng, Zhigang Luo
Summary: This study proposes a multi-object tracking method that leverages neighbor information, modeling the relationships between targets and their neighbors using graph convolutional networks (GCNs) to reduce identity switches and achieve state-of-the-art overall performance in MOT.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
HaiHui Huang, NaiQi Wu, Yong Liang, XinDong Peng, Shu Jun
Summary: The article proposes a self-paced learning L1/2 absolute network-based logistic regression model (SLNL), which improves the accuracy and interpretability of phenotype prediction and gene marker selection in genomic data analysis through L1/2 regularization and absolute network penalty.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Economics
Xindong Peng, Haihui Huang
TECHNOLOGICAL AND ECONOMIC DEVELOPMENT OF ECONOMY
(2020)
Article
Computer Science, Artificial Intelligence
Xindong Peng, Ganeshsree Selvachandran
ARTIFICIAL INTELLIGENCE REVIEW
(2019)
Article
Computer Science, Information Systems
Xindong Peng, Wenquan Li
Article
Computer Science, Artificial Intelligence
Xindong Peng, Yong Yang
APPLIED SOFT COMPUTING
(2017)