Grey Degree Research Articles

Research on Multi-Criteria Decision Based on Bidirectional Grey Relation Projection Method

There are many comprehensive efficiency evaluation problems in socioeconomic system, which are also taken as grey multi-criteria decision problems. Based on grey system theory and vector projection theorem, the grey relation projection method combines module with angle cosine to fully reveal the close degree of multiple decision schemes and the ideal scheme. Grey relation projection method considers spatial influences of factor indexes and is applicable to the situation of small sample and discrete data. However, traditional grey relation projection method can not solve the problem of sorting schemes with the same projection. On account of TOPSIS method, this paper studies bidirectional grey relation multi-criteria decision method on the basis of positive and negative ideal points from the perspective of vector projection, and constructs a bidirectional grey relation projection close degree calculating model. Analysis on application example shows that the method put forward in this paper has preferable feasibility and rationality.

Evaluation and Analysis in Product Evolution Design

aiming at the difficulty of dynamic evaluation and realizing innovation in Product Family Evolution (PFE), an evaluation method of the product family for mass customization is presented by analyzing the influences of customer needs, enterprise resources and product data in the implementation process of Product Family (PF). From the perspective of time and space, the dynamic and static relative of PFE is summarized. In order to judge the situation of current product family and achieve the evolution innovation of product family, a comparative evaluation model for the product family based on Grey Conjunction Degree is established. Finally, the effectiveness and feasibility of the method were proved by evaluation and analysis of Small Wheel Loaders (SWLs).

Evaluation of Bupleuri Radix resources in Qingchuan based on DTOPSIS and grey related degree

In order to select high quality and suitable Bupleuri Radix varieties in Qingchuan, and establish a new comprehensive method to evaluation the quality of Bupleuri Radix, 12 characters of 14 samples were evaluated by DTOPSIS and grey related degree. The results showed that varieties No. 8 and No. 10 had high quality. DTOPSIS and grey related degree gave the uniformity result, and the biggest difference of value of Ci in DTOPSIS method was 46. 33% , but the biggest difference of the weighting correlation number( r (i)) in grey related degree was only 13.10%. The DTOPSIS combined with grey related degree can evaluate the quality of Bupleuri Radix comprehensively and objectively.

Safety Comprehensive Evaluation of Spacecraft Assembly Process Based on Grey-Fuzzy Method

Multilevel evaluation indicator system for spacecraft assembly safety was built, considering six aspects: operators, process equipment, operating environment, operation types, objects to be operated, and emergency measures. Based on that, a grey-fuzzy comprehensive evaluation approach was proposed to support the spacecraft assembly safety evaluation. In the approach, analytic hierarchy process and grey degree were applied to construct weight matrix, and the principle with which the appropriate memberships could be determined was taken as a basis for creation of grey-fuzzy comprehensive evaluation matrix. The docking assembly, a typical stage in spacecraft assembly process, was taken as the case study to evaluate its safety level by the proposed grey-fuzzy comprehensive evaluation method, and it was confirmed that the result is coherent with the reality of the accident statistics. The evaluation results can be utilized as a technical basis for developing safety and protective measures, perfecting risk management, and furthermore lowering the risk to minimize economic loss and behind-schedule of project.

Determinants of disability in multiple sclerosis: an immunological and MRI study.

Multiple sclerosis (MS) is characterized by a wide interpatient clinical variability and available biomarkers of disease severity still have suboptimal reliability. We aimed to assess immunological and MRI-derived measures of brain tissue damage in patients with different motor impairment degrees, for in vivo investigating the pathogenesis of MS-related disability. Twenty-two benign (B), 26 secondary progressive (SP), and 11 early, nondisabled relapsing-remitting (RR) MS patients and 37 healthy controls (HC) underwent conventional and diffusion tensor brain MRI and, as regards MS patients, immunophenotypic and functional analysis of stimulated peripheral blood mononuclear cells (PBMC). Corticospinal tract (CST) fractional anisotropy and grey matter volume were lower and CST diffusivity was higher in SPMS compared to RRMS and BMS patients. CD14+IL6+ and CD4+IL25+ cell percentages were higher in BMS than in SPMS patients. A multivariable model having EDSS as the dependent variable retained the following independent predictors: grey matter volume, CD14+IL6+ and CD4+IL25+ cell percentages. In patients without motor impairment after long-lasting MS, the grey matter and CST damage degree seem to remain as low as in the earlier disease stages and an immunological pattern suggestive of balanced pro- and anti-inflammatory activity is observed. MRI-derived and immunological measures might be used as complementary biomarkers of MS severity.

Prediction Modeling Method of Interval Grey Number Based on Different Type Whitenization Weight Functions

The modeling objects of existing prediction models for interval grey number are limited to the interval grey number sequences with unknown or the same type of whitenization weight function. Therefore, the existing methods are useless when the types of whitenization weight function of interval grey number in the modeling sequence are heterogeneous. On the basis of the existing prediction models for interval grey number and according to the axiom of undecreased degree of greyness and grey number, the present paper build a prediction model for interval grey number based on different types of whitenization weight functions through expanding the calculation of "kernel and grey degree" of the interval grey number. At last, this model was applied in forecasting the demand for emergency materials in disaster. The research results are significant for enriching and perfecting the grey prediction model theory system, and extending the applied scope of grey models and promoting the effective association of the grey theory and the practical issues.

An Improved Gray Similarity Degree with Adaptive Weight for Guidance Simulation Credibility Evaluation

Credibility evaluation of guidance system simulation based on similarity degree is researched. Concerning the engineering problems that similarity degree method is faced, an improved gray similarity degree method combined with variable weight function is presented. Firstly, the ameliorated similarity degree method using for static simulation parameter is built by utilizing the gray measure function of flight data. Then, the sequences coming from dynamic simulation parameters are divided into important region and unimportant region, the un-homogeneous exponential operator as well as the mean operator is applied and the improved similarity degree method using for dynamic simulation parameter is established. Finally, the method is verified through actual measurement data. Practice proves that the improved method can give more creditable evaluation result and have a bright prospect.

Gray Relevancy Analysis on Blasters' Unsafe Act in Chinese Coal Mine

In order to find exactly which unsafe act would cause gas explosions easily, some traditional statistics of the blasters' unsafe act which recorded during 1999 to 2008 were reviewed. The gray relevancy analysis method was used to analyze the blaster's unsafe act. The gray relevancy degree of blaster's unsafe act was got. Results show that the four kinds of act ('blasting with fire or coal mine electric power', do not cover the connection of bus properly', 'hole sealing without water stemming', 'do not have enough stemming') have a closer relationship with gas explosions.

Grey Incidence Cluster Analysis of Colliery Security Management Evaluating Indicator

It is necessary to exactly classify the evaluating indicator of colliery security management, and the classification is also the foundation and prerequisite of colliery security management and evaluation. In this paper, reasonable classification to colliery security management and evaluation is carried by the method of grey incidence cluster. Grey incidence cluster is one kind of grey cluster evaluation in grey system theory. On the basis of lots of investigation, analysis and summary, sample nine coal mines, 13 safety management evaluation，calculate their gray absolute degree, taken given threshold r=0.75，classify these indicators appropriately to simplify the evaluation and examination indicator. Evaluating indicator cluster method is simple and convenient and has the character of strong applicability.

Investigation of Entropy and Gray Theory in Coal and Gas Outburst Controlled Factors Assessment

Using gray theory established entropy weight and gray association model in analyzing the mostly infection factors of coal and gas outburst, entropy theory was used to calculate the weights of contamination. Analysis of sample data, in accordance with the order of gray correlative degree, it is found out the closest relations with the outstanding master factors to identify the most likely sensitive indicators to improve the accuracy of coal and gas outburst forecast prominently.

Fault-tolerant federated filtering algorithm based on improved B-style grey relationship degree and balance coefficient

To analyze the difficulties of detection under "soft" failures,an improved B-style grey relationship degree based on the moving state propagator for the Federated Filter(FF) was developed.The mode can obtain the highest fault tolerance quality without feedback,mutual pollution was avoided by using FF.Besides,an adaptive balance coefficient and its algorithm were presented to balance the optimal information sharing approach and the fault tolerance one.According to the algorithm in this paper,the information sharing coefficients were adaptively adjusted by the failure grade,and the approximate highest fusion accuracy was ensured.The algorithm is characterized by low calculation,simple configuration and high precision,and it is suitable to practical application.The simulation results indicate that fusion accuracy under the largest range of failures increases approximately 28.5%,which shows the fusion accuracy under failures is efficiently improved and the approximate highest fusion accuracy of whole process is realized.

The Coal Mining Methods Selection of Large Mine Based on Grey Relevance Analysis

In order to select the reasonable coal mining method of large mine, analysing the main factors of affecting the mining method and establishing the evaluation index system of coal mining methods selection to large mine, then using Analytic Hierarchy Process (AHP) to calculate the weight of each index. The grey correlation evaluation model of mining method was established for large mine by using grey relevance analysis of the grey theory, this model can calculate grey relevance coefficient and grey relevance degree between the evaluation system indexes by determining the reference sequence and comparative sequence of the evaluation object, and according to the size of the grey relevance degree to determine the reasonable coal mining methods. The evaluating case analysis shows this model is practical to select the reasonable coal mining method of large mine, and it is a scientific decision-making method.

Research on Methods to Improve Parallel Coordinates Visualization

In parallel coordinate plots, the density could not be represented where the polylines were over intensive. Based on the problem, the aggregation degree conception was proposed. The three-dimension parallel coordinate system with the aggregation degree axis was built, and the mapping from aggregation degree to gray degree value was built. The three-dimension polylines with gray color were projected onto the original two-dimension plane, and the two-dimension parallel coordinate plots with the aggregation degree information were acquired. The results show that they are effective in representing the density change of polylines on parallel coordinate plots.

Skill assessment in software projects by grey possibility degree

It is well known that the development of large software systems can be very challenging. Research shows that inadequate planning and management of human resources can sometimes lead to catastrophic failures in building these systems. Careful planning requires the consideration of the relationships between skills developed by engineers considered for these systems and those required in building high-quality software systems. However, there is a noticeable absence of reliable methodologies for assessing these relationships. This paper presents a method that evaluates skill relationships based on a set of task and resource specific skill parameters. These parameters are used as measures in a multi-attribute decision problem to evaluate the skills of each engineer candidate. The problem is solved by using the concept of possibility degree for ranking two grey numbers in grey systems theory. A case study is presented to show how this method can be applied in these problems.

Verhulst Model of Interval Grey Number Based on Information Decomposing and Model Combination

Grey Verhulst models are often employed to simulate the development tendency with the characteristic of saturated process of S curve. However, the uncertainty of interval grey numbers will be increased since the boundaries of interval grey number are extended by the Axiom of nondecreasing grey degree in the existing Verhulst modeling method. In this paper, the interval grey number is divided into two real number parts, that is, “white” and “grey” parts. Then the “white” and “grey” parts are simulated and forecasted by building the grey Verhulst model and DGM (1, 1) model, respectively. To some degree, this method resolves the issue of amplifying the range of interval grey number. Finally, an example is used to compare the simulation performance between the new model and the traditional model, and the results show that the new model is superior to the other model.

Prediction of membrane protein types by using dipeptide and pseudo amino acid composition-based composite features

Membrane proteins are fundamental elements of a cell that play essential roles nearly in all the cellular processes. Prediction of membrane protein types using biological experiments are often complicated and time consuming. Therefore it is highly desirable to develop a robust, reliable and high-throughput silico method to predict membrane protein types. In this study, the authors have used two feature extraction strategies known as dipeptide and pseudo amino acid (PseAA) compositions for classification of membrane proteins types. In addition, a composite model is also developed by concatenating dipeptide and PseAA composition based features. Further, two feature selection methods such as neighbourhood preserving embedding and locally linear embedding (LLE) are applied to reduce the dimensionality of the composite model. The performance of these feature extraction strategies is evaluated using four different classifiers: K-nearest neighbour, probabilistic neural network (PNN), support vector machine (SVM) and grey incidence degree. The highest success rates have been observed using the LLE-based reduced features. SVM has yielded the best accuracy of 88.2% in case of jackknife test. Although in case of independent dataset test, PNN has obtained the highest accuracy of 98.4%. Performance measures other than accuracy are also used such as ‘Mathew correlation coefficient’, sensitivity and precision. The authors simulated results show that the composite model has significantly discriminated the types of membrane protein and might be useful for future research and drug discovery.

Analysis of the Relevancy between Energy Consumption and Environmental Pollution Based on Grey Theory

In order to analyze the relationship between energy consumption and environmental pollution, grey theory has been applied. By making use of the correlative statistic data, inherent grey relevancy between energy consumption and environmental pollution of China has been discussed as an example, and different impact degrees that various energies consumption have on environmental quality of China has been ascertained by calculating the grey relevancy degree. The results show that fuel oil, coal, coal oil, crude oil and gasoline are the energy varieties that have great impact on environmental quality, while natural gas has less impact on environmental quality. In the end, energy consumption development strategies that can improve environmental quality have been put forward to offer scientific gist for adjusting energy consumption structure, improving environmental quality and actualizing sustainable development between energy consumption and environment.

General grey numbers and their operations

PurposeThe purpose of this paper is to advance new rules about operations of grey numbers.Design/methodology/approachThe paper first puts forward the definitions of basic element of grey number and general grey number. The operation axiom, operation rules of general grey numbers and a new algebraic system for general grey numbers are built based on the “kernel” and the degree of greyness of grey numbers.FindingsUp to now, the operation of general grey numbers has been transformed to operation of real numbers; thus, the difficult problem for set up operation of general grey numbers has been solved to a certain degree.Practical implicationsThe method exposed in the paper can be used to integrate information from a different source. The operation of general grey numbers could be extended to the case of grey algebraic equation, grey differential equation and grey matrix which includes general grey numbers. The operation system of general grey numbers also opened a new passageway for research on grey input‐output and grey programming, etc.Originality/valueThe new conception of a basic element of grey number and general grey number was given for the first time in this paper. The novel operation rules of general grey numbers were also constructed.

Pregnant Environment Analysis Model of Earthquake-Induced Underground Engineering Slope Based on Gray Relation and Variation

Complicated and variational relation among the factors of the pregnant environment, resulted that, it was hard to orderly sentence the connection from the pregnant risk factors to the overall slope safety. Through differentiating risk relational factors into the extreme variation, same directional matrix was established for the pregnant environment safety of earthquake-induced underground engineering slope. Gray relation Analysis Model was established on the pregnant environment of earthquake-induced underground engineering slope, which was integrated with entropy information of same directional matrix. Model calculated out the gray relation degree and variation coefficient among the sample data sequence of the observed units, and finally sentenced the overall safety of underground engineering slope systemically. Example showed that toward the multi-objective decision-making problem for the safety assessment of underground engineering slope, model possessed with a scientific, simple, practical feature, whose outcome revealed the full status of the slope pregnant environment.

Course Evaluation Model and its Application Based on Grey Correlation Analysis Method

Combining ideal solving method and Euclidean distance, the article constructs a new course evaluation model based on grey correlation analysis method. First, idealizes and standardizes the quantitatively treated evaluation indicators, constructs positive and negative incidence matrix. Then, defines grey correlation distance degree, puts forward an evaluation way close to the optimal solution and far from the worst one. At last, introduces the actual use of model by combining a course evaluation, and tests its accuracy and feasibility.