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.

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.

Core Competitiveness Evaluation of Financial Institution with Rough Sets and Gray Correlation Analysis

The comprehensive evaluation method of enterprise core competitiveness is proposed by combining rough sets and gray correlation theories. Firstly,the initial index is screened through rough set attribute reduction algorithm,and the evaluation weight of each index is obtained through the rough set theory. Then,based on the gray correlation theory, an evaluation model is built for empirical analysis. The 30 financial institutions on the Yangtze River Delta are examined from the theoretical and empirical perspective.The result demonstrates not only the feasibility of rough set attribute reduction algorithm in the core competitiveness index system of the financial institution,but also the accuracy of the combination of these two methods in the comprehensive evaluation of corporate core competitiveness.

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.

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.

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.

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.

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).

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.

Research on the Influencing Factors of Passenger Traffic at Sanya Airport Based on Gray Correlation Theory

Many factors have an effect on the passenger traffic of Sanya Airport.In this paper,seven factors that have a great influence on passenger demand,namely accommodation and catering turnover,number of overnight visitors received,total tourism revenue,average room opening rate of tourist hotels,flight movements,airport passengerflow and railway station passengerflow,are selected to conduct gray correlation analysis on these factors to provide a research basis for passengerflow prediction.

Dynamic Evaluation and Analysis of Regional Innovation Capability in Eastern China from the Perspective of High-quality Development

The economy of China has turned to the stage of high-quality development. In this sense,the connotation of regional innovation capacity should reflect more aspects, such as better economic effectiveness, people-centered philosophy of development and better living conditions. This study aims at establishing the evaluation index system of regional innovation capacity under high-quality perspective.Then the dynamic evaluation method based on gray correlation degree and TOPSIS is improved. And the improved method is applied to evaluate the regional innovation capacity under high-quality development perspective. The results show that: 1) The regional innovation capacity of Jiangsu, Zhejiang,Shanghai and Guangdong under high-quality development perspective is better than other regions,while the regional innovation capacity of Beijing-Tianjin-Hebei is imbalanced. Regional innovation capability of Fujian, Shandong, and Hainan from a high-quality perspective is at the middle and lower levels. 2) From the perspective of development trends, the gap of regional innovation capacity between Beijing, Jiangsu, Zhejiang, Shanghai, Guangdong and Fujian, Hebei, Shandong is gradually narrowing.3) An in-depth analysis of the regional innovation capability of the eastern provinces and cities from the perspective of high-quality development through different dimensions shows that Beijing, Guangdong, Jiangsu perform well in all dimensions, while Fujian and Hainan need to pay more attention to innovation input and the creation of a better innovation environment to enhance innovation output and promote innovation effectiveness. At last, based on above analysis, relevant policy recommendations are proposed.

Research on Comprehensive Evaluation of Financial Innovation Ability of the National-Level New Areas Based on Grey Correlation

On the basis of setting up an evaluation index system of financial innovation ability and using the grey systems theory and the coefficient variation method, the article has proposed a synthetic evaluation method with grey correlation. Through evaluating the ability of financial innovation of the national-level new areas comprehensively, the article has offered reliable suggestions to adjust regional economic structure and make financial policy.