An approach to MCGDM based on multi-granulation Pythagorean fuzzy rough set over two universes and its application to medical decision problem.

Exploring efficiency approaches to solve the problems of decision making under uncertainty is a mainstream direction. This article explores the rough approximation of the uncertainty information with Pythagorean fuzzy information on multi-granularity space over two universes combined with grey relational analysis. Based on grey relational analysis, we present a new approach to calculate the relative degree or the attribute weight with Pythagorean fuzzy set and give a new descriptions for membership degree and non-membership. Then, this paper proposes a multi-granulation rough sets combined with Pythagorean fuzzy set, including optimistic multi-granulation Pythagorean fuzzy rough set, pessimistic multi-granulation Pythagorean fuzzy rough set and variable precision Pythagorean fuzzy rough set. Several basic properties for the established models are investigated in detail. Meanwhile, we present an approach to solving the multiple-criteria group decision making problems with fuzzy information based on the proposed model. Eventually, a case study of psychological evaluation of health care workers in COVID-19 show the principle of the established model and is utilized to verify the availability. The main contributions have three aspects. The first contribution of an approach of calculating the attribute weight is presented based on Grey Relational Analysis and gives a new perspective for the Pythagorean fuzzy set. Then, this paper proposes a mutli-granulation rough set model with Pythagorean fuzzy set over two universes. Finally, we apply the proposed model to solving the psychological evaluation problems.

Exploring the EPR system for power battery recycling from a supply-side perspective: An evolutionary game analysis.

As a core component of new energy vehicle development, power battery will bring serious environmental pollution if it is not disposed of in a standardized way after retirement, so a scientific recycling mechanism is the key to achieve sustainable development. This paper explores the EPR mechanism of power battery recycling from a supply-side perspective based on a game theory approach. The system dynamics evolution model was constructed using Vensim software. Model testing, reward and punishment mechanism design and analysis of key parameters changes were carried out. The results show that the initial state of tripartite strategy choice is not conducive to the positive operation of reverse supply chain. The curve gradually fluctuates toward positive strategy side after the introduction of static reward and punishment mechanism, at which time the three parties show a cyclical behavior pattern. The dynamic reward and punishment mechanism can make consumers and almost 97% of the new energy vehicle manufacturers (NEVMs) participate in the environmental protection of power battery recycling, which has a better effect. In addition, the high cost of recycling will prevent a higher percentage of NEVMs from participating in supply chain construction. At the same time, the recycling price raised by private enterprises and small workshops is also one of the key factors that interfere with the participation of supply-side groups in formal recycling.

Quantitative knowledge presentation models of traditional Chinese medicine (TCM): A review.

Modern computer technology sheds light on new ways of innovating Traditional Chinese Medicine (TCM). One method that gets increasing attention is the quantitative research method, which makes use of data mining and artificial intelligence technology as well as the mathematical principles in the research on rationales, academic viewpoints of famous doctors of TCM, dialectical treatment by TCM, clinical technology of TCM, the patterns of TCM prescriptions, clinical curative effects of TCM and other aspects. This paper reviews the methods, means, progress and achievements of quantitative research on TCM. In the core database of the Web of Science, "Traditional Chinese Medicine", "Computational Science" and "Mathematical Computational Biology" are selected as the main retrieval fields, and the retrieval time interval from 1999 to 2019 is used to collect relevant literature. It is found that researchers from China Academy of Chinese Medical Sciences, Zhejiang University, Chinese Academy of Sciences and other institutes have opened up new methods of research on TCM since 2009, with quantitative methods and knowledge presentation models. The adopted tools mainly consist of text mining, knowledge discovery, technologies of the TCM database, data mining and drug discovery through TCM calculation, etc. In the future, research on quantitative models of TCM will focus on solving the heterogeneity and incompleteness of big data of TCM, establishing standardized treatment systems, and promoting the development of modernization and internationalization of TCM.