Influences of lithofacies on fluid mobility in mixed sedimentary rocks:Insights from NMR analysis of the middle Permian Lucaogou Formation,Junggar Basin

The multi-source mixed sedimentation resulted in a unique series of mixed fine-grained sedimentary rocks evolved within the Permian Lucaogou Formation in the Jimusar Sag,located in the southeastern Junggar Basin,China.The variety of lithofacies within this series resulted in pronounced heterogeneity of pore structures,complicating the analysis of fluid occurrence space and state within reservoirs.As a result,the impact of lithofacies on fluid mobility remains ambiguous.In this study,we employed qualitative methods,such as field emission scanning electron microscopy(FE-SEM)and thin section observation,and quantitative analyses,including X-ray diffraction(XRD),total organic carbon(TOC),vitrinite reflectance(Ro),high-pressure mercury intrusion(HPMI)porosimetry,and nuclear magnetic resonance(NMR),along with linear and grey correlation analyses.This approach helped delineate the effective pore characteristics and principal factors influencing movable fluids in the fine-grained mixed rocks of the Lucaogou Formation in the Jimusar Sag,Junggar Basin.The findings indicate the development of three fundamental lithologies within the Lucaogou Formation:fine sandstone,siltstone,and mudstone.Siltstones exhibit the highest movable fluid saturation(MFS),followed by fine sandstones and mudstones sequentially.Fluid mobility is predominantly governed by the content of brittle minerals,the sorting coefficient(Sc),effective pore connectivity(EPC),and the fractal dimension(D_(2)).High content of brittle minerals favors the preservation of intergranular pores and the generation of microcracks,thus offering more occurrence space for movable fluids.A moderate Sc indicates the presence of larger connecting throats between pores,enhancing fluid mobility.Elevated EPC suggests more interconnected pore throat spaces,facilitating fluid movement.A higher D_(2)implies a more intricate effective pore structure,increasing the surface area of the rough pores and thereby impeding fluid mobility.Ultimately,this study developed a conceptual model that illustrates fluid distribution patterns across different reservoirs in the Lucaogou Formation,incorporating sedimentary contexts.This model also serves as a theoretical framework for assessing fluid mobility and devising engineering strategies for hydrocarbon exploitation in mixed fine-grained sedimentary rocks.

Grey Correlation Analysis of Physiological Traits Related to Drought Tolerance in Pennisetum sp.

The drought resistance of Pennisetum sp. was analyzed under different drought stress conditions simulated by various concentrations of PEG-6000. Changesofa series of indexes such as chlorophyll content, water content, relative electrical conductivity of osmotic solution, MDA content, proline content, soluble polysaccharide content and soluble protein content in the leaves were measured.The correlation of these indexes with the drought resistance of Pennisetum sp. was an- alyzed by the method of grey correlation analysis. The results showed that the chlorophyll, water content, relative electrical conductivity and soluble protein con- tentexhibited obvious negative correlation with the stress concentration, which de- creasedfollowing the increase of PEG-6000 concentration. The soluble polysaccha- ride contentshowed an increasing trend,the MDA content showed a rise at first fol- lowed by a declinetrend, while the prolinecontent was just opposite to MDA. The changes of the 3 indexes showed obvious positive correlation with thestress con- centration. The correlation of these indexes with the drought resistance of Pennise- tum sp. were ranked as follows： leaf water content （0.980 8）, chlorophyll content （0.967 9）, MDA content （0.876 0）, soluble polysaccharide content （0.839 5）, soluble protein content（0.827 5）, relative electrical conductivity of osmotic solution（0.670 8）, and proline content（0.571 3）.

Analysis of Driving Factors of Grain Output in Henan Province Based on Grey Correlation Model

Henan Province is an important grain production base, whose stable production is related to the economic development and social stability significantly. To summarize the primary factors of grain producing, we used grey correlation analysis method to analyze 10 correlative factors such as grain yield, grain yield per unit area, effective irrigated area, rural employed persons, grain planting area, consumption of chemical fertilizer in 25 years. The results showed order of synthetic degree of incidence: effective irrigated area>rural electricity consumption>consumption of chemical fertilizer>disaster crop area>grain yield per unit of area>total power of agricultural machinery>afflicted crop area>grain planting area>number of the rural employed persons. Finally, according to synthetic degree of incidence between influential factors and total grain output respectively, a series of measures and the suggestions was proposed for grain production in Henan Province, which will also provide the scientific basis and help for the government correct decision-making.

Effects of Nitrogen, Phosphate and Potassium Fertilizers on Soft Rot of Konjac Based on Grey Correlation Analysis

[Objective] The effects of different application amounts of nitrogen, phos-phate and potassium fertilizers on soft rot of konjac were investigated in this study. [Method] The grey correlation analysis was adopted to evaluate the correlation be-tween the application amount of nitrogen, phosphate and potassium fertilizers and the occurrence of soft rot of konjac. [Result] The excessive application of nitrogen fertilizer would induce the occurrence of soft rot of konjac, but the application of potassium fertilizer had a good control effect on soft rot. [Conclusion] The applica-tion amount of nitrogen fertilizer should be control ed reasonably in the planting of konjac, but the application amount of phosphate and potassium fertilizer could be in-creased to some extent, reducing the occurrence of soft rot of konjac.

The Grey Correlation Analysis on the Relationship between the Rural Finance and the Rural Economical Growth in Sichuan Province

This paper analyzes the relationship between rural finance and the rural economy of Sichuan Province from 1999 to 2009 by using the sequential growth rate of the gross value of farming, forestry, animal husbandry and fishery and the sequential growth rate of the per capital total income of rural households as the indicators of rural economic development; and taking the volume of deposit, volume of credit, volume of agricultural credit and the credit volume of township enterprises as the indicators of rural financial development; as well as the method of grey correlation analysis. The results show that there is an obvious positive correlation between them, and the development of country finance has the closest connection with the sequential growth rate of farming, forestry, animal husbandry, sideline production and fishery. The loan scale of township enterprises has the biggest influence on the increase of the rural economy. The countermeasures are put forward, covering optimizing investment structure; supporting the development of township enterprises; encouraging loan; actively lightening the financial difficulties in the process of developing rural economy; innovating and exploring; and promoting the diversified development of rural finance.

Grey analysis of the relationship between grain output and major input factor in Guizhou Province:1983-2005

Because conditions for the grain production are not favorable and the input in the production factors ofmodern agriculture is not sufficient, the grain supply has been less than the demand for a long time. By means of greycorrelation analysis, this paper deals with the correlation situation among such input factors as the grain sown area, thetotal power of agricultural machinery, the fertilizer utilization volume, the actual irrigation area, the damage area, thenumber of farming labor force, in order to understand the major restricting and driving forces that have affected thegrain output in the recent 23 years. The analysis shows that the grain sown area and fertilizer utilization volume are thetwo most important leading factors that affect grain production in Guizhou Province, while the damage area and the totalpower of the farming-used machines are the following factors. Fertilizer utilization volume and the actual agriculturalmachinery and irrigation area are the two increasingly influential factors that affect grain production. The influence of thefarming labor force upon grain production became less strong. The main measures to increase grain production outputin Guizhou Province are to stabilize the arable land, increase the actual irrigation area, expedite the transfer of thefarming labor force and increase the input of modern agriculture.

Application of Grey-correlated Spectral Region Selection in Analysis of Near-infrared Spectra

The optimal selection method of spectral region based on the grey correlation analysis was applied in the analysis of near-infrared（NIR） spectra. In order to compute ＂characteristic＂ spectral region, 160 samples of tobacco were surveyed by NIR. Next, the whole spectral region was randomly divided into six regions, and the values of association coefficients and correlation orders of different regions were computed for total sugar, reducing sugar and nicotine. Moreover, two regions that owned the largest value of association coefficient were regarded as ＂characteristic＂ spectral region of a model. Finally, the quantitative analysis models of different components were established via the partial least squares method, and the common selection methods of spectral region were compared. The simulation results indicate that the models to choose the spectral region based on grey correlation analysis are more effective than the common selection methods of spectral region, the optimized time of algorithm is shorter, the prediction precision of the models is higher and generalization ability for quantitative analysis results is stronger. This research can provide the support for the quantitative analysis models of NIR spectra and new idea for commercial analysis software of NIR. So, it has a high application value in the analysis of NIR spectra.

Analysis of Factors Influencing Comprehensive Productivity of Agriculture in Henan Province on the Basis of Grey Correlation

According to the data from Henan Statistical Yearbook from 2002 to 2008, from production capital, production conditions, labour inputs and financial support, this paper selects 11 variables influencing comprehensive productivity of agriculture in Henan Province. Through calculation and analysis of grey correlation of variables and comprehensive productivity of agriculture, this paper determines the impact of different variables on comprehensive productivity of agriculture. The results show that the agricultural capital has become the most important factor influencing comprehensive productivity of agriculture in Henan Province, while the impact of production conditions, labour inputs and financial support on comprehensive productivity of agriculture in Henan Province diminishes in turn. Corresponding countermeasures and suggestions are put forward to promote the sustainable development of comprehensive productivity of agriculture in Henan Province as follows: strengthen agricultural financial system building, and ensure agricultural production expenditure; scientifically arrange allocation of agricultural resources, and improve agricultural production conditions; carry out training of agricultural skills, and elevate the quality of agricultural labour forces; increase financial expenditure for agricultural production, and optimize financial expenditure structure.

Evaluation of Comprehensive Performance of Agronomic Traits of Anmai 1241 by Grey Correlation Analysis and Cluster Analysis Methods

The agronomic traits of the new wheat variety Anmai 1241 were comprehensively evaluated,in order to provide comprehensive and objective theoretical basis for further improvement and production utilization of this variety.The winter water production test results of Anmai 1241 in 14 pilot sites of Henan Seed Management Station from 2016 to 2017 were summarized.The comprehensive performance of 11 agronomic traits of Anmai 1241 in different tests sites in Henan Province was evaluated by the grey correlation analysis and clustering analysis methods.The results showed that among the observed values of 11 traits,the variation coefficient,correlation degree and weight of black embryo rate were 181.64%,0.6679 and 0.1051,respectively.The clustering analysis showed that the 11 traits could be divided into 3 groups.The first type of traits(yield,number of grains per ear and 1000-grain weight)and the third group of traits(percentage of earbearing tillers,number of productive tillers and volume weight)belonged to the yield factor traits,and the sum of their weights was 0.5242.Yield and its related factors played an important role in the variety evaluation of Anmai 1241,and the effect of black embryo on yield should be eliminated in variety improvement.

Regional Economic Vitality Based on Weighted Grey Relational Analysis

The future development of cities has a great relationship with economic vitality.To determine the size of the economic vitality and its main influencing factors.This article takes some cities in China as examples.First,determine the main factors.Aiming at many factors,this paper starts from the perspective of population changes in different cities and changes in corporate vitality.After applying the rough set theory to objectively evaluate index weights,the main factors are screened out.Then,the weights of the corresponding evaluation indexes of each group of cities are calculated by a multiple linear regression to a weighted index system,and then the cities are ranked using the gray correlation analysis method.Finally,we get the ranking of the economic vitality level of different cities.Finally,suggestions are made based on the weighting factors of major factors and economic vitality.

A Diagnosis Method of Vibration Fault of a Steam Turbine Based on Information Entropy and Grey Correlation Analysis

The vibration fault, one of the common faults in the steam turbine generator unit, brings great damage to the production and the running process. It is well known that the information entropy is to describe the degree of indeterminacy of the system, so the information entropy can be used to measure Despite its efficiency, one kind of information entropy is just enabled to identify make up for this limitation, based on nalysis was studied for vibration fault the vibration condition of the unit. certain part of the faults. In order to the faulty signals collected from the rotor test platform, the grey correlation adiagnosis of steam turbine shafting in this paper. The reference faulty matrix and the calculation model of grey correlation degree was established based on three kinds of information entropy. The analysis shows that grey correlation analysis is a useful method for fault diagnosis of shafting and can be used as a quantitative index for fault diagnosis.

The Establishment of Mathematical Models for the Composition Analysis and Identification of Ancient Glass Products

Glass is the precious material evidence of the trade of the early Silk Road. The ancient glass was easily affected by the environmental impact and weathering, and the change of composition ratios affected the correct judgment of its category. In this paper, mathematical models and methods such as Chi-square test, weighted average method, principal component analysis, cluster analysis, binary classification model and grey correlation analysis were used comprehensively to analyze the data of sample glass products combined with their categories. The results showed that the weathered high-potassium glass could be divided into 12, 9, 10 and 27, 7, 22 and so on.

Comprehensive Evaluation Method for Traffic Flow Data Quality Based on Grey Correlation Analysis and Particle Swarm Optimization

Nowadays,data are more and more used for intelligent modeling and prediction,and the comprehensive evaluation of data quality is getting more and more attention as a necessary means to measure whether the data are usable or not.However,the comprehensive evaluation method of data quality mostly contains the subjective factors of the evaluator,so how to comprehensively and objectively evaluate the data has become a bottleneck that needs to be solved in the research of comprehensive evaluation method.In order to evaluate the data more comprehensively,objectively and differentially,a novel comprehensive evaluation method based on particle swarm optimization(PSO)and grey correlation analysis(GCA)is presented in this paper.At first,an improved GCA evaluation model based on the technique for order preference by similarity to an ideal solution(TOPSIS)is proposed.Then,an objective function model of maximum difference of the comprehensive evaluation values is built,and the PSO algorithm is used to optimize the weights of the improved GCA evaluation model based on the objective function model.Finally,the performance of the proposed method is investigated through parameter analysis.A performance comparison of traffic flow data is carried out,and the simulation results show that the maximum average difference between the evaluation results and its mean value(MDR)of the proposed comprehensive evaluation method is 33.24%higher than that of TOPSIS-GCA,and 6.86%higher than that of GCA.The proposed method has better differentiation than other methods,which means that it objectively and comprehensively evaluates the data from both the relevance and differentiation of the data,and the results more effectively reflect the differences in data quality,which will provide more effective data support for intelligent modeling,prediction and other applications.

Evaluation and Influencing Factors on Particle Agglomeration in RAP

Asphalt extraction test and scanning electron microscopy(SEM) were used for analysis of agglomerations of reclaimed asphalt pavement(RAP) particles. In order to quantify the agglomeration degree of RAP, the fineness modulus ratio(FMR) and the percentage loss index(PLI) were proposed. In addition, grey correlation analysis was conducted to discuss the relationship between particle agglomerations and RAP size,asphalt content(AC), and surface area. Two indexes indicate that the agglomeration degree increases in general as the RAP size reduces. This can be attributed to that particles are prone to agglomeration in the case of higher AC. Based on the SEM images and the material composition of RAP, the particle agglomeration in RAP can be classified into weak agglomeration and strong agglomeration. Grey correlation analysis shows that AC is the crucial factor affecting the agglomeration degree and RAP variability. In order to produce consistent and stable reclaimed mixtures, disposal measures of RAP are suggested to lower the AC of RAP.

Spatiotemporal evolution and influencing factors of urban resilience in the Yellow River Basin,China

The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment.Industrialization and urbanization promote social-economic development,but they also have generated a series of environmental and ecological issues in this basin.Previous researches have evaluated urban resilience at the national,regional,urban agglomeration,city,and prefecture levels,but not at the watershed level.To address this research gap and elevate the Yellow River Basin’s urban resilience level,we constructed an urban resilience evaluation index system from five dimensions:industrial resilience,social resilience,environmental resilience,technological resilience,and organizational resilience.The entropy weight method was used to comprehensively evaluate urban resilience in the Yellow River Basin.The exploratory spatial data analysis method was employed to study the spatiotemporal differences in urban resilience in the Yellow River Basin in 2010,2015,and 2020.Furthermore,the grey correlation analysis method was utilized to explore the influencing factors of these differences.The results of this study are as follows:(1)the overall level of urban resilience in the Yellow River Basin was relatively low but showed an increasing trend during 2010–2015,and significant spatial distribution differences were observed,with a higher resilience level in the eastern region and a low-medium resilience level in the western region;(2)the differences in urban resilience were noticeable,with industrial resilience and social resilience being relatively highly developed,whereas organizational resilience and environmental resilience were relatively weak;and(3)the correlation ranking of resilience influencing factors was as follows:science and technology level>administrative power>openness>market forces.This research can provide a basis for improving the resilience level of cities in the Yellow River Basin and contribute to the high-quality development of the region.

Average Incremental Correlation Analysis Model and Its Application in Fault Diagnosis

The concept of average incremental correlation degree is put forward.It has been proved that the average incremental correlation model has such properties as parallelism,consistency,affine,affine transformation isotonicity and interference factors independence,and it will not lead to changes of the sequence order relation because of the data transformation.Therefore,the new model keeps good stability.Finally,the incremental average correlation model is applied to failure model analysis of equipment,and an ideal diagnostic effect is obtained.

Employment Quality EvaluationModel Based on Hybrid Intelligent Algorithm

In order to solve the defect of large error in current employment quality evaluation,an employment quality evaluation model based on grey correlation degree method and fuzzy C-means(FCM)is proposed.Firstly,it analyzes the related research work of employment quality evaluation,establishes the employment quality evaluation index system,collects the index data,and normalizes the index data;Then,the weight value of employment quality evaluation index is determined by Grey relational analysis method,and some unimportant indexes are removed;Finally,the employment quality evaluation model is established by using fuzzy cluster analysis algorithm,and compared with other employment quality evaluation models.The test results show that the employment quality evaluation accuracy of the design model exceeds 93%,the employment quality evaluation error can meet the requirements of practical application,and the employment quality evaluation effect is much better than the comparison model.The comparison test verifies the superiority of the model.

The Study on Industrial Structure Adjustment of Farmer Economic Net Income Doubled in Mountain Area

The aim was to study the main industry effect the double of the per capi- ta net income of farmers economic. The relation between six industry net income per capita income of farmers including grain, animal husbandry, flue-cured tobacco, walnut, long-term labor expot, seasonal labor export and the net income of farmers per capita in the Wazitian Village of Baoshan, Yunnan was studied by means of the effect main industry doubled net income of farmers per capita economic and the grey correlation analysis. The correlation degree of six industry and the net income of farmers per capita economic was long-term labor export〉seasonal labor export〉 walnut〉grain〉animal husbandry〉flue-cured tobacco. The pillar industry affecting the net income of farmers per capita economic was long-term labor export, seasonal la- bor export and walnut. The study provided the scionce theoretical basis and method of support for net income per capita economic multiplier of farmers in Baoshan, Yunnan province and even a similar low latitude mountain plateau.

Variation Character of Grain Yield per Unit Area in Main Grain-producing Area of Northeast China

Based on the surveys and the statistic data during 1980-2003, the variation character of grain yield per unit area in Northeast China and its main factors have been discussed by the methods of statistics and grey correlation analysis. The results show that: 1) the grain yield per unit area has been taking on an increasing trend in the recent 20 years. It increased from 2519.80kg/ha in 1980 to 4216.11kg/ha in 2003, with an increasing rate of 67.32%; 2) the variation of grain yield per unit area is considerably prominent and its range is also very great, with the maximal increase rate of 42.59% and maximal decrease rate of 21.13%, respectively, which are far above the whole Chinese average level; 3) the variation of main crops' yield per unit area is remarkable, which takes on the character that the yield of corn is much higher than that of soybean and rice; and 4) the grey correlation analysis shows that the most important factors impacting the variation of grain yield per unit area are the total power of agricultural machinery, the consumption of chemical fertilizer and effective irrigated area. However, the influence of natural disaster and income level should not be ignored. Effective ways to improve grain yield per unit area are to construct farmland improvement groundwork, reclaim the middle- and low-yield farmland, etc.

Relationship of Remote Sensing Normalized Differential Vegetation Index to Anopheles Density and Malaria Incidence Rate

Objective To study the relationship of remote sensing normalized differential vegetation index （NDVI） to Anopheles density and malaria incidence rate. Methods Data of monthly average climate, environment, Anopheles density and malaria incidence rate, and remote sensing NDVI were collected from 27 townships of 10 counties in southeastern Yunnan Province from 1984 to 1993. The relationship of remote sensing ecological proxy index, NDVI, to Anopheles density and malaria incidence rate was studied by principal component analysis, factor analysis and grey correlation analysis. Results The correlation matrix showed that NDVI highly correlated with Anopheles density in 4 townships of Mengla, Jinghong, and Yuanjiang counties, but in other 23 townships the relationship was not clear. Principal component and factor analyses showed that remote sensing NDVI was the representative index of the first principal component and the first common factor of Anopheles density evaluation. Grey correlation analysis showed that in rainy season NDVI had a high grey correlation with Anopheles density and malaria incidence rate. The grey correlation analysis showed that in rainy season the grey degree of NDVI correlated with Anopheles. Minimus density was 0.730, and 0.713 with Anopheles sinensis density, and 0.800 with malarial incidence rate. Conclusion Remote sensing NDVI can serve as a sensitive evaluation index of Anopheles density and malaria incidence rate.