MULTIVARIATE ABSOLUTE DEGREE OF GREY INCIDENCE BASED ON DISTRIBUTION CHARACTERISTICS OF POINTS

The analysis result of absolute degree of grey incidence for multivariate time series is often inconsistent with the qualitative analysis. To overcome this shortage, a multivariate absolute degree of grey incidence based on distribution characteristics of points is proposed. Based on the geometric description of multivariate time se- ries, the neighborhood extrema are extracted in the different regions, and a characteristic point set is constructed. Then according to the distribution of the characteristic point set, a characteristic point sequence reflecting the ge- ometric features of multivariate time series is obtained. The incidence analysis between multivariate time series is transformed into the relational analysis between characteristic point sequences, and a grey incidence model is established. The model possesses the properties of translational invariance, transpose and rank transform invari- ance, and satisfies the grey incidence analysis axioms. Finally, two cases are studied and the results prove the ef- fectiveness of the model.

Ranking grey numbers based on dominance grey degrees

With respect to the decision making problems where a lot of fuzzy and grey information always exists in the real-life decision making information system methods as fuzzy mathematics, it is difficult for such uncertainty probability, and interval numbers to deal with. To this end, based on the thought and method of grey numbers, grey degrees and interval numbers, the concept of dominance grey degree is defined. And then a method of ranking interval grey numbers based on the dominance grey degree is proposed. After discussing the relevant properties, the paper finally uses an example to demonstrate the effectiveness and applicability of the model. The result shows that the proposed model can more accurately describe uncertainty decision making problems, and realize the total ordering process for multiple-attribute decision-making problems.

Application of grey weighted related degree to the ambient air quality assessment

It is difficult to establish the integrated method to assess the ambient air quality because the atmospheric environmental system is composed of several environmental elements, which contains many contanination factors. In view of the typical grey system character of the monitored data in the ambient air, this paper introduces the weighted value to obtain related degree during applying the method of grey related degree analvsis to assess ambient air quality by each polluting factor producing different effects on the environment quality. This method could give more reasonable and reliable evaluating results. Taking the monitored data of Harbin, a provincial city of Heilongjiang, for example in this paper, the result of assessment by this method was coincide,It with the actual environmental quality of Harbin.

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.

Residential Electricity Consumption Behavior Mining Based on System Cluster and Grey Relational Degree

In order to improve the utilization of the residential electricity consumption data which contains the information on the user’s electricity consumption habits, a residential electricity consumption behaviors mining algorithm model is constructed. Firstly, according to the attribute, the collected data can be divided into the global data and the phase data, then the appropriate global variables are selected to mine the user’s electricity consumption patterns in the near future on the system clustering algorithm. Based on the theory of grey relational analysis, combing phase data with the power modes to analyze the potential characteristics of residential electricity consumption behaviors deeply that verify the ability of latest power mode to predict household electricity consumption situation in the coming few days and the effect of dominant phase variables on the peak load shifting. Finally, from the actual data of a certain family, the proposed data mining algorithm is testified that it can effectively explore the electricity consumption behavior habits and characteristics of the family.

Study on Complex System Evaluation Method Based on PCA and Grey Relative Degree

The complexity and limited data samples in evaluation of complex system are obstacles for traditional evaluation method. Based on Grey relative degree theory and principal components analysis (PCA) method, a novel systemic evaluation method is put forward in this paper. Firstly, standardization method is modified for evaluation objective, and the method includes expression (2) and (3). Secondly, for few schemes of complex system, grey relative degree, expression (5), is substituted for relation coefficient. At last, validity of the method is verified by evaluating 3 schemes of a type of UUV.

NOVEL GENERALIZED GREY INCIDENCE MODEL BASED ON INTERVAL GREY NUMBERS

To extend the traditional generalized grey incidence model, a novel grey incidence model based on inter- val grey numbers is constructed. Considering the numerical information of indexes cannot be accurately obtained and can be defined as interval grey numbers, the interval grey numbers are defined as standard interval grey num- bers which are split in white part and grey part. The absolute degree of incidence and relative degree of incidence based on the interval grey numbers are constructed and their arithmetic are given. Finally, an example about commercial aircraft index selection illuminates the effectiveness of the model. The results show that the model can sort indexes better and can extend the grey incidence models significantly.

ENTROPY MEASUREMENT OF INTERVAL GREY SEQUENCE AND ITS APPLICATION

The uncertainty measurement method for grey information theory and the metric formula are established, and its application in decision-making is researched. The entropy measurement of grey sequence based on the limited interval grey number sequence is different from the Shannon probability entropy. The measurement formula of grey number and its properties are studied, such as the invariance, the applicable conditions, and the grey entropy of union and intersection of two grey numbers, and so on. Finally, the algorithm for interval grey sequence and an example are given to show the effectiveness of the method.

Novel combinatorial algorithm for the problems of fuzzy grey multi-attribute group decision making

To study the fuzzy and grey information in the problems of multi-attribute group decision making, the basic concepts of both fuzzy grey numbers and grey interval numbers are given firstly, then a new model of fuzzy grey multi-attribute group decision making based on the theories of fuzzy mathematics and grey system is presented. Furthermore, the grey interval relative degree and deviation degree is defined, and both the optimistic algorithm of the grey interval relational degree and the algorithm of deviation degree minimization for solving this new model are also given. Finally, a decision making example to demonstrate the feasibility and rationality of this new method is given, and the results by using these two algorithms are uniform.

Grey information coverage interaction relational decision making and its application

This study aims to reflect the information coverage grey number and the interaction between attributes in grey relational decision making. Therefore, a multi-attribute decision method based on the grey information coverage interaction relational degree(GIRD) is proposed. Firstly, this paper defines the information coverage grey number, and establishes the GIRD model by using the Choquet fuzzy integral and grey relational principle. It proves that the proposed model not only is the general and unified form of the point relational degree, interval relational degree, mixed relational degree and grey fuzzy integral relational degree, but also can effectively deal with the interaction between attributes. Further,a decision making example of evaluating the industrial operation quality for 14 cities in Hunan province of China is provided to highlight the implementation, availability, and feasibility of the proposed decision model.

Application of Improved Grey Prediction Model to Petroleum Cost Forecasting

The grey theory is a multidisciplinary and generic theory that deals with systems that lack adequate information and/or have only poor information. In this paper, an improved grey model using step function was proposed. Petroleum cost forecast of the Henan oil field was used as the case study to test the efficiency and accuracy of the proposed method. According to the experimental results, the proposed method obviously could improve the prediction accuracy of the original grey model.

Comprehensive security risk factor identification for small reservoirs with heterogeneous data based on grey relational analysis model

Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.

Investigation of the Interactive,Intimidating Relation Between Urbanization and the Environment in an Arid Area Based on Grey System Theory

Taking the Hexi Corridor in western China as an example, this paper studies the interactive intimate i relation between urbanization and the environment in add areas based on the grey system theory. The results show that the grey relational degree between urbanization and the environment is low in the agriculture-oriented cities, modest in the tourism-oriented cities and great in the industry-oriented cities. The changing trend of coupling degree between urbanization and the environment does not entirely agree with that of urbanization or the environment. It showed fluctuating trends, which reflects the compactness and properties of the different stages of the coupling states between urbanization and the environment. In order to achieve a harmonious development with the environment in add areas, traditional development ideas about urbanization should be revised and more attention should be paid to the effect of restriction of water resources and the ecological environment on the development of the economy and society.

The Evaluation on Ecological Agricultural Development in Sichuan Province on the Basis of Grey Relational Analysis

By using the grey relational model,14 indexes of ecological agricultural development in Sichuan Province from 1997 to 2008 are analyzed.According to the relational degree results,the ecological agricultural development in 12 years can be divided into three stages:the first stage is from 1997 to 2000,with the shape of inverted U;the second stage is from 2001 to 2004,belonging to transition stage with slow growth rate;the third stage is from 2005 to 2008,belonging to the stage of rapid growth.It draws conclusion that per capita grain yield is an important element for evaluating ecological agricultural construction.Besides,reducing the energy consumption of per unit production,improving labor productivity and increasing agricultural science and technology application and input on agricultural infrastructure construction are the engine for developing Sichuan ecological agriculture.

Application of Improved Grey Target Technology in Weapon Evaluation

A new method of effectiveness evaluation of weapon systems is set up by improving the formula of approaching degree. According to the grey target theory of grey system theory, the patterns of the weapon systems to be evaluated are formed with the main tactical and technical performance indices of these weapon systems, thereby the standard pattern of these patterns is determined. By solving the approaching degree of patterns to their standard one and making a comparison among them, the evaluation results can be obtained.

Time-delay nonlinear model based on interval grey number and its application

In this paper, an optimization model is proposed to simulate and predict the current situation of smog. The model takes the interval grey number sequence with the known possibility function as the original data, and constructs a time-delay nonlinear multivariable grey model MGM based on the new kernel and degree of greyness sequences considering its time-delay and nonlinearity. The time-delay parameter is determined by the maximum value of the grey time-delay absolute correlation degree, and the nonlinear parameter is determined by the minimum value of average relative error. In order to verify the feasibility of the model, this paper uses the smog related data of Nanjing city for simulation and prediction. Compared with the other four models, the new model has higher simulation and prediction accuracy.

Application of Grey Associative Analysis to the Assessment of Regional Water Security

The assessment of water security is an important content in the security management of water resources due to the fact that the state of water security directly affects both the sustainable development of regional economy and the improvement on the living quality of mankind. Grey associative analysis is introduced and applied to assessment of water security on the basis of grey characteristics of the assessment index system of water security. As a case study shows, grey associative analysis is used for evaluating water security of some provinces in China, and the satisfactory assessment results are obtained. The sequence of provinces in China with regard to water security from good to poor is obtained and, moreover, the water security level of each region is also confirmed. The results obtained accord with the actual state of each region. They are of practical significance and can be used to guide the management of regional water security and a sustainable development of the economy therein. At the same time, the results demonstrate that grey associative analysis provides a new method for assessing water

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.

Analysis on Industry Structure Adjustment and Energy Consumption Based on Grey Theory——A Case Study of Qinghai Province

In view of the complexity and non-linearity of energy consumption system and the status quo of the development of energy in Qinghai Province,the relations between energy consumption and industrial structure is analyzed by using the quantitative analysis of grey relation degree by using the grey system theory.The relevancy degree among the primary industry,the secondary industry and the tertiary industry and living energy consumption are obtained,and then the trend of energy consumption in the following several years can be predicted.The results show that the secondary industry has the largest relevancy degree to the total energy consumption.In the end,according to the results of the research,several suggestions on how to saving energy are put forward.Firstly,the government should improve the high-tech industry and restrict the development of high-consumption and high-pollution industries.Secondly,the government should promote the low-carbon way of life;promote energy saving and control the energy consumption of the department of life.Thirdly,clean production should be actively promoted in the tertiary industry and the circular economy should be vigorously expanded.