GRA BASED ANALYSIS ON FACTORS INFLUENCING CO_2 EMISSIONS IN CHINA

How to achieve the objective of reducing CO2 emissions has been an academic focus in China recently. The factors influencing CO2 emissions are the vital issue to accomplish the arduous target. Firstly, three influential factors, the energy consumption, the proportion of tertiary industry in gross domestic product （GDP）, and the degree of dependence on foreign trade, are carefully selected, since all of them have closer grey relation with China＇s COz emissions compared with others when the grey relational analysis （GRA） method is applied. The study highlights co-integration relation of these four variables using the co-integration analysis method. And then a long-term co-integration equation and a short-term error correction model of China＇s CO2 emissions are devel- oped. Finally, the comparison is exerted between the forecast value and the actual value of China＇s CO2 emissions based on error correction model. The results and the relevant statistics tests show that the pro- posed model has better explanation capability and credibility.

Grey relational analysis on the relation between marine environmental factors and oxidation-reduction potential

The effects of marine environmental factors-temperature （T）, dissolved oxygen （DO）, salinity （S） and pH--on the oxidation-reduction potential （ORP） of natural seawater were studied in laboratory. The results show an indistinct relationship between these four factors and the ORE but they did impact the ORP. Common mathematical methods were not applicable for describing the relationship. Therefore, a grey relational analysis （GRA） method was developed. The degrees of correlation were calculated according to GILA and the values of T, pH, DO and S were 0.744, 0.710, 0.692 and 0.690, respectively. From these values, the relations of these factors to the ORP could be described and evaluated, and those of T and pH were relatively major. In general, ORP is influenced by the synergic effect of T, DO, pH and S, with no single factor having an outstanding role.

Response surface method using grey relational analysis for decision making in weapon system selection

A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） problem. This paper proposes a new mathematical model based on the response surface method （RSM） and the grey relational analysis （GRA）. RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to an- alyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.

Combining TOPSIS and GRA for supplier selection problem with interval numbers

Supplier selection can be regarded as a typical multiple attribute decision-making problem. In real-world situation, the values of the alternative attributes and their weights are always being nondeterministic, and as a result of this, the values are considered interval numbers. In addition, the common approach to measure the similarity between alternatives through their distance suffers from some minor shortcomings. To address these problems, this study develops a novel hybrid decision-making method by combining the technique for order preference by similarity to an ideal solution （TOPSIS） with grey relational analysis （GRA） for supplier selection with interval numbers. By introducing the intervals theory, the extensions of Euclidean distance and grey relational grade are defined. And then a new comprehensive closeness coefficient is constituted for supplier alternatives evaluation based on the interval Euclidean distance and the interval grey relational grade, which could indicate the distance-based similarity and the shape-based similarity simultaneously. A mtmerical example is taken to validate the flexibility of the proposed method, and result shows that this method can tackle the uncertainty in real-world supplier selection and also help decision makers to effectively select optimal suppliers.

System portfolio selection based on GRA method under hesitant fuzzy environment

The hesitant fuzzy set(HFS) is an important tool to deal with uncertain and vague information.In equipment system portfolio selection, the index attribute of the equipment system may not be expressed by precise data;it is usually described by qualitative information and expressed as multiple possible values.We propose a method of equipment system portfolio selection under hesitant fuzzy environment.The hesitant fuzzy element(HFE) is used to describe the index and attribute values of the equipment system.The hesitation degree of HFEs measures the uncertainty of the criterion data of the equipment system.The hesitant fuzzy grey relational analysis(GRA) method is used to evaluate the score of the equipment system, and the improved HFE distance measure is used to fully consider the influence of hesitation degree on the grey correlation degree.Based on the score and hesitation degree of the equipment system,two portfolio selection models of the equipment system and an equipment system portfolio selection case is given to illustrate the application process and effectiveness of the method.

Grey Relevance Analysis of Major Factors of Energy-Related CO2 Emissions in Tianjin,China

Energy-related CO2 emissions from Tianjin’s production and household sectors during 2000–2012 were calculated based on the default carbon-emission coefficients provided by the Intergovernmental Panel on Climate Change.Grey relational analysis was used in this study to capture the dynamic characteristics of 12 different factors related to CO2 emissions.The results indicated that population scale and structure,industrial structure,per capita disposable income,energy consumption and structure appeared as the main drivers related to the CO2 emissions increase during the study period.Based on the research,we make the policy recommendations including optimizing the industrial structure and energy structure,improving energy efficiency and promoting low-carbon consumption.

Partner selection of collaborative innovation of strategic emerging industry - based on ANP-GRA

The rise and development of strategic emerging industries need a new innovative mode--collaborative innovation, collaborative innovation as a complex multi-object relationship, it is essential to select an appropriate partner. Partner selection is the key to the success of strategic emerging industry collaborative innovation. This paper takes collaborative innovation partner selection as research focus, establishing evaluation system of collaborative innovation partner selection, using analytic network process （ANP） to determine the weight of evaluation index, then, obtaining grey correlation rank of collaborative innovation partner by Grey relational analysis （GILA）, providing the basis for strategic emerging industry to select collaborative innovation partner.

Grain Yield Predict Based on GRA-AdaBoost-SVR Model

Grain yield security is a basic national policy of China,and changes in grain yield are influenced by a variety of factors,which often have a complex,non-linear relationship with each other.Therefore,this paper proposes a Grey Relational Analysis-Adaptive Boosting-Support Vector Regression(GRA-AdaBoost-SVR)model,which can ensure the prediction accuracy of the model under small sample,improve the generalization ability,and enhance the prediction accuracy.SVR allows mapping to high-dimensional spaces using kernel functions,good for solving nonlinear problems.Grain yield datasets generally have small sample sizes and many features,making SVR a promising application for grain yield datasets.However,the SVR algorithm’s own problems with the selection of parameters and kernel functions make the model less generalizable.Therefore,the Adaptive Boosting(AdaBoost)algorithm can be used.Using the SVR algorithm as a training method for base learners in the AdaBoost algorithm.Effectively address the generalization capability problem in SVR algorithms.In addition,to address the problem of sensitivity to anomalous samples in the AdaBoost algorithm,the GRA method is used to extract influence factors with higher correlation and reduce the number of anomalous samples.Finally,applying the GRA-AdaBoost-SVR model to grain yield forecasting in China.Experiments were conducted to verify the correctness of the model and to compare the effectiveness of several traditional models applied to the grain yield data.The results show that the GRA-AdaBoost-SVR algorithm improves the prediction accuracy,the model is smoother,and confirms that the model possesses better prediction performance and better generalization ability.

Study on the evaluation index system and evaluation method for self-elevating drilling unit design

In the process of designing self-elevating drilling unit, it is important, yet complicated, to use comparison and filtering to select the optimum scheme from the feasible ones. In this research, an index system and methodology for the evaluation of self-elevating drilling unit was proposed. Based on this, a multi-objective combinatorial optimization model was developed, using the improved grey relation Analysis （GRA）, in which the analytic hierarchy process （AHP） was used to determine the weights of the evaluating indices. It considered the connections within the indices, reflecting the objective nature of things, and also considered the subjective interests of ship owners and the needs of designers. The evaluation index system and evaluation method can be used in the selection of an optimal scheme and advanced assessment. A case study shows the index system and evaluation method are scientific, reasonable, and easy to put into practice. At the same time, such an evaluation index system and evaluation method will be helpful for making decisions for other mobile platforms.

Hybrid customer requirements rating method for customer-oriented product design using QFD

Quality function deployment （QFD） is a well-known customer-oriented product design methodology. Rating the final importance of customer requirements （CRs） is really a very es- sential starting point in the implementation of QFD, since it largely affects the target setting value of design requirements. This pa- per aims to propose a novel method to deal with the relative importance ratings （RIRs） of CRs problem considering customers＇ diversified requirements and unknown information on customers＇ weights, which is an indispensable process for determining the final importance ratings of CRs. First, a new concept of customer＇s assessment structure is proposed according to the basic idea of grey relational analysis （GRA）, and then a constrained nonlinear optimization model is constructed to describe the assessment information aggregation factors of CRs considering customers＇ personalized and diversified requirements. Furthermore, an im- mune particle swarm optimization （IPSO） algorithm is designed to solve the model, and the weight vector of customers is obtained. Finally, a car door design example is introduced to illustrate the novel hybrid GRA-IPSO method＇s potential application in deter- mining the RIRs of CRs.

Grey correlational and SSR analyses of cotton hybrids

Ten upland cotton strains exhibiting 3 fiber quality traits and 8 yield traits, were grown for two years in an investigation of the correlation between grey relational analysis （GRA） and genetic identity in heterosis of cot- ton hybrid. The aim was to establish the optimal approach for heterosis prediction and parent selection. Plant traits data were collected and analyzed for GRA. In addition, 72 simple sequence repeat （SSR） markers were examined and 148 polymorphisms were detected. Correlation analysis of GRA, genetic identity, Ft fiber quality and yield heterosis was conducted. Significant differences were observed between the two analytic methods, whereas compa- rable predictions were given for yield heterosis. GRA for yield exhibited slightly higher correlation than genetic identity analysis, with a correlation coefficient of 0.49. GRA and genetic analysis exhibited overlapping yet dis- tinct advantages in heterosis prediction. Therefore, these analytical methods should be integrated to achieve the op- timal heterosis prediction and parent selection.

Safety Evaluation of Water Environment Carrying Capacity of Five Cities in Ningxia Based on Ecological Footprint of Water Resources

[Objectives]To make safety evaluation of water environment carrying capacity of five cities in Ningxia based on ecological footprint of water resources.[Methods]With the help of the grey relational model,15 indicators were selected from the natural,economic,and social aspects,and the most influential factors in the three fields were selected.Based on the concept of ecological priority,the water resources carrying capacity of the five cities in Ningxia from 2010 to 2019 was calculated with the help of the water resources ecological footprint model.Then,the indicators of the water resources ecological footprint model were coupled with the existing indicators to establish a comprehensive evaluation indicator system.Finally,the changes of the water environment carrying capacity of the five cities in Ningxia were analyzed with the help of the principal component analysis(PCA).[Results]The ecological pressure of water resources and the ecological deficit of water resources in the five cities were relatively large.Specifically,Yinchuan City had the most obvious deficit of water resources but good carrying capacity;Zhongwei City had a large ecological deficit of water resources,poor carrying capacity,and the largest ecological pressure index of water resources;Guyuan City had low water resources ecological deficit,water resources ecological carrying capacity and water resources ecological pressure index.[Conclusions]Through the analysis of the coupling indicator system,it can be seen that the water environment carrying capacity of the five cities is in an upward trend,indicating that the water environment in each region tends to become better.

The Grey Relational Analysis （GRA） of Influence Factors on Exports in China

There are many factors influencing export in China, such as the supply in domestic market, the market openness in China, the demand in overseas market, exchange rate and so on. Since the late of 1990＇s, non-tariff barriers such as antidumping, safeguard measures and technical barriers to trade （TBT） have become the main factors. We analyze the influence factors and the degree of the influence about exports in China by the Grey Relational Analysis （GRA） and put forward countermeasures for enterprises.

Measuring author influence in scientific collaboration networks

Purpose:The purpose of this paper is to measure author influence in scientific collaboration networks by considering the combined effects of multiple indexes.In the meanwhile,we intend to explore a method to avoid assigning subjective weights.Design/methodology/approach:We applied four centrality measures(degree centrality,betweenness centrality,closeness centrality and eigenvector centrality)and authors’published papers to the scientific collaboration network.The grey relational analysis(GRA)method based on information entropy was used to measure an author’s impact in the collaboration network.The weight of each evaluation index was determined based on information entropy.The ACM SIGKDD collaboration network was selected as an example to demonstrate the practicality and effectiveness of our method.Findings:Author influence was not always positively correlated with evaluation indexes such as degree centrality and betweenness centrality.This implies that combined effects of multiple indexes should be considered in author impact analysis.The introduction of the GRA method based on information entropy can reduce the interference of human factors in the evaluation process.Research limitations:We only analyzed author influence from the perspective of scientific collaboration,but the impact of citation on author influence was ignored.Practical implications:The proposed method can be also applied to detect influential authors in bibliographic co-citation network,author co-citation network,bibliographic coupling network or author coupling network.It would help facilitate scientific collaboration and enhance scholarly communication.Originality/value:This paper proposes an analytical method of evaluating author influence in scientific collaboration networks,in which combined effects of multiple indexes are considered and the interference of human factors is reduced in the evaluation process.

Evaluation and analysis of cutting speed, wire wear ratio, and dimensional deviation of wire electric discharge machining of super alloy Udimet-L605 using support vector machine and grey relational analysis

The current study investigates the behavior of wire electric discharge machining （WEDM） of the super alloy Udimet-L605 by employing sophisticated machine learning approaches. The experimental work was designed on the basis of the Taguchi orthogonal L27 array, consid- ering six explanatory variables and evaluating their influ- ences on the cutting speed, wire wear ratio （WWR）, and dimensional deviation （DD）. A support vector machine （SVM） algorithm using a normalized poly-kernel and a radial-basis flow kernel is recommended for modeling the wire electric discharge machining process. The grey rela- tional analysis （GRA） approach was utilized to obtain the optimal combination of process variables simultaneously, providing the desirable outcome for the cutting speed, WWR, and DD. Scanning electron microscope and energy dispersive X-ray analyses of the samples were performed for the confirmation of the results. An SVM based on the radial-basis kernel model dominated the normalized poly- kernel model. The optimal combination of process vari- ables for a mutually desirable outcome for the cutting speed, WWR, and DD was determined as Ton1, Toffa, Ip1, WT3, SV1, and WF3. The pulse-on time is the significant variable influencing the cutting speed, WWR, and DD. The largest percentage of copper （8.66%） was observed at the highest cutting speed setting 7.05% of copper at the low of the machine compared to cutting speed setting of the machine.

Multi-objective optimization in wire electric discharge machining of Ti-6AL-4v using grey relational analysis for square and circular profiles

In this work,an attempt has been made for optimization of process parameters in Wire Electric Discharge Machining(WEDM)of Ti–6Al–4V while producing square and cir-cular profiles.The input parameters,namely pulse on time,pulse off time,peak current and servo voltage,were considered to study the responses cutting speed(CS)and sur-face roughness(SR).Each input parameter was set at three levels.Experiments were conducted as per central composite face(CCF)centered design.Based upon the exper-imental data,Gray relational analysis(GRA),a multi-objective optimization technique has been employed to find the best level of process parameters to optimize the machining profiles.Analysis of variance(ANOVA)has been conducted for investigating the effect of process parameters on overall machining performance.Finally,it was identified that the process parameters such as pulse on time,current and voltage have more impact on the square and circular profiles.

Comprehensive Suitability Evaluation of Tea Crops Using GIS and a Modified Land Ecological Suitability Evaluation Model

Tea （Camellia sinensis） is one of the most valuable cash crops in southern China; however, the planting distribution of tea crops is not optimal and the production and cultivation regions of tea crops are restricted by law and custom. In order to evaluate the suitability of tea crops in Zhejiang Province, the annual mean temperature, the annual accumulated temperature above 10 ℃, the frequency of extremely low temperature below -13 ℃, the mean humidity from April to October, slope, aspect, altitude, soil type, and soil texture were selected from climate, topography, and soil factors as factors for land ecological evaluation by the Delphi method based on the ecological characteristics of tea crops. These nine factors were quantitatively analyzed using a geographic information system （GIS）. The grey relational analysis （GRA） was combined with the analytic hierarchy process （AHP） to address the uncertainties during the process of evaluating the traditional land ecological suitability, and a modified land ecological suitability evaluation （LESE） model was built. Based on the land-use map of Zhejiang Province, the regions that were completely unsuitable for tea cultivation in the province were eliminated and then the spatial distribution of the ecological suitability of tea crops was generated using the modified LESE model and GIS. The results demonstrated that the highly, moderately, and non-suitable regions for the cultivation of tea crops in Zhejiang Province were 27552.66, 42 724.64, and 26507.97 km2, and accounted for 28.47%, 44.14%, and 27.39% of the total evaluation area, respectively. Validation of the method showed a high degree of coincidence with the current planting distribution of tea crops in Zhejiang Province. The modified LESE model combined with GIS could be useful in quickly and accurately evaluating the land ecological suitability of tea crops, providing a scientific basis for the rational distribution of tea crops and acting as a reference to land policy makers and land use planners.