Table of Content

01 June 2020, Volume 32 Issue 2

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A Novel Grey Incidence Decision-making Method Based on Close Degree and Its Application in Manufacturing Industry Upgrading

Peng Yu, Heng Ma, Yingjie Yang, Xiaochuan Li, David Mba

2020, 32(2):  1-19. 

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Targeting the problem of scheme ranking and indicator weighting that exist in grey incidence decision-making, a novel grey incidence decision-making method based on close degree is proposed, which can effectively distinguish evaluation results to the greatest extent. In this paper, we firstly define the concepts of the original and normative observation matrices, the vector normalization operator, and the data sequences of the positive and negative ideal systems’ behavioral characteristics. Then, the synthetic grey incidence coefficient is represented by the areas enclosed by two adjacent points between the scheme and the ideal sequences. This area is utilized to measure the proximity of two sequences in distance and their geometric similarity. Guided by the traditional weighting methods, the subjective-objective combined weighting method that is based on level difference maximization is employed to assign weights to indicators. We also provide theoretical proof that the weighting method is more reasonable and interpretable than traditional methods. Subsequently, we propose the close degree of grey incidence by employing the synthetic grey incidence coefficient and the subjective-objective combined weighting method, so that we can implement the scheme ranking. Finally, we take the evaluation of the status of the manufacturing industry upgrading in the Yangtze River Delta (YRD) as case analysis and explore the theoretical and practical value of the proposed method.

Grey Relational Local Regression Estimation Model of Soil Water Content Based on Hyperspectral Data

Xuesong Cao, Xican Li, Haoran Zhai, Hao Zhong, Zhengyan Li

2020, 32(2):  20-33. 

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It is of considerable significance to estimate soil water content quickly and accurately by hyperspectral technique for the development of precision agriculture. In this paper, 76 soil samples collected from the Zhangqiu District of Jinan City, Shandong province, were taken as the research object. Firstly, nine transformation methods, such as differential, square, and square root, were used to transform the spectral data after denoising, and the estimation factors were selected according to the principle of maximum correlation. Then the grey-weighted distance correlation degree is used to recognize the pattern of the estimated samples, and the local linear regression estimation model of soil water content is established by using the known pattern samples closest to the samples to be identified. Finally, the determination coefficient and average relative error are adopted to evaluate the validity of the established model. The results showed that the maximum correlation coefficient among the five estimation factors was 0.94, and when the number of samples modeled by linear regression was 35, the estimation accuracy of the soil water content of 12 test samples was higher, among which the determination coefficient R2 was 0.993, and the average relative error was 3.50%. The results show that it is feasible and effective to estimate soil water content using the grey relational local linear regression model.

Income-Growth Effects of The Rural Industry Integration In Zhejiang Province Of China—An Application of The New GRA Embedded Panel Data Regression Model

Yiqin Hu, Shuting Xu

2020, 32(2):  34-49. 

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The relationship between rural industry integration and farmers’ income increase has been analyzed in this paper. To this end, a novel index system for evaluating the level of rural industry integration in Zhejiang province has firstly been designed, and this rural industry integration level can be measured accordingly. Subsequently, to select the independent variables of the farmers’ income, a new Grey Relational Analysis Model (GRA) is proposed based on panel data, which is modified by comprehensively utilizing the increments of the time and index dimensions. By using this proposed grey model, explanatory variables will be determined among a range of influencing factors, including the rural industry integration level. Lastly, in order to reveal the Income-growth effects of the rural industry integration, the Panel Data Regression Model (PDRM) is introduced to conduct the experimental studies of 11 cities in Zhejiang province. The experimental results show that strong relationships exist between farmers’ income and rural industry integration, urbanization level, agricultural investments, and GDP. Furthermore, the higher the integration level is, the faster the farmers’ income grows. Besides, the farmers’ income increase also has positive relationships with the other three independent variables. Accordingly, some suggestions are offered to improve further the level of the rural industry integration in Zhejiang province so that it can promote the development of the family farm.

A Generalized Multivariate Grey Prediction Model DGM(1,N,τi) With Unknown Time Delays

Chong Li , Xiuping Xie

2020, 32(2):  50-76. 

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An Improved Non-Equal Interval GM(1,1) Model Based On Grey Derivative And Accumulation

Liwei Tang, Yayun Lu

2020, 32(2):  77-88. 

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To improving the fitting and prediction effects of the non-equal interval GM(1,1) model, based on analyzing the main factors of the error source of this model, an improved non-equal interval GM(1,1) model based on grey derivative and accumulating generation is proposed in this paper. Considering that the accumulating algorithm affects the exponential strength of the generated sequence and the geometric sequence implies the exponential form, a new algorithm for the accumulating generation of non-equal interval sequences is proposed, and a new grey derivative optimization method and parameter estimation method are proposed based on the new accumulating algorithm. Additionally, this paper infers to the accumulating algorithm of the traditional non-equidistant GM (1,1) model is an approximation of the new accumulating method in the case of a smaller development coefficient. The findings show that the model under the new parameter estimation method has several properties, including multiply transformation, does not change the fitting prediction and the white index rate coincidence. Finally, we verify the validity and practicability of the improved non-equal interval GM(1,1) model by examples.

A New Approach for Interval Grey Numbers: n-th Order Degree of Greyness

Erdal Aydemir

2020, 32(2):  89-103. 

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Uncertain information has complexity for various reasons in real-life decision-making problems in order to be useful information. Therefore, studying the characterization and size measurement of uncertain information is of significant interest. Therefore, the purpose of this paper is to investigate the n-th order level of the degree of greyness for analyzing as a new approach of distance measuring and sorting methods for general grey numbers. Also, a pseudocode form is given for the proposed method and illustrated by using an interval number, and its effects are presented on some experimental solutions

A Grey Correlational Analysis Method Based on Cross -correlation Time-delay

Song Zheng , Jialin Shi, Dan Luo

2020, 32(2):  104-118. 

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The Measurement and Comparison of Leading Innovation Incentives of Chinese Provincial Small and Medium Sized Industrial Enterprises Based on Matrix Grey Clustering

2020, 32(2):  119-135. 

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Based on the leading Innovation behavior activity and product richness, a two-dimensional quantitative analysis framework and measurement index system of Chinese provincial industrial enterprises in small and medium-sized enterprises (in short: SMIEs) are established, and the matrix grey clustering model is applied. This paper makes an empirical analysis of the leading Innovation dynamic level of SMIEs in various provinces of China. The results show that the leading Innovation incentives level of in various provinces of China is mainly divided into "Behavior Activity High-Product Richness High", "Behavior Activity Medium-Product Richness Medium", "Behavior Activity Low-Product Richness Medium", "Behavior Activity Low-Product Richness Low". And there are significant differences in geographical spatial distribution and certain regional gradients from east to west. At the same time, the leading Innovation incentives of SMIEs in china are generally at a low level, and the overall innovation incentives are still insufficient.

Feature Selection For Chiller Fault Detection And Diagnosis Based On Grey Similitude Degree Of Incidence

Hua Liu, Zhiping Zhang , Zhanwei Wang

2020, 32(2):  136-149. 

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From the perspective of online applications of chiller fault detection and diagnosis (FDD) systems, a feature selection (FS) method based on grey similitude degree of incidence (GSDI) is proposed, in order not only to save initial sensor costs of online applications through reducing the number of sensors and selecting low-cost sensors but also to keep the excellent FDD performance. Firstly, under the constraints of online applications: low cost of measurement and high sensitivity to faults, 16 candidate features are determined. Secondly, the optimal number of features is determined based on mutual information (MI) technique. Thirdly, the specific feature subsets are determined based on GSDI. Finally, a multi-class support vector machine (SVM) is introduced as an evaluation tool to evaluate the FS results through its diagnostic performance. Seven typical faults of the chiller are concerned in this paper. The experimental data are from the ASHRAE RP-1043. The results show that the number of features is reduced effectively, meanwhile keeping the excellent FDD performance, i.e., the diagnostic correct rates exceed 95%; the misdiagnosis rates are lower than 0.5%; the false alarm rates are lower than 1%.

Modelling and Control Structure of a Phosphorite Sinter Process with Grey System Theory

Nigina Toktassynova, Hassen Fourati, Batyrbek Suleimenov

2020, 32(2):  150-166. 

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The sintering process of phosphorite ore occurs with a large amount of return caused by untimely process control. The control task of the phosphorite ore sintering is to regulate parameters of the process to obtain a high-quality sinter. The parameter clearly responsible for the sinter quality is the temperature in the wind box (also called burn through point (BTP)). Therefore, in order to solve the real-time control task, it is necessary to predict the BTP. In this paper, the grey system theory is used as a predictive approach, which makes it possible to obtain an adequate model that has the character of a “generalized energy system” and uses a small initial sample. Based on the grey model GMC(1,n), which is constructed in real-time by using real data at the beginning of the process, the temperature is well predicted at the end of the sintering process. When the temperature does not match the set value or to find out an optimal regulation, a control synthesis is carried out through an optimization of the prediction according to the “particle swarm” algorithm.