The Grey Correlation Analysis on the Relationship between the Rural Finance and the Rural Economical Growth in Sichuan Province

This paper analyzes the relationship between rural finance and the rural economy of Sichuan Province from 1999 to 2009 by using the sequential growth rate of the gross value of farming, forestry, animal husbandry and fishery and the sequential growth rate of the per capital total income of rural households as the indicators of rural economic development; and taking the volume of deposit, volume of credit, volume of agricultural credit and the credit volume of township enterprises as the indicators of rural financial development; as well as the method of grey correlation analysis. The results show that there is an obvious positive correlation between them, and the development of country finance has the closest connection with the sequential growth rate of farming, forestry, animal husbandry, sideline production and fishery. The loan scale of township enterprises has the biggest influence on the increase of the rural economy. The countermeasures are put forward, covering optimizing investment structure; supporting the development of township enterprises; encouraging loan; actively lightening the financial difficulties in the process of developing rural economy; innovating and exploring; and promoting the diversified development of rural finance.

Study on Evaluation of the Rainstorm Disaster in Fujian Province Based on Spectral Clustering Model with Grey Correlation Analysis

[ Objective] The research aimed to study assessment index system of the rainstorm disaster in Fujian Province based on spectral cluste- ring model with grey correlation analysis. [Method] According to meteorological disaster yearbook in Fujian Province, by comprehensively consider- ing disaster-inducing factor, disaster-inducing environment, disaster-sustaining body and regional disaster-prevention level, evaluation index system of the regional rainstorm disaster in Fujian was established. By spectral clustering model based on grey correlation analysis, dsk zoning of the rain- storm disaster was conducted in each area of Fujian. Finally, effect and application of the clustering model were analyzed by case research. [ Re- sult] In order to dig immanent connection among regional characteristics and improve disaster-preventing linkage performance of the evaluation unit, a spectral clustering model based on grey correlation analysis was used to conduct risk zoning of the rainstorm disaster in Fujian Province. Moreo- ver, combined weight was introduced to judge each evaluation index, so as to adjust clustering model. By case study, rainstorm disaster levels in 67 counties were obtained. Internal characteristics of each type were analyzed, and main correlation factors of each type were extracted. It was compared with statistical result of the rainstorm disaster, verifying validity and feasibility of the model. [ Conclusion] The method was feasible, and its evaluated result had better differentiation and decision accuracv.

Application of Grey Correlation Degree Analysis in Broad Bean Strain Screening

[Objectives] The aim was to clarify the target and approach to purifying and selecting Baoshan Touxinlv broad bean. [Methods] In 2012,5 homozygous strains were selected successfully as the material,and completely randomized block arrangement was adopted with 3 repeated trials to analyze the effects of plant height,effective length of podding branches,branch number per plant,pod number per plant,grain number per pod and 100-grain weight on the yield of each plant in the system. [Results] The results showed that the effects of the various factors on the yield of Baoshan broad beans were in the order of grain number per pod 〉 effective length of podding branches 〉 100-grain weight 〉 pod number per plant 〉 branch number per plant 〉 plant height. [Conclusions]In breeding new strains of Baoshan broad beans,under the premise of ensuring the seed nature and quality of the original variety,priority should be given to the gain number per pod and the increment of effective length of podding branches,followed by the pod number per plant,branch number per plant,plant height,which is the best way to breed new strains of Baoshan Touxinlv broad beans.

Analysis of Factors Influencing Comprehensive Productivity of Agriculture in Henan Province on the Basis of Grey Correlation

According to the data from Henan Statistical Yearbook from 2002 to 2008, from production capital, production conditions, labour inputs and financial support, this paper selects 11 variables influencing comprehensive productivity of agriculture in Henan Province. Through calculation and analysis of grey correlation of variables and comprehensive productivity of agriculture, this paper determines the impact of different variables on comprehensive productivity of agriculture. The results show that the agricultural capital has become the most important factor influencing comprehensive productivity of agriculture in Henan Province, while the impact of production conditions, labour inputs and financial support on comprehensive productivity of agriculture in Henan Province diminishes in turn. Corresponding countermeasures and suggestions are put forward to promote the sustainable development of comprehensive productivity of agriculture in Henan Province as follows: strengthen agricultural financial system building, and ensure agricultural production expenditure; scientifically arrange allocation of agricultural resources, and improve agricultural production conditions; carry out training of agricultural skills, and elevate the quality of agricultural labour forces; increase financial expenditure for agricultural production, and optimize financial expenditure structure.

Fuzzy Comprehensive Evaluation of Air Quality in Shijiazhuang City Based on Grey Correlation

[Objectives]This study was conducted to evaluate the air quality of Shijiazhuang City,in order to facilitate the government to correctly formulate measures to prevent and control air pollution and protect Shijiazhuang's ambient air quality. [Methods] With the air quality data of Shijiazhuang City from February to March in 2019 as the research object,the gray correlation analysis method was used to determine weight A of each pollutant factor first,and then a single factor evaluation matrix R was constructed. The weight A and the single factor evaluation matrix R were synthesized using the M( ·,+) fuzzy composite operator,obtaining a fuzzy matrix B between the factor set and the evaluation level. [Results] The eigenvalue of air quality was calculated according to matrix B: H = 2. 259 5.[Conclusions]The air quality in Shijiazhuang City from February to March was between grade 2 and grade 3,closer to grade 2,indicating that the air quality was good.

Evaluation of Comprehensive Performance of Agronomic Traits of Anmai 1241 by Grey Correlation Analysis and Cluster Analysis Methods

The agronomic traits of the new wheat variety Anmai 1241 were comprehensively evaluated,in order to provide comprehensive and objective theoretical basis for further improvement and production utilization of this variety.The winter water production test results of Anmai 1241 in 14 pilot sites of Henan Seed Management Station from 2016 to 2017 were summarized.The comprehensive performance of 11 agronomic traits of Anmai 1241 in different tests sites in Henan Province was evaluated by the grey correlation analysis and clustering analysis methods.The results showed that among the observed values of 11 traits,the variation coefficient,correlation degree and weight of black embryo rate were 181.64%,0.6679 and 0.1051,respectively.The clustering analysis showed that the 11 traits could be divided into 3 groups.The first type of traits(yield,number of grains per ear and 1000-grain weight)and the third group of traits(percentage of earbearing tillers,number of productive tillers and volume weight)belonged to the yield factor traits,and the sum of their weights was 0.5242.Yield and its related factors played an important role in the variety evaluation of Anmai 1241,and the effect of black embryo on yield should be eliminated in variety improvement.

Assessment of Forest Soil Fertility in Yunfu City based on Grey Correlation

Due to the spatial heterogeneity of forest soil,it is a difficult problem to evaluate the forest soil fertility on a large scale.This study conducted a grid survey of forest soil in Yunfu City,Guangdong Province,and used the the gray correlation system to evaluate forest soil fertility in each county.The results showed that the effect of using the gray correlation analysis to evaluate soil fertility in Yunfu city was ideal,and the fertilizer strength in each county was in order of Yunan,Yun'an,Yuncheng,Xinxing,and Luoding.The results can provide an appropriate scientific basis for forestry division within the county scale.

A Diagnosis Method of Vibration Fault of a Steam Turbine Based on Information Entropy and Grey Correlation Analysis

The vibration fault, one of the common faults in the steam turbine generator unit, brings great damage to the production and the running process. It is well known that the information entropy is to describe the degree of indeterminacy of the system, so the information entropy can be used to measure Despite its efficiency, one kind of information entropy is just enabled to identify make up for this limitation, based on nalysis was studied for vibration fault the vibration condition of the unit. certain part of the faults. In order to the faulty signals collected from the rotor test platform, the grey correlation adiagnosis of steam turbine shafting in this paper. The reference faulty matrix and the calculation model of grey correlation degree was established based on three kinds of information entropy. The analysis shows that grey correlation analysis is a useful method for fault diagnosis of shafting and can be used as a quantitative index for fault diagnosis.

Comprehensive Evaluation Method for Traffic Flow Data Quality Based on Grey Correlation Analysis and Particle Swarm Optimization

Nowadays,data are more and more used for intelligent modeling and prediction,and the comprehensive evaluation of data quality is getting more and more attention as a necessary means to measure whether the data are usable or not.However,the comprehensive evaluation method of data quality mostly contains the subjective factors of the evaluator,so how to comprehensively and objectively evaluate the data has become a bottleneck that needs to be solved in the research of comprehensive evaluation method.In order to evaluate the data more comprehensively,objectively and differentially,a novel comprehensive evaluation method based on particle swarm optimization(PSO)and grey correlation analysis(GCA)is presented in this paper.At first,an improved GCA evaluation model based on the technique for order preference by similarity to an ideal solution(TOPSIS)is proposed.Then,an objective function model of maximum difference of the comprehensive evaluation values is built,and the PSO algorithm is used to optimize the weights of the improved GCA evaluation model based on the objective function model.Finally,the performance of the proposed method is investigated through parameter analysis.A performance comparison of traffic flow data is carried out,and the simulation results show that the maximum average difference between the evaluation results and its mean value(MDR)of the proposed comprehensive evaluation method is 33.24%higher than that of TOPSIS-GCA,and 6.86%higher than that of GCA.The proposed method has better differentiation than other methods,which means that it objectively and comprehensively evaluates the data from both the relevance and differentiation of the data,and the results more effectively reflect the differences in data quality,which will provide more effective data support for intelligent modeling,prediction and other applications.

Water and nitrogen input optimization for jujube trees under surge root irrigation based on weighted grey correlation model

In order to obtain the optimal input of water and nitrogen(W&N)suitable for the jujube trees in Northern Shaanxi,12 treatments had been set in the demonstration base of micro-irrigation jujube tree of Mizhi County in 2014-2015 through field experiment of jujube trees under surge root irrigation(SRI),in which three soil moisture levels(high moisture level W1:60%-85%θ,middle moisture level W2:50%-75%θ,low moisture level W3:40%-65%θ)and four nitrogen input levels(high nitrogen F75:0.75 kg/plant,middle nitrogen F50:0.50 kg/plant,low nitrogen F25:0.25 kg/plant,no nitrogen F0:0.00 kg/plant)were set.Through analyzing the effects of different W&N inputs on the yield,net income(NI)and W&N utilization efficiency(WUE and NUE)of jujube trees and establishing a weighted grey correlation model,the optimization of W&N input for jujube trees could be achieved under SRI.Results showed that different W&N inputs had significant influences on yield,NI,WUE and NUE.Along with the increase of soil moisture content,the yield and NUE increased,while WUE decreased gradually,and the NI had the tendency to increase first and then decrease.Along with the increase of nitrogen input,the yield,NI and WUE had the tendency to increase first and then decrease while the NUE decreased significantly,and the yield,NI,WUE and NUE could not reach the maximum at the same time.Through the study on the grey correlation model of jujube tree’s comprehensive benefit based on the yield,NI,WUE and NUE,results showed the comprehensive benefit of jujube trees was significantly different when W&N input was different,and the gray correlation degree of W2F25 treatment was the highest in two years,which means that the soil moisture content of 50%-75%θand nitrogen input of 0.25 kg/plant was the optimal W&N input for jujube trees under SRI in Northern Shaanxi area.

Evaluation and Influencing Factors on Particle Agglomeration in RAP

Asphalt extraction test and scanning electron microscopy(SEM) were used for analysis of agglomerations of reclaimed asphalt pavement(RAP) particles. In order to quantify the agglomeration degree of RAP, the fineness modulus ratio(FMR) and the percentage loss index(PLI) were proposed. In addition, grey correlation analysis was conducted to discuss the relationship between particle agglomerations and RAP size,asphalt content(AC), and surface area. Two indexes indicate that the agglomeration degree increases in general as the RAP size reduces. This can be attributed to that particles are prone to agglomeration in the case of higher AC. Based on the SEM images and the material composition of RAP, the particle agglomeration in RAP can be classified into weak agglomeration and strong agglomeration. Grey correlation analysis shows that AC is the crucial factor affecting the agglomeration degree and RAP variability. In order to produce consistent and stable reclaimed mixtures, disposal measures of RAP are suggested to lower the AC of RAP.

Average Incremental Correlation Analysis Model and Its Application in Fault Diagnosis

The concept of average incremental correlation degree is put forward.It has been proved that the average incremental correlation model has such properties as parallelism,consistency,affine,affine transformation isotonicity and interference factors independence,and it will not lead to changes of the sequence order relation because of the data transformation.Therefore,the new model keeps good stability.Finally,the incremental average correlation model is applied to failure model analysis of equipment,and an ideal diagnostic effect is obtained.

Application of Grey-correlated Spectral Region Selection in Analysis of Near-infrared Spectra

The optimal selection method of spectral region based on the grey correlation analysis was applied in the analysis of near-infrared（NIR） spectra. In order to compute ＂characteristic＂ spectral region, 160 samples of tobacco were surveyed by NIR. Next, the whole spectral region was randomly divided into six regions, and the values of association coefficients and correlation orders of different regions were computed for total sugar, reducing sugar and nicotine. Moreover, two regions that owned the largest value of association coefficient were regarded as ＂characteristic＂ spectral region of a model. Finally, the quantitative analysis models of different components were established via the partial least squares method, and the common selection methods of spectral region were compared. The simulation results indicate that the models to choose the spectral region based on grey correlation analysis are more effective than the common selection methods of spectral region, the optimized time of algorithm is shorter, the prediction precision of the models is higher and generalization ability for quantitative analysis results is stronger. This research can provide the support for the quantitative analysis models of NIR spectra and new idea for commercial analysis software of NIR. So, it has a high application value in the analysis of NIR spectra.

Income Growth of Peasants Based on Grey Theory

Taking Jiangsu Province for example and using the relevant data in Jiangsu Statistical Yearbook and Statistical Communique of Jiangsu Province on National Economic and Social Development during 2002-2009,the thesis selects eight indexes including per capita net income of farmers,the fixed asset investment level in rural areas,average educational level,agricultural scientific and technological level,urbanization level,industrialization level,average consumption level per rural residents and per capita GDP and adopts the theory of grey correlation to analyze the factors influencing the peasants' net income.As shown in the result,the effect on the peasants' net income gives the following subsequence from great to little:average consumption level per capita of rural residents,urbanization level,average educational level,industrialization level,per capita GDP,number of scientific and technical personnel and fixed asset investment level in rural areas,that is,r06>r04>r02>r05>r07>r03>r01.Then combining with the practical conditions,the thesis makes a detailed analysis of each factor influencing the peasant's income growth and proposes corresponding measures in order to improve the peasants' income.

Regional Economic Vitality Based on Weighted Grey Relational Analysis

The future development of cities has a great relationship with economic vitality.To determine the size of the economic vitality and its main influencing factors.This article takes some cities in China as examples.First,determine the main factors.Aiming at many factors,this paper starts from the perspective of population changes in different cities and changes in corporate vitality.After applying the rough set theory to objectively evaluate index weights,the main factors are screened out.Then,the weights of the corresponding evaluation indexes of each group of cities are calculated by a multiple linear regression to a weighted index system,and then the cities are ranked using the gray correlation analysis method.Finally,we get the ranking of the economic vitality level of different cities.Finally,suggestions are made based on the weighting factors of major factors and economic vitality.

Employment Quality EvaluationModel Based on Hybrid Intelligent Algorithm

In order to solve the defect of large error in current employment quality evaluation,an employment quality evaluation model based on grey correlation degree method and fuzzy C-means(FCM)is proposed.Firstly,it analyzes the related research work of employment quality evaluation,establishes the employment quality evaluation index system,collects the index data,and normalizes the index data;Then,the weight value of employment quality evaluation index is determined by Grey relational analysis method,and some unimportant indexes are removed;Finally,the employment quality evaluation model is established by using fuzzy cluster analysis algorithm,and compared with other employment quality evaluation models.The test results show that the employment quality evaluation accuracy of the design model exceeds 93%,the employment quality evaluation error can meet the requirements of practical application,and the employment quality evaluation effect is much better than the comparison model.The comparison test verifies the superiority of the model.

A modified EDAS model for comparison of mobile wallet service providers in India

The present paper has two-fold purposes.First,the current work provides an integrated theoretical framework to compare popular mobile wallet service providers based on users’views in the Indian context.To this end,we propose a new grey correlationbased Picture Fuzzy-Evaluation based on Distance from Average Solution(GCPF-EDAS)framework for the comparative analysis.We integrate the fundamental framework of the Technology Acceptance Model and Unified theory of acceptance and use of technology vis-a-vis service quality dimensions for criteria selection.For comparative ranking,we conduct our analysis under uncertain environments using picture fuzzy numbers.We find that user-friendliness,a wide variety of use,and familiarity and awareness about the products help reduce the uncertainty factors and obtain positive impressions from the users.It is seen that PhonePe(A3),Google Pay(A2),Amazon Pay(A4)and PayTM(A1)hold top positions.For validation of the result,we first compare the ranking provided by our proposed model with that derived by using picture fuzzy score based extensions of EDAS and another widely used algorithm such as The Technique for Order of Preference by Similarity to Ideal Solution.We observe a significant consistency.We then carry out rank reversal test for GCPF-EDAS model.We notice that our proposed GCPF-EDAS model does not suffers from rank reversal phenomenon.To examine the stability in the result for further validation,we carry out the sensitivity analysis by varying the differentiating coefficient and exchanging the criteria weights.We find that our proposed method provides stable result for the present case study and performs better as ranking order does not get changed significantly with the changes in the given conditions.

Evaluation of the coordinated development of China’s forest resources-economy-environment system

Forests provide enormous ecological, economic, and social benefits, as such forest development should be ori‐ented toward resource-economy-environment harmonization. This paper constructs a comprehensive evalua‐tion index system and uses the coupled coordination degree model to measure the coordinated development level of China’ s forest resources-economy-environment system. The results show that, across 2006‒2020, the level of coupled coordinated development of China’ s forest resources-economy-environment composite system fluctuates in an upward trend, thus gradually developing from an initial imbalance to a high degree of coordi‐nation;the level of coordinated development of each subsystem of the forest resources, economy, and environ‐ment also shows an upward trend. The factors influencing the coordinated development of the forest resource economy-environment system are, in order, the government’ s financial capacity, market environment, scien‐tific and technological innovation capacity, level of economic development, and strength of policy implemen‐tation. Therefore, this paper proposes some measures to improve the coordinated development.

The Establishment of Mathematical Models for the Composition Analysis and Identification of Ancient Glass Products

Glass is the precious material evidence of the trade of the early Silk Road. The ancient glass was easily affected by the environmental impact and weathering, and the change of composition ratios affected the correct judgment of its category. In this paper, mathematical models and methods such as Chi-square test, weighted average method, principal component analysis, cluster analysis, binary classification model and grey correlation analysis were used comprehensively to analyze the data of sample glass products combined with their categories. The results showed that the weathered high-potassium glass could be divided into 12, 9, 10 and 27, 7, 22 and so on.

Quantitative description of characteristics of high-capacity channels in unconsolidated sandstone reservoirs using in situ production data

Quantitative description of the high-capacity channels in unconsolidated sandstone reservoirs, into which water was injected to improve oil recovery, is a hot topic in the field of reservoir development. This paper presents a novel approach to describing quantitatively the characteristics of connected macropores in unconsolidated sandstone reservoirs using in situ production data. Based on physical simulation for formation mechanisms of high capacity channels and interwell tracer test data, a mathematical model was established to describe high-capacity channels by grey correlation theory, flow mechanism of fluid in porous media and reservoir engineering, and a program was developed to describe quantitatively the channel characteristics. The predicted results were consistent with field monitoring data （80%）, so this model could be economically and effectively used to identify high-capacity channels.