Absolute Correlation Degree Research Articles

Spatiotemporal variability and driving factors of the shallow soil moisture in North China during the past 31 years

To fully understand the dynamic change characteristics of soil moisture in North China, the spatiotemporal patterns of soil moisture anomalies (SMA) in the four active soil layers from January 1990 to December 2020 are analyzed based on the Global Land Data Assimilation System (GLDAS) model, then the driving factors and corresponding contribution rates (CRs) for SMA change are determined together with the meteorological, socioeconomic and land cover data. The results show that the SMA in the last three layers present decreasing trends, and the trend magnitudes increase in multiples with the increase of soil depth. The area with the most severe soil dry is clustered in the east-central plain, while the relatively wet areas are scattered in western Shanxi and northern Hebei. The annual, intra- and inter-annual cycles (1.0, 0.5, 4.3 and 7.3 yr) are the dominant frequency of the SMA time series, which are driven jointly by 6 natural-type factors and 6 human-type factors, especially the intensified evaporation and dramatically expanding urbanization. By combining principal component analysis (PCA) and grey absolute correlation degree, the reintegrated human and natural factors respectively account for 49.46% and 50.54% of mean CRs to SMA in the four layers, but the human factor dominates the change of the bottom SMA. On the other hand, the determined mean CRs by combining exploratory factor analysis (EFA) and grey absolute correlation degree are 53.46% and 46.44% for reintegrated positive and negative factors, but the negative factor has a greater effect on the bottom SMA. The results provide a clear clarification of the soil moisture dynamic change, which is conducive to shedding new light on water resources management, agricultural security and ecological sustainability.

Study of the Durability Damage of Ultrahigh Toughness Fiber Concrete Based on Grayscale Prediction and the Weibull Model

The purpose of this research is to investigate the durability damage law for ultrahigh toughness cementitious composites (UHTCCs) under freeze–thaw environments and impact resistance. In this study, UHTCCs with fiber length-to-diameter ratios of 5/30, 8/30, 12/20, 12/30 and 12/48 were tested for impact resistance and freeze–thaw cycles. The freeze–thaw cycle process and impact resistance process for UHTCC are comprehensively analyzed and evaluated in terms of mass loss, compressive strength loss, relative dynamic elastic modulus loss and impact resistance number. The freeze–thaw damage prediction model for the relative dynamic elastic modulus of the UHTCC is established based on the regularity of the measured data for the relative dynamic elastic modulus of UHTCC and also on the GM(1,1) power model. The accuracy and reliability of the GM(1,1) power model is analyzed using the relative error, absolute correlation degree, mean variance and probability of small errors. According to the evolution law of the impact resistance number of the UHTCC, the impact damage prediction model for UHTCC is established based on the Weibull distribution model, and the accuracy of the model is analyzed by using the decision coefficient R2. The results show that UHTCC has high durability performance, and the durability performance of UHTCC at a length-diameter ratio of 12/48 is optimal. The freeze–thaw damage evolution model and impact damage evolution model established in this research are sufficiently realistic, the average relative error of the GM(1,1) power model is less than 5%, and the coefficient of determination R2 of the Weibull distribution model is greater than 0.93, which effectively reflects the damage development process for concrete under freeze–thaw and impact environment with high fitting accuracy.

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 <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{MGM}(1,m \vert \tau,\gamma)$</tex> 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.

Prediction Method of Asphalt Pavement Performance and Corrosion Based on Grey System Theory

The Grey system theory is a new mathematical method to predict data changes in the poor data integrity. As a branch of Grey system theory, the GM (1, 1) model is widely used because only small sample data and simple calculations are needed in prediction of engineering project. It is a critical problem to effectively predict the performance and corrosion of asphalt pavement of highway construction due to the inadequacy of highway performance monitoring data. The smoothness, rut, and pavement skid resistance are three important indexes to evaluate the performance and corrosion of asphalt pavement. This paper has established the prediction model and derived prediction equation of asphalt pavement performance according to the GM (1, 1) model method and then listed the calculation equation of residual and the gray absolute correlation degree. Based on the experience of constructed Dalian-Guangzhou expressway in China, the vectors “a” and “b” in the prediction equation of smoothness, rut, and pavement skid resistance have been calculated by using the original monitoring data. The field monitoring data are compared with the predictive data for residual and the gray absolute correlation. The results reveal that the predicted data of the smoothness, rut, and skid resistance are mostly consistent with the monitoring data, the biggest residual of the above three indexes is smaller than 8.09%, and the gray absolute correlation degrees all exceed 0.9, which means the accuracy of the predicted equation is excellent. The calculation method based on GM (1, 1) model can effectively predict the changing performance index of asphalt pavement.

Research on quality evaluation and forecast control in assembly process for complex products

Assembly quality affects complex product’s performance in high degree because the assembly is the end of manufacture process. In this paper, a comprehensive evaluation and forecast control of various factors affecting assembly failure is presented based on theory of gray system. Firstly, the absolute correlation degree and relative degree of correlation are calculated by using data from assembly process of complex products. Then, the comprehensive correlation degree and rank analysis are obtained with the gray method. Finally, the gray system theory is used in quality analysis and forecast control of a valve manufacturer. The final result indicates that excess amount of leakage is the main factor affecting product quality in accord with the actual situation.

The empirical study of executive compensation in China port and shipping listed companies based on the grey relational analysis

Purpose – The purpose of this paper is to find the key influence factors of executive compensation within China ports and listed shipping companies and provide some reasonable suggestions. Eventually, help to perfect the executive compensation evaluation mechanism against the background of new area. Design/methodology/approach – Grey correlation analysis is an important part of grey system theory. Professor Liu Sifeng further studies the relationship between two sequences absolute increment on the basis of Deng’s degree and put forward the “Grey absolute correlation degree,” which is widely used in practice. In the study, on the basis of the area of the line between sequences size, it measures the correlation degrees of firm performance, executive stock holding, continuous growth capacity and other relevant factors of executive payment in China ports and listed shipping companies. Findings – The paper concludes that the main factors influence CEO salary in China ports and listed shipping companies are return on equity and growth rate of fixed assets. However, the authors consider the frequent occurrence of executives’ corruption in China listed state-owned enterprise under the environment of financial and economic crisis, the authors argue that the significant influence of net assets attributed to shareholders cannot be ignored. In addition, cash flow in operating activities and executive stock holding both have relatively important effect on executive compensation. Research limitations/implications – This paper still has some limitations. First, it merely takes into account the financial indicators and ignores the influence of non-financial indicators to the performance evaluation of listed companies, such as: innovation ability, human capital and goodwill. Second, it has not considered the power consumption and other types of “invisible income” in the executive compensation structure, neither the influence of investing and financing activities on corporate performance. Consequently, these are likely to cause a certain deviation to the results of the study. Practical implications – The outcome obtained in this paper can be provided for China ports and listed shipping companies to establish a reasonable executive compensation evaluation and incentive mechanism under the background of depressed shipping market. Social implications – This paper intends to use correlation analysis between firm performance, executive stock holding, sustainability and executive compensation in the new area of time, tries to make a greater contribution to the major component of salary policy and then make some suggestions on incentive supervising and restraining mechanisms for the ports and listed shipping firms in China. Originality/value – Although scholars have done many studies about the association analysis of executive compensation and firm performance, they neglect the economic environment of industry. Meanwhile, considering the non-financial indicators and incomplete information, this paper studies the grey correlation analysis of executive compensation and influence factors in China ports and listed shipping firms under the background of the Chinese flagging shipping industry.

P Taylor Series Expansion Vibratory Source Localization Algorithm Based on the Gross Error Gray Judgment

The complex environment and high frequency interference lead to the poor consistency of vibration measurement and even appear the gross error, the emergence probability of gross time delay error shocks and it can seriously affect the target localization result. In order to solve this problem, this paper puts forward the positioning search algorithm based on the gross time delay error grey discrimination and Taylor series expansion. Firstly, this algorithm confirms the credible degree of each sensor according to the Signal-noise-ratio (SNR) of signals and gray absolute correlation degree, and then it chooses three sensors with high credible degree to locate the position and estimate the initial value of the source coordinates. Time delay difference is calculated for each sensor on the basis of the initial value of the source coordinates and it is made difference with the measurement time delay difference, obtain the time delay error sequence of multiple sensor. Then the gross error gray discriminate rule is used to estimate and eliminate the gross time delay error. Finally, the Taylor series iteration searching method is used to determine the vibratory source location. Experimental results show that this method can effectively improve the search speed positioning precision and anti-interference ability of the vibration source.

Control of Production Cost Based on Grey Correlation Degree in Wulongquan Mine

In order to solve the problems such as low production capacity, high production costs and insufficient resources utilization in Wulongquan mine, the method of grey correlation analysis has been adopted to analyze the main affecting factors about mine production cost. Considering the changes and tendency of these time sequences, grey absolute correlation degree has been used to reflect the strong-weak degrees and orders of the relationship between reference sequence and comparison sequences better based on non-dimensional values. According to the calculating results, labor cost, depreciation cost and materials cost is main factors. So some appropriate measures have been put forward to control total cost.

Using grey relational analysis to evaluate resource configuration and service ability for hospital on public private partnership model in China

Purpose – The purpose of this paper is to evaluate resource configuration and service ability in hospital on public private partnership (PPP) model (Chaonan Minsheng Hospital of Guangdong Province), supplying decision-making reference for participants of hospital on PPP model. Design/methodology/approach – Four model of grey relational analysis (GRA) (Deng's correlation degree, grey absolute correlation degree, grey relative correlation degree and grey comprehensive correlation degree) are applied to evaluate resource configuration and service ability, a total of 11 indicators of hospital on PPP model public hospital and private hospital from 2007 to 2011. Findings – The paper finds that different GRA models have different results when the paper applied them to evaluate resource configuration and service ability in hospital on PPP model. More than 60 per cent indicators of resource configuration (total six indicators) and service ability (total six indicators) are assessed as “hospital on PPP model ≻ public hospital” or “hospital on PPP model≻ private hospital” from three models of Deng's correlation degree, grey absolute correlation degree and grey comprehensive correlation degree. Practical implications – Evaluation of resource configuration and service ability for hospital on PPP model with GRA makes results quantified objective and provides reference for decision making and management. GRA makes the comparison of resource configuration and service ability between hospital on PPP model and other model hospitals becoming possible. Originality/value – The shortcoming for data analysis method of “large sample” is overcome and data analysis method of “small sample” is realized by using GRA, which broaden the method of evaluating hospital on PPP model.

Module Matching Method Based on the Gray Theory

The matching method is used to select the most similar modular design scheme from the history product database. The existed methods are not efficient enough. A new matching method based on the gray theory was presented. The absolute correlation degree and the relative correlation degree between the target modular product and the history product were calculated respectively, and finally the comprehensive correlative degree was gotten, the most similar historical product was matched. In the end, the approach is illustrated with a hydraulic turbine case.

A Model of Weight Absolute Grey Correlation Degree for the Transformer Bushing State Assessment

Accurate assessment for the operational status of the transformer bushing is not only a prerequisite for the implementation of condition-based maintenance, but also to ensure the normal operation of the transformer and the whole power equipment conditions. In the paper, a model of weight absolute grey correlation degree was used to assess the transformer bushing state. Firstly, determined the assessment indicators and handled them. Secondly, the weights, correlation coefficients and each association were calculated. Thirdly, to compare the largest association of assessment indicators in grades as the transformer bushing final run state. Finally, give the state assessment results, according to the remark set. The result shows the model works well.

Analysis of Interwell Communication by Rate Correlation Degree Method

In the process of oilfield development, understanding of interwell communication and judging directions of water drive and breakthrough are the premise of formulating development plans and adjusting producing measures. Rate correlation degree analysis method of grey theory is applied to calculate the rate correlation degree between water injection and water/oil production, and to quantitatively describe interwell communication. This method, avoiding the tedious work of researching interwell communication through sedimentary microfacies and numerical simulation methods, overcomes the shortcoming of being affected by extremum as in absolute correlation degree analysis method. Applications indicate that rate correlation degree analysis method is practicable

Fusion and classification of Beijing-1 small satellite remote sensing image for land cover monitoring in mining area

In order to promote the application of Beijing-1 small satellite (BJ-1) remote sensing data, the multispectral and panchromatic images captured by BJ-1 were used for land cover classification in Pangzhuang Coal Mining. An improved Intensity-Hue-Saturation (IHS) fusion algorithm is proposed to fuse panchromatic and multispectral images, in which intensity component and panchromatic image are combined using the weights determined by edge pixels in the panchromatic image identified by grey absolute correlation degree. This improved IHS fusion algorithm outperforms traditional IHS fusion method to a certain extent, evidenced by its ability in preserving spectral information and enhancing spatial details. Dempster-Shafer (D-S) evidence theory was adopted to combine the outputs of three member classifiers to generate the final classification map with higher accuracy than that by any individual classifier. Based on this study, we conclude that Beijing-1 small satellite remote sensing images are useful to monitor and analyze land cover change and ecological environment degradation in mining areas, and the proposed fusion algorithms at data and decision levels can integrate the advantages of multi-resolution images and multiple classifiers, improve the overall accuracy and produce a more reliable land cover map.