Application of gray correlation analysis and artificial neural network in rock mass blasting

Studied forecasting and controlling the blasting fragmentation by using artifi- cial neural network for multi-ingredients. At the same time, according to the characteris- tic of multi-parameters input to network model, the gray correlation theory was employed to find out key factors, which can not only save time of computation and parameters in- put, but improve the stability of the model.

Comprehensive Evaluation of Flood and Flood in the Yellow River Basin Based on Gray Correlation Analysis

Due to the concentrated rainfall and serious soil erosion in July and August in the Yellow River Basin, the flood discharge is not timely leading to serious floods. Therefore, a reasonable assessment of the flood-affected areas, advance arrangements for the deployment of the Yellow River basin flood disaster prevention and control plays a decisive role. For this purpose, this paper proposes a level assessment method based on the flood which analyzes three factors related to flooding disaster (disaster impact range, social index, and property index) through the gray correlation analysis method, to evaluate the level of flood disaster. Different from the traditional assessment method, which evaluates the nature of flood from the perspective of indicators such as frequency, duration, and magnitude, or indirect factors such as rainfall and soil loss, this paper conducts qualitative calculation of macro-scale indicators from the perspective of post-disaster losses in previous years. This study provides a new way of thinking and method for the classification of the flood disaster, which has certain practical application value under the condition of conforming to its own use.

Influencing Factors of Fabric-Skin Adhesion Based on Gray Correlation Analysis Method

Fabric-skin adhesion was objectively described by the indices of the maximum adhesion force F_(max) , the maximum separation distance L_(max) ,and adhesion work W as well as the adhesion force-separation distance curve. Firstly,gray correlation analysis method was adopted to investigate the correlation levels between adhesion indices,and secondly the relative importance of fabric structural parameters to fabric-skin adhesion,as well as the correlation levels between skin adhesion, water absorption, and wicking properties of the fabric. The results prove that W exhibits clear correlations with both F_(max) and L_(max) , yet the relevance between F_(max) and L_(max) is weak. Fabric adhesion indices are most associated with fabric mass and least with fabric thickness,whereas fabric wicking and water absorption present closest correlation with fabric thickness. Therefore, it is concluded that the relevance between fabric wicking, water absorption, and skin-adhesion properties are rather comprehensive than straight.

Identification of key genes and active anti-inflammatory ingredients in Panax medicinal plants by climate-regulated callus culture combined with gene-component-efficacy gray correlation analysis

Objective:We aimed to establish a novel strategy for identifying key genes and active anti-inflammatory ingredients in Panax medicinal plants.Methods:First,fresh roots of 2-year-old Panax plants,including P.ginseng C.A.Mey.,P.quinquefolium L.,P.notoginseng(Burk.)F.H.Chen,P.japonicus C.A.Mey.,P.japonicus Mey.var.major(Burk.)C.Y.Wu et K.M.Feng,were selected as explants,and callus formation was induced under three experimental temperatures(17,24,and 30℃).Second,high-performance liquid chromatography-mass spectrometry was used to analyze the saponin content of the callus.Nitric oxide reduction efficacy was used for“component-efficacy”gray correlation analysis to find the active anti-inflammatory ingredients.Quantitative reverse-transcription polymerase chain reaction(qRT-PCR)was used to determine the inflammatory factors and verify the active ingredients’anti-inflammatory effects.Finally,qRT-PCR was used to detect the expression of key genes in the callus,and“gene-component”gray correlation analysis was used to examine the relationships between the regulatory pathway of the genes and the components.Results:Among the three experimental temperatures(17,24,and 30℃),the lowest temperature(17℃)is the most suitable for generating Panax callus.Lower-latitude native Panax notoginseng is more adaptable under high culture temperatures(24℃and 30℃)than other Panax plants.The ginsenoside contents of the callus of P.notoginseng and P.japonicus were the highest under similar climate conditions(17℃).Major anti-inflammatory components were G-Rh1,G-Rb1,G-Rg3,and G-Rh6/FloralGKa.CYP76A47 contributed to the accumulation of anti-inflammatory components.Conclusions:This study provides a strategy for the gene-component-efficacy correlational study of multi-component,multi-functional,and multi-purpose plants of the same genus.

Correlation knowledge extraction based on data mining for distribution network planning

Traditional distribution network planning relies on the professional knowledge of planners,especially when analyzing the correlations between the problems existing in the network and the crucial influencing factors.The inherent laws reflected by the historical data of the distribution network are ignored,which affects the objectivity of the planning scheme.In this study,to improve the efficiency and accuracy of distribution network planning,the characteristics of distribution network data were extracted using a data-mining technique,and correlation knowledge of existing problems in the network was obtained.A data-mining model based on correlation rules was established.The inputs of the model were the electrical characteristic indices screened using the gray correlation method.The Apriori algorithm was used to extract correlation knowledge from the operational data of the distribution network and obtain strong correlation rules.Degree of promotion and chi-square tests were used to verify the rationality of the strong correlation rules of the model output.In this study,the correlation relationship between heavy load or overload problems of distribution network feeders in different regions and related characteristic indices was determined,and the confidence of the correlation rules was obtained.These results can provide an effective basis for the formulation of a distribution network planning scheme.

Response of Ecosystem Service Value Based on Land Use Changes and Analysis of its Driving Factors in Typical Hilly Region with Red Soil

The contribution rate of ecosystem service value variation was used to analyze the effects of land use changes on the changes of ecosystem service value in Xingguo County during 1996-2005.Grey integrated correlation was employed to explore the contribution level of the indicators such as total population,urbanization level,proportion of primary industry and investment of social fixed assets on ecosystem service value,and the correlation analysis was also carried out.The results showed that the ecosystem service value in Xingguo County during 1996-2005 mainly was woodland,and the decrease of woodland area was the major reason for the sustained reduction of ecosystem service value.With the further increase of market demand and the incentives of local government,the garden area rapidly increased during 2001-2005,and the influence degree of garden towards the changes of ecosystem service value was only second to woodland,ranking No.2.Four socio-economic indicators had different correlation degree with ecosystem service value during the different research periods.Total population,urbanization level and proportion of primary industry had high correlation degree with ecosystem service value,whereas the influence degree of various socio-economic indicators on ecosystem service value was equal with each other day by day.Urbanization level,investment of social fixed assets and total population had significant negative correlation with ecosystem service value,while the proportion of primary industry had positive correlation with ecosystem service value.

Analysis of Main Climatic Factors Affecting Potato Yields of Western Guizhou

The climatic factors affecting potato yields in western Guizhou were analyzed by using the way of grey correlation degree and principal component analysis.The average yield of potato from 1978 to 2008 in western Guizhou was used as the sequence of numbers for reference.And the climatic factors including accumulated temperature(≥5 ℃),average temperature,precipitation,sunshine hours,daily average maximum temperature and daily average minimum temperature from March to August of potato at growth stage were used as the series for comparison.The results showed that the three integrative factors including temperature,moisture and light had a synergistic effect on potato production.The heat factor played a leading role in potato production with abundant light and ample water supply.Gray correlation analysis and principal component analysis could be used to estimate the influence factors of potato yield in western Guizhou.Very good agreement was found between the evaluation results obtained by the above-mentioned two methods.

Comprehensive Evaluation Model of Reservoir Operation Based on Improved Set Pair Analysis

A comprehensive evaluation model based on improved set pair analysis is established. Considering the complexity in decision-making process, the model combines the certainties and uncertainties in the schemes, i.e., identical degree, different degree and opposite degree. The relations among different schemes are studied, and the traditional way of solving uncertainty problem is improved. By using the gray correlation to determine the difference degree, the problem of less evaluation indexes and inapparent linear relationship is solved. The difference between the evaluation parameters is smaller in both the fuzzy comprehensive evaluation model and fuzzy matter-element method, and the dipartite degree of the evaluation result is unobvious. However, the difference between each integrated connection degree is distinct in the improved set pair analysis. Results show that the proposed method is feasible and it obtains better effects than the fuzzy comprehensive evaluation method and fuzzy matter-element method.

Carbon efficiency evaluation method for urban energy system with multiple energy complementary

Urban energy systems(UESs)play a pivotal role in the consumption of clean energy and the promotion of energy cascade utilization.In the context of the construction and operation strategy of UESs with multiple complementary energy resources,a comprehensive assessment of the energy efficiency is of paramount importance.First,a multi-dimensional evaluation system with four primary indexes of energy utilization,environmental protection,system operation,and economic efficiency and 21 secondary indexes is constructed to comprehensively portray the UES.Considering that the evaluation system may contain a large number of indexes and that there is overlapping information among them,an energy efficiency evaluation method based on data processing,dimensionality reduction,integration of combined weights,and gray correlation analysis is proposed.This method can effectively reduce the number of calculations and improve the accuracy of energy efficiency assessments.Third,a demonstration project for a UES in China is presented.The energy efficiency of each scenario is assessed using six operational scenarios.The results show that Scenario 5,in which parks operate independently and investors build shared energy-storage equipment,has the best results and is best suited for green and low-carbon development.The results of the comparative assessment methods show that the proposed method provides a good energy efficiency assessment.This study provides a reference for the optimal planning,construction,and operation of UESs with multiple energy sources.

Research on the Influencing Factors of Passenger Traffic at Sanya Airport Based on Gray Correlation Theory

Many factors have an effect on the passenger traffic of Sanya Airport.In this paper,seven factors that have a great influence on passenger demand,namely accommodation and catering turnover,number of overnight visitors received,total tourism revenue,average room opening rate of tourist hotels,flight movements,airport passengerflow and railway station passengerflow,are selected to conduct gray correlation analysis on these factors to provide a research basis for passengerflow prediction.

Quantitative Study on the Relationship between Water Disaster and Grain Production of Hubei Province in the 1990s

The research explored variation coefficient of grains and analyzed the fluctuations of grains in Hubei in the 1990s in order to investigate quantitative cor- relation between grain production and water-related disaster. The conclusion is that the effective irrigated area and growing structure are major factors influencing grain production capacity, whose grey relational degrees were 0.91 and 0.85 with grain production, respectively. These indicated that water-related disasters have significant effects on grain yield in Hubei Province.

Research on Global Higher Education Quality Based on BP Neural Network and Analytic Hierarchy Process

Having a universal, fair, democratic and practical higher education system plays a particularly important role in the future development of the country. However, the higher education system in various countries is uneven. It is of great significance to establish a general evaluation system for the development of global education. In this paper, 23 indicators are preliminarily selected from the education data of Universitas 21 and Global Statistical Yearbook. After the gray correlation analysis, 12 indicators were selected. On the one hand, principal component analysis is used to reduce the dimension of these 12 indicators in 50 countries, and the first four principal components with cumulative contribution rate of 99% are finally selected as the input parameters of BP neural network. On the other hand, 12 indicators are divided into four aspects as the standard of scheme decision-making. Finally, a higher education quality evaluation and decision-making model based on BP neural network and analytic hierarchy process are established. Then eight countries are selected to use the model to evaluate their current higher education quality. Based on the input and evaluation results of the four aspects of higher education in various countries, the analytic hierarchy process is used to make program decision, and several improvement suggestions are put forward for the current education policies of various countries.

A trust-based method for selection of contractors in construction industry

This paper presents a method for construction contractor selection based on trust building. By classifying criteria into three types of trust and applying gray correlation analysis, the presented method concerns multi-criteria for evaluation other than price, selects trust- and selection-related criteria, provides approaches for indicator quantification and determines the contractor on the basis of gray correlation degree.

Effect of Vegetation and Precipitation upon Runoff and Sediment Production on Slope Lands of the Loess Area in China

According to fixed-position data for 1992-2003 from 16 runoff plots of Caijiachuan watershed which lie in Jixian County, Shanxi Province, in the loess area, this paper studied the relationship between vegetation and runoff and sedimentproduction on slope lands. The results showed as follows: 1) Runoffand sediment production in Robinia pseudoacacia forestand Pinus tabulaeformis forest had a high correlation with precipitation amount and rainfall intensity, but the correlation decreased gradually with the increase of canopy density; 2) The secondary forest had better function of soil and water conservation than artificial R. pseudoacacia forest, and runoff and sedimentproduction in the former in an individual rain event was 65%-82% and 23%-92% lower than thosein the latter, respectively;3) The difference ofrunoff and sediment production in several land uses was very distinct. Runoff and sediment production in Ostryopsisdavidiana forest and the secondary forest were the least; runoff and sediment production in artificial R. pseudoacacia forest and P. tabulaeformis forest were 5-fold as much as those in O. davidiana forest. Besides, runoff and sediment production in mixed stand of apple trees and cropswere 16.14-fold and 2.96-fold higher than that in O. davidiana forest, respectively, but theamount decreased obviously after high-standard soil preparation for theformer;4) Based on gray correlation analysis of variousfactorsaffecting runoffand sedimentproduction on slope lands, it can be seen that stand canopy density and herb and litter biomass werethe most significant ones, whosegray correlation valuesall exceeded 0.6. Therefore, mixed forest with multi-layer stand structure and shrub forest should be developed in vegetation reconstruction of the loess area, which help to increase coverage and litter thicknessto cut down the runoffand sediment production dramatically on slope lands.