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.

基于LSTM模型的船舶材料成本滚动预测

船舶建造周期长、材料成本占比大,易受大宗商品价格指数和汇率等多个因素的影响,造成实际完工成本与报价估算存在较大误差的情况。采用灰色关联分析(Grey Correlation Analysis,GCA)方法识别材料成本的影响因素,基于长短期记忆网络(Long Short-Term Memory,LSTM)模型构建船舶材料成本滚动预测模型,并使用某造船企业53艘64000 t散货船63个月的材料成本数据和对应的影响因素数据进行试验分析。结果表明,预测数据与实际数据误差在可接受范围内,可证明所选择方法和构建模型的有效性。研究结果对制造过程的成本实时预测和控制具有现实意义。

Atlas-based deep gray matter and white matter analysis in Alzheimer's disease: diffusion abnormality and correlation with cognitive function

Objective To identify the diffusion alterations of deep gray matter(GM)and white matter(WM)among Alzheimer’s disease(AD),mild cognitive impairment(MCI)and healthy people by atlas-based analysis(ABA),and to investigate the respective relationship with cognitive function.Methods Twenty-one AD patients(AD group),8 MCI patients(MCI group)and

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.

基于GCA和LSTM神经网络的配电网网损预测

配电网馈线和节点较多且负荷多变,使得配电网中损耗分析预测困难。为此提出一种基于灰色关联分析(grey correlation analysis,GCA)和长短期记忆(long short-term memory,LSTM)神经网络的配电网网损预测方法。首先采用GCA法定量分析输入变量与网损的关联度,确定最佳特征指标;然后基于LSTM网络提取多时间尺度下网损的时间序列特征,并对配电网网损进行预测,以增强预测模型对时间的感知能力,提高预测精度。算例测试结果表明:该网损预测模型具有较高的精确度和可靠性,可应用于配电网网损预测,为电网降损节能提供决策依据。

HHT和GCA-NBC在S700K转辙机故障诊断中的应用

针对S700K转辙机故障现象与故障类型之间存在不确定性关系,提出一种基于希尔伯特-黄变换(HHT),灰色关联分析(GCA)和朴素贝叶斯分类器(NBC)的转辙机故障诊断方法。首先对转辙机功率曲线进行HHT,提取转辙机故障特征;其次采用属性约简对故障特征进行约简降低其维度;最后运用GCA-NBC模型将约简后的故障特征融合,通过网络推理计算各类型的后验概率值,从而确定故障类型。通过实例分析,验证了该方法的准确性和快速性。

Evaluation of Farmland Drainage Water Quality by Fuzzy–Gray Combination Method

The complex relationships between indicators and water conditions cause fuzzy and gray uncertainties in evaluation of water quality. Compared to conventional single-factor evaluation methods, the combination evaluation method can consider these two uncertainties to produce more objective and reasonable evaluation results. In this paper, we propose a combination evaluation method with two main parts:(1) the use of fuzzy comprehensive evaluation and gray correlation analysis as submodels with which to consider the fuzzy and gray uncertainties and(2) the establishment of a combination model based on minimum bias squares. In addition, using this method, we evaluate the water quality of a ditch in a typical rice–wheat system of Yixing city in the Taihu Lake Basin during three rainfall events. The results show that the ditch water quality is not good and we found the chemical oxygen demand to be the key indicator that affects water quality most significantly. The proposed combination evaluation method is more accurate and practical than single-factor evaluation methods in that it considers the uncertainties of fuzziness and grayness.

基于DEA-GCA法的导弹装备保障能力综合评估

针对导弹装备保障体系结构复杂,保障能力模型评估片面与不足的问题,文中将数据包络分析法与灰色关联度分析法相结合(DEA-GCA),构建了导弹装备保障效能综合评估模型并进行了计算。结果表明,该型导弹装备保障效率与保障人员考评合格率、装备完好率、保障时间高度相关,保障单位要充分利用与加强保障资源建设,方能有效提高导弹装备保障效率。

玉米DH系穗部性状配合力及其一般配合力相关性分析

本文利用西南核心材料及其以它们组建基础材料诱导选育出的DH系,通过不完全双列杂交试验,研究玉米6个产量性状的一般配合力(GCA)、特殊配合力(SCA)、遗传参数和GCA间的相互关系。结果表明:6个农艺性状的GCA和SCA均达极显著水平;控制这6个性状的基因效应中主要以加性基因效应为主,非加性基因效应较小;单株产量GCA与行粒数、穗长、结实长和穗粗4个性状的GCA呈极显著正相关关系,与穗行数相关不显著,本试验材料中DH系09Y1035、10Y1026、09Y1027、10Y1028和10Y1031、09Y1032、09Y1016、09Y1019、09Y1029、09Y1018共10个自交系GCA综合性状较优,系组配强优势杂交组合的优良自交系。通径分析表明:行粒数、穗长、穗粗GCA对单株产量GCA有较大的直接作用,是影响单株产量GCA的重要因素。

基于均匀试验的半填半挖路基边坡稳定性灰色关联分析法

首先对山区半填半挖路基边坡稳定性影响因素进行了分析,在总体上将其归纳为填料物理力学参数和填方区的几何参数;其次在深入研究边坡稳定影响因素敏感性分析方法的基础上,提出灰色关联分析特别适合于山区路基边坡稳定性这种复杂而且具有不确定性问题的分析和评价,并对传统灰色关联分析中的不足之处加以改进;然后结合均匀试验设计能使试验次数和计算工作量大大减少的优点,建立起基于改进灰色关联的山区路基边坡稳定性均匀试验分析方法;最后用该方法对某山区公路半填半挖路基边坡变形稳定性及强度稳定性影响因素进行了分析。结果表明,填方区填料的物理力学参数和几何参数对半填半挖路基变形均比较敏感,而对于强度稳定性填方区填料物理力学参数比其几何参数敏感,这可为预防和控制该类路基因强度不足失稳及填、挖结合面的差异沉降提供重要指导,为设计、施工及加固提供重要参考。

模拟降雨侵蚀产沙量与其影响因子的灰关联分析

在20°和25°坡度上,选用4种雨强条件进行人工模拟降雨实验,对土壤水蚀动力过程进行了系统模拟,并运用灰色关联度的分析方法,研究了坡面侵蚀产沙量与其影响因子之间的关联程度。研究结果表明,在实验条件下,雨强与坡面降雨径流产沙量的关联度最大,水流功率次之,可以用雨强和水流功率来描述坡面径流产沙量,并建立了坡面径流产沙量与雨强和水流功率的相关关系式。

南宁市粮食生产影响因素分析

本文以南宁市为例,运用灰色关联度和生产函数,分析了1997-2003年粮食生产的影响因素及其贡献率。粮食产量灰色关联度分析作出关联因子排序:粮食单产>耕地面积>粮食作物播种面积>化肥施用量>有效灌溉面积>农村用电量>农业机械总动力>农药施用量,表明粮食单产、耕地面积与粮食作物播种面积对粮食总产的影响最大,从投入角度分析粮食总产与化肥施用量、有效灌溉面积关联度大;基于生产函数的贡献率分析表明:化肥施用量、农业科技进步、粮食播种面积、农业机械总动力、有效灌溉面积、农业劳动力对粮食增长的贡献率分别为40.08%、27.62%、12.12%、10.78%、8.91%、0.49%,说明7年来粮食增长主要依靠化肥投入、农业科技进步,农业劳动力对粮食产量增加作用微小。