Grey relational analysis method based on cumulative prospect theory for intuitionistic fuzzy multi-attribute group decision making

>Water quality prediction of artificial intelligence model: a case of Huaihe River Basin, China

Accurate prediction of water quality contributes to the intelligent management of water resources. Water quality indices have time series characteristics and nonlinearity, but the existing models only focus on the forward time series when long short-term memory (LSTM) is introduced and do not consider the parallel computation on the model. Owing to this, a new neural network called LSTM-multihead attention (LMA) was constructed to predict water quality, using long short-term memory to process time series data and multihead attention for parallel computing and extracting feature information. Additionally, water quality indices have the issues of multiple data types and complex data correlations, as well as missing data and abnormal data problems in water quality data. In order to solve these problems, this study proposes a water quality prediction model called GRA-LMA-based linear interpolation, gray relational analysis and LMA. Two experiments are carried out to verify the predictive performance of the GRA-LMA with the water quality data of the Huaihe River Basin as a case study sample. The first experiment focuses on data processing, including the processing of missing data and abnormal data of water quality data, and the correlation analysis of water quality indices. Linear interpolation is adapted to process the missing data, while a combination of boxplot and histogram is adopted to analyze and eliminate the abnormal data, which is then repaired the abnormal data with linear interpolation. The gray relational analysis is adopted to calculate the correlation between different water quality indices, and water quality indices with high correlation are retained to determine the input variables of the water quality prediction model. The data processing results demonstrate that repairs can be made using linear interpolation without altering the pattern of data change and the model by using the gray relational analysis to reduce the quantity of data it needs as input. In the second experiment, the predictive capacity of GRA-LMA and existing models such as backpropagation neural network (BP), recurrent neural network (RNN), long short-term memory (LSTM), and gate recurrent unit (GRU) was evaluated and compared using different numerical and graphical performance evaluation metrics. Comparative experimental results show that the mean square error of pH, dissolved oxygen, chemical oxygen demand, ammonia nitrogen, electrical conductivity, turbidity, total phosphorus, and total nitrogen of GRA-LMA is reduced to 0.05890, 0.40196, 0.32454, 0.04368, 14.71003, 8.13252, 0.01558, and 0.14345. The results indicate that GRA-LMA has superior adaptability for predicting various water quality indices and can significantly lower the induced prediction error.

Taxonomy method for green competitiveness evaluation of equipment manufacturing enterprises under picture 2-tuple linguistic environment

The fourth industrial revolution, represented by intelligence, networking and greening, is breeding and breaking through, and China is increasingly Focus on green development, public awareness of environmental protection, and small changes are able to fundamentally change our industrial organization. The equipment manufacturing industry is an industry to which our country attaches great importance, and equipment manufacturing enterprises, as microscopic subjects, want to contribute to the “13th Five-Year Plan”. Equipment manufacturing industry is a highly valued industry in China, equipment manufacturing enterprises as a microscopic subject, in order to the “Thirteenth Five-Year Plan” equipment manufacturing industry rose to inject a strong impetus, must make essential changes, embrace the green economy, green development, and enhance the green competitiveness of enterprises. The green competitiveness evaluation of equipment manufacturing enterprises is the classical multiple criterion group decision making (MCGDM). In this paper, depending on the Taxonomy method, Taxonomy method will be extended to picture 2-tuple linguistic sets (P2TLSs) to address some MCGDM issues. Some essential concepts of picture 2-tuple linguistic sets (P2TLSs) are briefly reviewed. In addition, integrating the Taxonomy method with P2TLSs, the Taxonomy method with P2TLNs is constructed and all calculating procedures are simply depicted. Eventually, an empirical application for green competitiveness evaluation of equipment manufacturing enterprises has been offered to demonstrate this novel method and some comparative analysis are also made to confirm the merits of developed method.

An integrated method for evaluating the energy-saving and economic operation of power systems with interval-valued intuitionistic fuzzy numbers

Chinese population is numerous. Energy resources are limited. The ownership of per capita resource is far lower than the world average level. China is in the process of industrialization and urbanization, but energy resources are consumed and environmental pollution is serious. The energy crisis and environmental protection has restricted our country economy development and social harmony. As a source of energy consumption and environmental pollution, power industry is one of the important fields of energy saving and emission reduction. The reasonable power dispatch is the breakthrough to reduce the energy consumption and environmental pollution. In this paper, we first introduce some operations on interval-valued intuitionistic fuzzy sets, such as Heronian mean (HM) operator and Dombi operations, etc., and further develop the induced interval-valued intuitionistic fuzzy Dombi weighted Heronian mean (I-IVIFDWHM) operator. We also establish some desirable properties of this operator, such as commutativity, idempotency and monotonicity. Then, we apply the I-IVIFDWHM operator to deal with the interval-valued intuitionistic fuzzy multiple attribute decision making (MADM) problems. Finally, an illustrative example for evaluating the energy-saving and economic operation of power systems is given to verify the developed approach.

EDAS method for multiple attribute group decision making under spherical fuzzy environment

Despite the importance of multi-attribute group decision making (MAGDM) problem in the field of optimal design, it is still a huge challenge to propose a solution due to its uncertainty and fuzziness. The spherical fuzzy sets (SFSs) can express vague and complicated information of MAGDM problem more widely. The Evaluation based on Distance from Average Solution (EDAS) method, as a highly practical decision-making method, has received extensive attention from researchers for solving MAGDM problem. In this paper, a spherical fuzzy EDAS (SF-EDAS) method is proposed to solve the MAGDM problem. Moreover, the entropy method is also introduced to determine objective weights, resulting in a more proper weight information. In addition, a practical example is settled by SF-EDAS method, which proves the excellent efficiency in applications of MAGDM problem. The SF-EDAS method provides an effective method for solving MAGDM problems under SFSs, and EDAS also provides a reference for further promotion of other decision-making environments.

An integrated methodology for commercial concrete supplier selection with intuitionistic fuzzy CPT-VIKOR

Aiming at the multi-attribute group decision-making (MAGDM) problem with unclear index weights values, and thinking about the bounded rational behavior of decision makers (DMs), we proposed a new improved CPT-VIKOR decision method under intuitionistic fuzzy (IF-CPT-VIKOR). Due to the emergence of special cases in IFSs, a new IFS score function and distance formula are defined. Meanwhile, the use of entropy weight method to obtain the weight information of indicators enhances the objectivity of the model. Furthermore, CPT is integrated into the IFS environment, which fully reflects the psychological behavior of DMs, and take advantage of the VIKOR method to determine the final sorting of the scheme. Finally, through the application cases of the commercial concrete supplier selection (CCSS) and the comparison with the existing authoritative methods to verify the feasibility and validity of the method.

Methodology for building material suppliers selection based on the intuitionistic fuzzy multiple attribute decision making method

The selection of suppliers is an important part of the construction of engineering projects in supply chain management. If the partners in the supply chain are reliable enough, they can promote the continuous progress of the supply and demand sides in the cooperation, thereby achieving a win-win situation, which is conducive to the realization of a virtuous cycle process. Material suppliers provide the required products and raw materials for the production and construction of enterprises. They are an important source of construction projects and occupy a very important position in the development of enterprises. The supply of high-quality products can lay a good foundation for the subsequent production and construction of the project, thereby promoting the smooth completion of the entire project. Therefore, rational evaluation and selection of suppliers has very important practical significance. The selection and application of building material suppliers is a classic multiple attribute decision making (MADM). In this paper, we introduced some calculating laws on intuitionistic fuzzy sets (IFSs), Hamacher sum and Hamacher product and further propose the induced intuitionistic fuzzy Hamacher power ordered weighted geometric (I-IFHPOWG) operator. Meanwhile, we also study some ideal properties of built operator. Then, we apply the I-IFHPOWG operator to deal with the multiple attribute decision making (MADM) problems under IFSs. Finally, an example for physical health literacy evaluation of College students is used to test this new approach.

Research on service quality evaluation of sports clubs with Pythagorean fuzzy information

In this paper, considering the traditional geometric operation laws and Pythagorean fuzzy information, a varies of new distance measures of Pythagorean fuzzy set are proposed, such as generalized Pythagorean fuzzy ordered geometric distance (GPFOWGD) measures and generalized Pythagorean fuzzy hybrid weighted geometric distance (GPFHWGD) measures. Besides, some special issues including Hamming distance, Euclidean distance and Hausdorff distance of these raised geometric distance measures are investigated. To testify the valid of these new presented distance measures, a decision-making model is built and illustrated by a mathematical calculation example to evaluate the service quality of sports clubs using Pythagorean fuzzy information. The results display that the approach is uncomplicated, valid and simple to compute. The example illustrates that the method presented in the paper can be used to deal with problems of uncertainty such as dynamic multiple attribute decision making.

Extended EDAS method for multiple attribute decision making in mixture z-number environment based on CRITIC method

In multiple attribute decision making (MADM) issues, the ambiguity, imprecision, and imperfection of assessment information may lead to inadequate decision-making results. However, the Z-number suggested by Zadeh in 2011 could somehow prevent this problem. For MADM issues with unknown attributes weights, an extended Distance from the Average Solution (EDAS) method is proposed under a mixture Z-number environment. In addition, the Criteria Importance Through Inter-criteria Correlation (CRITIC) method is used to estimate the weights of the criterion, which is easy to calculate and avoids subjective forecasts. A novel illustrative example is provided to demonstrate the feasibility, validity, and practicability of the presented method, and is compared with existing decision methods. The outcome indicates that the suggested method can solve complicated decision-making problems.

VIKOR method for intuitionistic fuzzy multi-attribute group decision-making and its application to teaching quality evaluation of college English

The results of the nation-wide public college English tests and some other English tests held by the college itself are very valuable data for the assessment of the English teaching level. In the light of the selected and processed data and some other auxiliary approaches, the writer suggests that a modernized monitoring system be established to improve English teaching quality. Under this system, teachers’ and students’ English level can be evaluated in an objective way. Consequently, the subsequent measures such as teachers’ promotion as well as students’ development and employment and the evaluation of the quality of test-papers can be taken scientifically. We can solve the above issues with help of multi-attribute group decision making (MAGDM) method. Depending on the VIKOR steps and given intuitionistic fuzzy sets (IFSs), this paper devises the IF-VIKOR to assess the teaching quality of college English. In addition, the weights of attribute are derived through CRITIC method. Then, the VIKOR method is extended to IFSs to derive the order of each alternative. Therefore, all alternatives could be ranked and the best one can be identified. Eventually, we give an example of college English teaching quality evaluation, according to some comparison with other methods to make an analysis, the results show that the method proposed in such paper is effective and easy to compute.

EDAS method based on cumulative prospect theory for multiple attribute group decision-making under picture fuzzy environment

For the long-term development of shopping mall, the managers of shopping mall tend to build a new store to expand the enterprise’s market share in a new city. After holding a preliminary survey of the city, managers have initially identified five sites for construction. In order to select an optimal site, managers invite four experts who come from university, marking statistics, corporate executives and accounting to score sites. And they choose the best site on the basis of scores. The trait of EDAS method is to select an optimal alternative by using the distance of each alternative from the first-rank value. In this manuscript, we build the picture fuzzy EDAS method based on the cumulative prospect theory (PF-CPT-EDAS) for multiple attribute group decision-making (MAGDM) and it can help managers to choose an optimal alternative effectively. During the procedure of PF-CPT-EDAS means, we take advantage of the entropy means to calculate the original weights of all attributes. Ultimately, we testify the effectiveness of the novel model by comparing the overcome of PF-CPT-EDAS means with the results of PF-EDAS approach and other methods.

TOPSIS method for spherical fuzzy MAGDM based on cumulative prospect theory and combined weights and its application to residential location

Nowadays, how to choose a comfortable and relatively satisfactory residence is one of the multiple attribute group decision making (MAGDM) issues which people are paying more and more attention. However, since the inaccuracy and fuzziness of the information are given by decision makers (DMs) in practical decision-making and psychological factors of DMs should be considered in the decision-making process, this paper presents TOPSIS approach based on cumulative prospect theory (CPT) to deal with the MAGDM issues under the spherical fuzzy environment. Furthermore, considering the objective relationship between the attributes, the combined weights are used to get attribute weights in spherical fuzzy sets (SFSs). Finally, an example of residential location is introduced to prove the validity of our proposed approach by comparing with spherical fuzzy TOPSIS(SF-TOPSIS) method and spherical fuzzy WASPAS (SF-WASPAS) method.

Picture fuzzy MABAC method based on prospect theory for multiple attribute group decision making and its application to suppliers selection

In the garment manufacturing industry, purchasing management is an important link. The materials of making clothes often need high cost. In addition, customers put forward a request in the quality of clothes. Thus, choosing an optimal supplier is an essential part of job. Reaching cooperation with an optimal supplier not only can help garment manufacturer improve the quality of clothes but also is benefit to reduce the cost of producing. Most importantly, it can improve the competitiveness of manufacture enterprises. So, it is important for managers to find an optimal supplier and make a cooperation with it. In this paper, we analysis an issue about choosing an optimal supplier during four different suppliers. With analyzing this problem, we can introduce an extended method under picture fuzzy environment to evaluate and choose an optimal supplier. In this article, we describe some basic knowledges about picture fuzzy sets (PFSs) and picture fuzzy numbers (PFNs). Then, we introduce the extension of MABAC method which is on the basis of prospect theory (PT) with picture fuzzy numbers (PF-PT-MABAC) and utilize the PF-PT-MABAC model to evaluate different suppliers to choose an optimal supplier. Finally, we compare the result of PF-PT-MABAC with the result of traditional MABAC, PFWG operators and traditional TODIM method to test the efficiency of PF-PT-MABAC model.