Grey Correlation Analysis Method Research Articles

Dynamic Changes of NDVI in the Growing Season of the Tibetan Plateau During the Past 17 Years and Its Response to Climate Change.

The fragile alpine vegetation in the Tibetan Plateau (TP) is very sensitive to environmental changes, making TP one of the hotspots for studying the response of vegetation to climate change. Existing studies lack detailed description of the response of vegetation to different climatic factors using the method of multiple nested time series analysis and the method of grey correlation analysis. In this paper, based on the Normalized Difference Vegetation Index (NDVI) of TP in the growing season calculated from the MOD09A1 data product of Moderate-resolution Imaging Spectroradiometer (MODIS), the method of multiple nested time series analysis is adopted to study the variation trends of NDVI in recent 17 years, and the lag time of NDVI to climate change is analyzed using the method of Grey Relational Analysis (GRA). Finally, the characteristics of temporal and spatial differences of NDVI to different climate factors are summarized. The results indicate that: (1) the spatial distribution of NDVI values in the growing season shows a trend of decreasing from east to west, and from north to south, with a change rate of −0.13/10° E and −0.30/10° N, respectively. (2) From 2001 to 2017, the NDVI in the TP shows a slight trend of increase, with a growth rate of 0.01/10a. (3) The lag time of NDVI to air temperature is not obvious, while the NDVI response lags behind cumulative precipitation by zero to one month, relative humidity by two months, and sunshine duration by three months. (4) The effects of different climatic factors on NDVI are significantly different with the increase of the study period.

A Grey Correlation Analysis Method for Relationship of the Overseas M&A and Business Growth of Commercial Banks

While the Chinese banks have started the impact of foreign banks. At the same time, rising pressure on foreign exchange reserves and appreciation of the renminbi has prompted Chinese banks to go abroad and diversify their risks. The financial crisis of 2008 has caused the continued turbulence of the major financial markets around the world, and the valuation of foreign financial institutions has been drastically shrinking, providing opportunities for Chinese banks to carry out overseas M&A. Based on the overseas M&A status of Chinese commercial banks, this paper sums up the characteristics of the overseas M&A. Then taking a series of overseas M&A conducted by ICBC from 2006 to 2011 as an example, it analyzes the relationship between M&A and performance growth using grey incidence model. The test shows: there is a positive correlation between both overseas M&A and interest rate differential with performance growth of ICBC, and overseas M&A transactions role in promoting the performance growth is significantly higher than the interest rate differential.

Grey Correlation Analysis of the Factors Influencing the Construction of Agricultural Products Logistics System in Ningxia

On the basis of analyzing the current situation of the construction of agricultural products logistics system in Ningxia, this paper finds out the various problems and influencing factors in the system construction, and then uses the gray correlation analysis method to sort the influence factors. The paper finds that the amount of the fixed assets investment in transportation, storage and postal industry and the purchase quantity of urban residents' agricultural products are the main influence factors. Suggestions are put forward to strengthen road planning, improve facilities and equipment and integrate the logistics demand of agricultural products in order to provide reference for the construction of agricultural products logistics system in Ningxia, and try hard to contribute to the optimization of agricultural product economic structure.

Determinants and Differences of Township Hospital Efficiency among Chinese Provinces.

This study aimed to measure the efficiency and change in efficiency over time of township hospitals among Chinese provinces, to decompose the difference in efficiency between districts, and to study the correlations between the difference in efficiency and its determinants. Based on Chinese provincial panel data, the empirical analysis was established using data envelopment analysis (DEA), Malmquist index, Theil index decomposition method and Grey correlation analysis method. First, it was found that the township hospitals in most provinces were operating in an inefficient state, and the township hospitals in most provinces achieved gains in efficiency. Second, from 2003 to 2016 the shrinkage of the difference in provincial efficiency of township hospitals progressed slowly. Intra-regional difference is the main cause of the overall provincial efficiency difference of Chinese township hospitals, while inter-regional difference is the minor cause of the overall difference. Third, the correlation between the difference of overall provincial efficiency and the difference of economic development level is the highest among all the correlations, while other determinants rank second to seventh place in their degree of correlation with respect to the overall difference in provincial efficiency. Furthermore, the correlations between the intra-regional difference of provincial efficiency of Chinese township hospitals and its determinants vary tremendously across regions. Based on our findings, we can conclude, first, that efforts should be made to improve the overall provincial difference in efficiency of Chinese township hospitals, and enhance the utilization level of input resources, and to reduce resource waste. Second, in order to shrink the overall provincial efficiency of Chinese township hospitals, the most important measure that should be taken is to improve the economic development level in relatively backward provinces in order to lay a solid economic foundation for the improvement of efficiency and shrink the differences in efficiency between provinces. Third, more attention should be paid to the shrinkage of intra-regional efficiency differences in Chinese township hospitals, while the narrowing of inter-regional efficiency difference should not be ignored. For each region, it is necessary to recognize the difference in the relative importance of determinants, and to make development strategies according to local conditions so as to make full use of local characteristics and advantages.

A New Calculating Method of Pressure Response Time of Pneumatic Brake Pipe Based on Experiments

Air brake system is one of the common braking methods for buses and trucks; its excellent performance guarantees the safety of the vehicle and the stability of the braking. As an important part of the pneumatic brake system, the brake pipe is an important factor influencing the pressure response time of the pneumatic brake system. Based on the exploratory experiment of pneumatic brake pipe, the influence of pipe length, pipe diameter, inlet sonic conductance, initial pressure, and supply pressure on pipe pressure response time was analyzed by fuzzy gray correlation analysis method. The results show that tube length is the most important factor affecting the pressure response time. Combined with the analysis results of gray correlation degree, the experimental scheme of the response time of the pneumatic brake pipe was designed by the response surface experimental design method. Based on the multiparameter analysis method, the influence of the experimental parameters on the pipe pressure response time was analyzed. Based on the experimental data, the form of calculation formula is derived by dimension analysis method, which provides a theoretical basis for the selection of pneumatic brake pipes and the design of air brake system.

Primary Pollutants and Air Quality Analysis for Urban Air in China: Evidence from Shanghai

In recent years, China's urban air pollution has caused widespread concern in the academic world. As one of China's economic and financial centers and one of the most densely populated cities, Shanghai ranks among the top in China in terms of per capita energy consumption per unit area. Based on the Shanghai Energy Statistical Yearbook and Shanghai Air Pollution Statistics, we have systematically analyzed Shanghai’s atmospheric pollutants from three aspects: Primary pollutants, pollutants changing trends, and fine particulate matter. The comprehensive pollution index analysis method, the grey correlation analysis method, and the Euclid approach degree method are used to evaluate and analyze the air quality in Shanghai. The results have shown that Shanghai's primary pollutants are PM2.5 and O3, and the most serious air pollution happens during the first half of the year, particularly in the winter. This is because it is the peak period of industrial energy use, and residential heating will also lead to an increase in energy consumption. Furthermore, by studying the particulate pollutants of PM2.5 and PM10, we clearly disclosed the linear correlation between PM2.5 and PM10 concentrations in Shanghai which varies seasonally.

Study on corrosion rate of buried gas steel pipeline in Nanjing based on the GM(1, N) optimization model

In view of the complex and fuzzy corrosion mechanism of buried gas steel pipelines, the grey correlation analysis method is used to find out the main factors affecting the corrosion rate and sort them by association degree. And then the corrosion rate model of buried natural gas steel pipeline is established based on GM (1, N) model and OGM (1, N) (an optimization method for the GM (1, N)) model. Results show the main factors affecting the corrosion rate of buried steel pipelines in Nanjing are service life, pipeline protection measures, soil resistivity and stray current. Compared with the GM (1, N) model, the accuracy of OGM (1, N) model is greatly improved. OGM (1, N) model can effectively simulate pipeline corrosion rate considering multiple factors, which has a certain reference value for the study on residual life of buried gas steel pipelines.

Using grey relational analysis to analyze influential factor of hand, foot and mouth disease in Shenzhen

Purpose Hand, foot and mouth disease (HFMD) is a common infectious disease in infants and children. HFMD has caused millions of cases and a large epidemic worldwide. A number of studies have shown that the incidence of HFMD is closely related to various factors such as meteorological factors, environmental air pollution factors and socio-economic factors. However, there are few studies that systematically consider the impact of various factors on the incidence of HFMD. The paper aims to discuss these issues. Design/methodology/approach This study used grey correlation analysis and principal component analysis (PCA) method to systematically analyse the impact of meteorological factors, health resource factors, socio-economic factors and environmental air pollution factors on the incidence of HFMD in Shenzhen. Findings The incidence of HFMD in Shenzhen was affected by multiple factors. Grey correlation analysis found eight influencing factors which are as follows: volume of industrial waste gas emission; the days of air quality equal to or above grade; the volume of industrial nitrogen oxide emission; precipitation; the mean air temperature; the gross domestic product; the expenditure for medical and health care; and the gross domestic product per capita. PCA found that the gross domestic product, the volume of industrial soot emission, the relative humidity, and the days of air quality equal to or above grade have a higher load value. Originality/value This study is the one of the first studies that apply the grey correlation analysis to analyse the influencing factors of HFMD in the English literature, which to some extent fills up the blank in this field.

Dynamic and its driving factors of soil potential acid in croplands of Fujian Province, China.

Soil potential acid is one of the potential factors limiting plant growth, and also an important base in soil acidity regulation. The potential acid and pH value of surface soil samples of cultivated lands in Fujian Province were proportionally selected and measured, and then the optimized relational model between soil pH and potential acid value was fitted. The 1:50 000 databases of cropland soil potential acid in 1982, 2008 and 2016 were established by using the topsoil pH data of 36777, 236445 and 21269 sampling sites collected in 1982, 2008 and 2016 respectively. The dynamics of cropland soil potential acid in Fujian Province and its driving factors were explored by the integrative method of GIS and grey correlation analysis. The results showed that the quantities of soil potential acid in cropland generally increased in Fujian Province from 1982 to 2016. Compared with 1982, the averages of soil potential acid in 2008 and 2016 increased 1.30 and 1.49 cmol·kg-1, respectively. The increase rate of soil potential acid from 1982 to 2008 was 0.03 cmol·kg-1·a-1 higher than that from 2008 to 2016. Meanwhile, the changes of cropland soil potential acid showed significant spatial difference. The change of cropland soil potential acid in Sanming was minimum, and the change in Longyan was maximum, being four times higher than that in Sanming. The change of soil potential acid in different use types of cropland was following the order: paddy field > irrigated land > dry land. The changes of soil potential acid in acid sulfate paddy soils, gleyed paddy soils and submergenic paddy soils were maximum, which were one time higher than the mean change across the whole Province, while the changes in latosolic red earths and salinized paddy soils were minimum, which were 25.7% and 28.4% of the mean change in the Province, respectively. The driving factors for the dynamics of cropland soil potential acid in Fujian Province included the application rates of nitrogen and phosphorus fertilizer, cation exchange capacity (CEC), clay content, pH and silt content, with grey correlation coefficient (absolute value) being higher than 0.92. Accordingly, it would be an effective approach to slow down the increase of cropland soil potential acid in Fujian Province to optimize fertilization management and apply alkaline ameliorant scientifically.

Analyzing Qualitative Changes of Rural Settlements due to Rural Furniture Establishment (Case Study: Zoeram Dehestan of Shirvan County)

Purpose- Planning for optimum distribution of physical services and furniture in order to improve people’s welfare is one of the major purposes for rural planners. Rural furniture is the main purpose of developing rural settlements to decrease environmental side effects. The quality of human environments in villages highly depends on the quality of infrastructures of physical welfare including rural furniture. Rural furniture not only improves the quality of villages, but also keeps them consistent and permanent. The present study involves analyzing rural furniture and their effects on the environmental quality of rural settlements in Zoeram Dehestan, Shirvan. Design/methodology/approach- In this research we used an analytical-descriptive approach and data was gathered through library information and field study. Statistical population involves all rural families of Zoeram that equals to 258 families randomly selected through Cochran Formula with error level of 0.06. We used a questionnaire that its reliability was confirmed by a specific academic panel and its validity was calculated through α-Chronback coefficient. We also used SPSS software to analyze the data. Findings- The results obtained from Chi Square Test show that among all dimensions, aesthetic and visual beauty factors with mean of 2.70 and among all rural furniture, infrastructural furniture with mean of 3.17 are the most effective factors in increasing the quality of physical environment. Also, results from Spearman Correlation and Simple Linear Regression Models show that there is a strong, direct, and meaningful relationship (Sig: 0.000) between rural furniture and the quality of physical environment. In the end, using Gray Correlation Analysis and Vikor Method, we get the results that in these villages with different qualities in rural furniture, environmental quality is not the same level and according to Spearman Correlation there is a strong, meaningful relationship between the quality of rural furniture and the quality of environment. Practical implications- Today it is vital to consider and improve the quality of rural settlements, since it has been a major concern of local administrators and rural planners. In this respect, analyzing and measuring the level of available rural accommodations can be a helpful tool to understand and to show differences and inequalities in villages in order to provide better life quality in rural areas and be able to obtain more successful goals and objectives in establishing rural stable development and constant population growth. Originality/value- No direct research and study considering changes in the quality of rural settlements due to establishing rural accommodations have been done so far. Therefore, it is worth performing a thorough, comprehensive research and study regarding both rural accommodations and quality of environment to show the differences and innovations in this field.

Prediction of District Heating Load Based on Grey Neural Network Model

In this paper, the gray correlation analysis method is used to evaluate the factors affecting the district heating load, and the gray prediction is combined with the BP neural network algorithm to establish a gray neural network structure, which can screen the factors affecting the heating load and predict the heating load. The heating load forecasting and verification of a district heating load is carried out. By comparing the prediction results and errors of the gray correlation GM(1, N) model, it is shown that the gray neural network model can select the appropriate influencing factors and exclude impact factors with low relevance in the heat load forecasting, improve the accuracy of heat load forecasting, and provide a theoretical basis for regional heat load forecasting.

Research on correlation of compositions with oestrogenic activity of Cistanche based on LC/Q-TOF-MS/MS technology

AbstractLC technology is a recognized method used worldwide to evaluate the quality of traditional Chinese medicines (TCM). The quality of TCM has a direct impact on its efficacy. Therefore, in order to thoroughly reveal how TCM exerts its efficacy, first of all, it is necessary to understand the material basis for its efficacy, and then to control the quality of active compounds. The application of the spectrum-effect relationship method is crucial for determining the pharmacological material basis. The goal of this paper was to investigate the underlying correlations between the chemical profiles and oestrogenic activity of Cistanche, to reveal the active compounds. The chemical profiles of Cistanche were recorded using HPLC/Q-TOF-MS/MS, and oestrogenic activity was determined by the Uterus growth test and the MTT assay. Then combining the results of bivariate analysis, principal component analysis and gray correlation analysis method, fifteen active compounds were identified. They are 8-epiloganic acid, salidroside, syringalide A 3’-α-l-rhamnopyranoside, cistanoside A, echinacoside, cistanoside F, cistanoside B, cistanoside C, osmanthuside B, acteoside, isoacteoside, tubuloside B, 2’-acetylacteoside, and two unknown compounds. This study lays a foundation for in vivo studies of Cistanche and for the development of its clinical application.

1995-2014年拉萨河流域水环境变化及其驱动力

PDF HTML阅读 XML下载 导出引用 引用提醒 1995-2014年拉萨河流域水环境变化及其驱动力 DOI: 10.5846/stxb201806031241 作者: 作者单位: 西藏自治区环境监测中心站,中国水利水电科学研究院流域水循环模拟与调控国家重点实验室,中国水利水电科学研究院流域水循环模拟与调控国家重点实验室,中国水利水电科学研究院流域水循环模拟与调控国家重点实验室,中国水利水电科学研究院流域水循环模拟与调控国家重点实验室,中国水利水电科学研究院 作者简介: 通讯作者: 中图分类号: 基金项目: 西藏自治区重点科技计划项目（Z2016C01G01/08）；国家重点研发计划（2016YFC0502103） Analysis on trend and driving force for water environmental change of the Lhasa River basin (1995-2014) Author: Affiliation: The Tibet autonomous region environmental monitoring center,China Institute of Water Resources and Hydropower Research,China Institute of Water Resources and Hydropower Research,China Institute of Water Resources and Hydropower Research,China Institute of Water Resources and Hydropower Research,China Institute of Water Resources and Hydropower Research Fund Project: 省、部研究计划基金 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:探究自然环境和人类活动影响下的河流水环境变化，对于流域水资源管理和保护有重要意义。目前从较长时间尺度上系统开展拉萨河流域水环境的研究较少，基于拉萨河流域达孜、卡林、才纳3个环境监测中心站近20年（1995-2014）的水质资料，综合单因子指数法和内梅罗指数法评估拉萨河流域水环境状况，并采用Mann-Kendall检验法分析其多年变化趋势。同时，从经济社会和自然环境两个方面通过灰色关联分析法识别了影响流域水环境变化的关键驱动因子，以期为流域水环境保护提供借鉴。结果表明：（1）总体上，拉萨河流域水环境状况良好，满足水功能区要求；（2）水体中pH、溶解氧、化学需氧量、总磷等指标的取值较高，在0.7左右，是拉萨河流域水环境需重点关注指标；（3）水环境质量稍有下降，内梅罗指数从1995年的0.62增加到2014年的0.73；（4）近20年来拉萨河流域水环境变化的主要驱动因子为降水量、牲畜存栏数、人口数、农村人口数和国民经济生产总值等，农牧非点源污染是拉萨河流域的主要污染源，要重点关注和管控。 Abstract:Studying the influence of the natural environment and human activities on river water environment is of great significance for the management and protection of river basin water resources. Systematic and long-term research on water environment of the Lhasa River Basin is needed to provide necessary technical support for scientific decision-making. Based on the water quality data of three environmental monitoring stations in the Lhasa River Basin (Dazi, Kalin, and Caina) over the past 20 years (1995-2014), the single factor index method and the Nemerow index method were applied to assess the water environment. The Mann-Kendall test was used to analyze the multi-year trends of the water environment. Further, the key driving factors affecting change in the water environment of the river basin were identified from the economic, social, and natural environment using the grey correlation analysis method, which can provide a reference for protection of the watershed water environment. The results showed that:(1) the overall water quality at the three environmental monitoring stations was in good condition and met the requirements of the water function zone; (2) the index of pH, dissolved oxygen, ammonia nitrogen, and total phosphorus was about 0.7 (higher than other indexes), and could be the main indexes affecting the water environment in Lhasa River Basin; (3) the water environment of the Lhasa River basin was in good condition with a certain degree of a downward trend, and the Nemerow index increased from 0.62 in 1995 to 0.73 in 2014; (4) The water environment has changed in the Lhasa River basin in the past 20 years, and was mainly affected by precipitation, livestock stock population, rural population, and GDP. The main source of pollution in the Lhasa River basin was non-point source pollution from rural areas and agriculture, which should be focused on and controlled in the future. 参考文献 相似文献 引证文献

Detection of spindle thermal state accuracy of vertical CNC machine tool

In order to test the thermal accuracy of spindle system of mining vertical CNC machine tools, to enhance the error compensation ability of the system accuracy detection model and improve the machine tool processing accuracy, a test platform for thermal accuracy of spindle system was constructed. Five-point method was used to test the thermal accuracy of spindle system, and thermocouple and infrared thermal imager were used to measure the spindle system. Temperature change data at key points of temperature rise are used to identify temperature sensitive measurement points by grey comprehensive correlation analysis method. A thermal accuracy prediction model based on cooperative quantum particle algorithm is constructed. The prediction effect of the model is evaluated. The experimental results show that the thermal accuracy detection model has high detection accuracy.

Application of Evaluation Algorithm for Port Logistics Park Based on Pca-Svm Model

Abstract To predict the logistics needs of the port, an evaluation algorithm for the port logistics park based on the PCASVM model was proposed. First, a quantitative indicator set for port logistics demand analysis was established. Then, based on the grey correlation analysis method, the specific indicator set of port logistics demand analysis was selected. The advantages of both principal component analysis and support vector machine algorithms were combined. The PCA-SVM model was constructed as a predictive model of the port logistics demand scale. The empirical analysis was conducted. Finally, from the perspective of the structure, demand, flow pattern and scale of port logistics demand, the future logistics demand of Shenzhen port was analysed. Through sensitivity analysis, the main influencing factors were found out, and the future development proposals of Shenzhen port were put forward. The results showed that the port throughput of Shenzhen City in 2016 was 21,328,200 tons. Compared with the previous year, it decreased by about 1.74 %. In summary, the PCA-SVM model accurately predicts the logistics needs of the port.

Photovoltaic Output Power Prediction Based on Weather Type

Precise prediction of photovoltaic (PV) output power can effectively improve the safe and stable operation of power grids. In this paper, the influence of weather types on the output of PV output power is analyzed. Based on extreme learning machine (ELM) neural network, a prediction model of PV power generation output taking into account weather types is established. The grey correlation analysis method is used to process the weather types, and the established ELM neural network prediction model is trained by using the prediction results of the improved equal-dimension grey (IEDG) model, and the trained model is used to predict the output of PV output power. Compared results show that the prediction model presented in this paper can predict the output of each day in different weather types. The results show that the proposed model based weather type is of high accuracy and reliability in predicting the output power of PV.

Transformer Topology Identification Method Based on GPU Acceleration

Traditional transformer topology identification methods have poor accuracy and efficiency and are easy to be interfered. Aiming at these problems, this paper proposes a transformer topology identification based on GPU acceleration, which obtains and analyses the data from large quantities of smart meters and effectively identify the corresponding relationship between transformers and meters, via high performance computing technology and large data methods. Data analysis is implemented by GPU parallel accelerated grey correlation analysis method, which effectively improves the efficiency of the method. Numerical experiments show that the method proposed in this paper has high accuracy and computational efficiency, which has the value and potential of engineering applications.

Risk analysis of debris flow based on grey correlation method

In this paper, the research status and evaluation methods of debris flow risk at home and abroad are analyzed. Finally used the grey correlation analysis method, according to the climate and geographical conditions of Jilin province has chosen six factor model (watershed cut density, loose source quantity per catchment area, vegetation coverage, main ditch slope, slope gradient, length of supply section), and determine each factor weight. Based on this, the risk level of six debris flow gullies in Longjing city was determined.

Data Feature Analysis of Non-Scanning Multi Target Millimeter-Wave Radar in Traffic Flow Detection Applications.

The millimeter-wave radar has been widely used in traffic applications. However, little research has been done to install the millimeter-wave radar on the top of a road for detecting road traffic flow at a downward looking direction. In this paper, the vehicle parameters, including the distance, angle and radar cross-section energy, are collected by practical experiments in the aforementioned application scenario. The data features are analyzed from the dimensions of single parameter sampling characteristics and multi-parameter relationships. Further, the correlations of different parameter series are given using the grey correlation analysis method. For millimeter-wave radar used in the traffic flow detection, our work can definitely provide significant support for further intelligent transportation applications, such as vehicle trajectory tracking, traffic flow estimation and traffic event identification.

Application of wavelet entropy and grey relational analysis in fault diagnosis of hydraulic system of engineering machinery

The working environment of engineering machinery is complex. The signal of the equipment in operation is characterized by non-stationary and complex variability. In this paper, the wavelet transform is used to extract the non-stationary fault signals of the hydraulic system of the equipment. At the same time, a fault classification method based on the multi wavelet entropy feature extraction is proposed with the information entropy. The fault features are extracted quickly and accurately. The grey correlation analysis method is used to identify the fault, and the remote fault is set up. Diagnosis platform. The results show that the method can improve the support and accuracy of the fault diagnosis, and provides a feasible new method for the fault diagnosis of the engineering machinery.