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.

Deformation mechanism of high-stress and broken-expansion surrounding rock and supporting optimization based on the gray correlation theory

Aiming at the large deformation and support problems of high-stress and broken-expansion surrounding rock, and taking 1 000 m level roadway of Mine II in Jinchuan as the research object, an investigation on the deformation and damage of roadway surrounding rock and an analysis of its mechanism were carried out. The gray correlation theory was used in support scheme optimization design. First, causes and mechanism of deformation of the 1 000 m horizontal transport channel were analyzed through field investigation, laboratory test and data processing methods. We arguued that poor engineering geological conditions and deep pressure increases were the main factors, and the deformation mechanism was mainly the ground deformation pressure. Second, the gray correlation theory was used to construct supporting optimization decision method in the deep roadway. This method more comprehensively considers various factors, including construction, costs, and supporting material functions. The combined support with pre-stressed anchor cables, shotcrete layer, bolt and metal net was put forward according to the actual roadway engineering characteristics. Finally, 4 support schemes were put forward for new roadways. The gray relational theory was applied to optimizing the supporting method, undertaking technical and economic comparison to obtain the correlation degree, and accordingly the schemes were evaluated. It was concluded as follows： the best was the flexible retaining scheme using the steel strand anchor; the second best was the one using plate anchors on the top and rigid common screw steel bolt on the two sides; the ttiird was; the rigid common screw steel bolt in full section of roadway; and the worst is the planished steel rigid support. The optimized scheme was applied to the 1000 m level of new excavation roadway. The results show that the roadway surrounding rock can reach a stable state after 5 to 6 months monitoring, with a convergence rate less than 1 mm/d.

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.

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

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

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.

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

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

Nutrients Determination in Nuts from Different Torreya grandis Cultivars

[Objectives]This study aimed to investigate the differences in nutritional properties of nuts from different Torreya grandis cultivars.[Methods]Seven T.grandis cultivars were selected to analyze the protein,soluble carbohydrate,vitamin E,amino acids and fatty acid composition,and evaluate nutritional value of T.grandis nuts from different cultivars using gray correlation analysis.[Results]The kernels of T.grandis contained 9.47%-13.3% protein,1.92%-2.36% soluble carbohydrate,0.16-0.22 mg/g vitamin E,8.40%-11.55% amino acids,and 42.09%-49.29% fatty acid including 35.14%-40.14% oleic acid.And the coefficient of variation ranged from 5.02% to 18.9% among different cultivars.Meanwhile,the average contents of essential amino acids(E),nonessential amino acids(N)and children essential amino acids(C)were 3.88%,6.07% and 0.99%,respectively.The ratios of E/T and E/N were quite stable and in fully compliance with the recommendation standards of amino acids composition from WHO/FAO.[Conclusions]Overall,the nutritional value of tested seven cultivars could be ranked in the following decreasing order using gray correlation analysis:T.grandis cv.Dong No.2>T.grandis cv.Longfeng>T.grandis cv.Dingshan>T.grandis cv.Merrilli>T.grandis cv.Dong No.3>T.grandis cv.Dong No.1>T.grandis cv.Zhuyan.

A matching algorithm based on hybrid matrices consisting of reference differences and disparities

Unique correct correspondence cannot be obtained only by use of gray correlation technique, which describes gray similar degree of feature points between the left and right images too unilaterally. The gray correlation technique is adopted to extract gray correlation peaks as a coarse matching set called multi-peak set. The disparity gradient limited constraint is utilized to optimize the multi-peak set. Unique match will be obtained by calculating the correlation of hybrid matrices consisting of reference differences and disparities from the multi-peak set. Two of the known corresponding points in the left and right images, respectively, are set as a pair of reference points to determine search direction and search scope at first. After the unique correspondence is obtained by calculating the correlation of the hybrid matrices from the multi-peak set, the obtained match is regarded as a new reference point till all feature points in the left (or right) image have been processed. Experimental results proved that the proposed algorithm was feasible and accurate.

A Hybrid Model for the Mid-Long Term Runoff Forecasting by Evolutionary Computation Techniques

The mid-long term hydrology forecasting is one of most challenging problems in hydrological studies. This paper proposes an efficient dynamical system prediction model using evolutionary computation techniques. The new model overcomes some disadvantages of conventional hydrology forecasting ones. The observed data is divided into two parts; the slow 'smooth and steady' data, and the fast 'coarse and fluctuation' data. Under the divide and conquer strategy, the behavior of smooth data is modeled by ordinary differential equations based on evolutionary modeling, and that of the coarse data is modeled using gray correlative forecasting method. Our model is verified on the test data of the mid-long term hydrology forecast in the northeast region of China. The experimental results show that the model is superior to gray system prediction model (GSPM).

Industrial Carbon Emissions Status and Analysis Based on Energy Consumption

With frequent disastrous weathers and increasingly prominent GHG effects in recent years, normal existence and development of mankind are facing unprecedented threats and challenges. GHG emissions mitigation for the global climate changes has been the focus of concern of the world. As the biggest developing country and the second largest country of carbon-emission, China attaches importance to the carbon emission reduction. The major GHG component is carbon dioxide and in China, the emis- sion of carbon dioxide is mainly from industrial production. In the paper, the status and trend of Coz emission from industrial departments, high-carbon emission and its specific industries are shown in statistics. Meanwhile, the policy environment, industrial organization structure and technology of carbon high emission are all discussed based on practical situations in these departments and industries. At the end, through the analysis of gray correlation, correlativity is explored for both fossil energy consumption and total carbon emission, and also for the production value and carbon emission of each industrial sector. Some policy proposals for the establishment of low-carbon industries and transition of economic development pattern are set forth.

GRADIENT OF REFERENCE DIFFERENCE BASED MATCHING ALGORITHM FOR IMAGE FEATURE POINT

During matching on feature point, gray correlation matching technology is utilized to extract multi-peaks as a coarse matching set. A pair of given corresponding reference points within the left and right images is used to calculate gradients of reference difference between the reference points and each feature point within the multi-peaks set. The unique correspondence is determined by criterion of minimal gradients of reference difference. The obtained correspondence is taken as a new pair of reference points to update the reference points continuously until all feature points in the left (or right) image being matched with the right (or left) image. The gradients of reference difference can be calculated easily by means of pre-setting a pair of obvious feature points in the left and right images as a pair of corresponding reference points. Besides, the efficiency of matching can be improved greatly by taking the obtained matching point as a new pair of reference points, and by updating the reference point continuously. It is proved that the proposed algorithm is valid and reliable by 3D reconstruction on two pairs of actual natural images with abundant and weak texture, respectively.

Impact of demographic dynamics on CO_2 emissions in Sichuan,China

Global climate change is one of the major environmental issues faced by humans.Existing evidence indicates that the anthropogenic push for a rise in the atmospheric concentration of greenhouse gases(GHGs)(particularly CO_2) has been a primary cause for global warming.Aside from economic and teclinological factors,demographic dynamics(including human consumption in a broad demographic sense) has been a major driver for CO_2 emissions.In this paper,we performed both nonlinear regression analysis(based on the STIRPAT model) and gray correlation degree analysis(based on gray system theory) on the impact of demographic dynamics on CO_2 emissions.Our results reveal that CO_2 emissions are positively correlated with population size and GDP per capita and negatively correlated with energy intensity.We also show that gray con-elation degree with CO_2 emissions for five variables(i.e.,household consumption,urbanization rate,household size,population aging rate,population size) varies substantially:household consumption > urbanization rate >household size > population aging rate > population size,with household consumption being the highest,and population size the lowest.To mitigate the impact of demographic dynamics on CO_2 emissions,it is of vital significance to nurture people's awareness of sustainable consumption and to adhere to current population control policies.

Effects of Environmental Resources on Industrial Agglomeration

Firstly,agriculture,industry and tourism in the Yangtze River Delta,Pearl River Delta and Bohai Economic Rim were chosen to represent the primary,secondary and tertiary industries respectively,and industrial agglomeration in the three economic zones was analyzed using location quotient coefficient method.Afterwards,the critical factors influencing industrial agglomeration were discussed using gray correlation analysis.The results showed that industrial agglomeration of agriculture,industry and tourism formed gradually in the three economic zones,and the critical factors influencing industrial agglomeration were human capital,science and technology progress,and natural resources.Meanwhile,environmental pollution affected and restricted the development of industrial agglomeration.

Research and Application of Rainstorm Disaster Risk Assessment along the Middle and Lower Reaches of Yangtze River

We explored and studied rainstorm disaster impact grade. Firstly,we selected average precipitation,precipitation intensity,coverage and duration during rainstorm process,and economic losses,the number of deaths and total casualties in rainstorm disaster situation as the pre-assessment indexes of rainstorm process impact grade along the middle and lower reaches of Yangtze River. Then,normalized and dimensionless processing of each index was conducted. By using gray correlation method,we established rainstorm process grade and rainstorm disaster impact grade. At last,we conducted regression analysis of relevancy degree between rainstorm process grade and rainstorm disaster situation grade,and established a linear relationship between the two,thereby getting a rainstorm disaster pre-assessment method. On this basis,using rainstorm hazard factors in independent sample,we carried out pre-assessment test of disaster impact grade. The results show that this pre-assessment method is quick and easy,and the effect is better.