Comprehensive Weighting Method Research Articles

Proposal of a comprehensive risk assessment model for cut slope considering long-term deterioration characteristics based on the concept of disaster immunity

In Japan, the stability of cut slopes alongside expressways has deteriorated over time due to factors such as weathering, rendering them susceptible to significant collapses, especially during heavy rainfall. This study presents an evaluation model to assess the stability of cut slopes, with the aim of capturing their long-term deterioration characteristics using the logistic regression method. Additionally, to explore variations in deterioration patterns among cut slopes in diverse regions with varying geological compositions, a hierarchical Bayesian model is utilized to estimate parameters in the logistic regression model. This methodology enables the creation of a novel stability probability evaluation model for cut slopes that is adaptable to regions with different geological structures. Moreover, to comprehensively evaluate changes in the disaster resistance capabilities of extensively used cut slopes, the post-disaster recovery capabilities in the slope region are assessed through a comprehensive weighted evaluation method (EWM-TOPSIS). Building on this assessment, a novel, simplified, and more generalized resilience evaluation method is proposed. By integrating stability probability and resilience, an evaluation metric named "disaster immunity" is introduced to measure alterations in the disaster risk resistance of extensively utilized cut slopes. A case study is presented to illustrate the application of the evaluation model on selected cut slopes from various regions. This evaluation framework can assist road managers in predicting the disaster risk status of extensively used cut slopes and identifying priority slopes for implementing preventive measures to mitigate potential losses in the event of slope disasters.

Prediction and Verification of Groundwater Potential in Qingyang Area Based on Reliability Test, Validity Test and ROC Curve Method

The combination of remote sensing and GIS has become a common method to locate groundwater potential. Selecting reasonable and effective evaluation factors has become the most important thing in groundwater potential prediction. In this paper, reliability test and validity test are used to evaluate the rationality and validity of evaluation factors. The weight is determined by comprehensive weight method, and the groundwater potential map is obtained by visualization processing based on GIS.

Rock Burst Intensity-Grade Prediction Based on Comprehensive Weighting Method and Bayesian Optimization Algorithm–Improved-Support Vector Machine Model

In order to accurately judge the tendency of rock burst disaster and effectively guide the prevention and control of rock burst disaster, a rock burst intensity-grade prediction model based on the comprehensive weighting of prediction indicators and Bayesian optimization algorithm–improved-support vector machine (BOA-SVM) is proposed for the first time. According to the main factors affecting the occurrence and intensity of rock burst, the rock stress coefficient (σθ/σc), brittleness coefficient (σc/σt) and elastic energy index (Wet) are selected to construct the rock burst prediction indicator system. On the basis of the research of other scholars, according to the main performance and characteristics of rock burst, rock burst is divided into four intensity levels. The collected and sorted 120 sets of rock burst case data at home and abroad are taken as learning samples, and the T-SNE algorithm is used to perform dimensionality-reduction visualization processing on the sample data, visually display the distribution of samples of different grades, evaluate the representativeness of the sample data and prejudge the feasibility of the machine learning algorithm to distinguish different rock burst intensity levels. The combined improved analytic hierarchy process (IAHP) and Delphi method determine the subjective weight of the indicators; the combined entropy weight method and CRITIC method determine the objective weight of the indicator, and use the harmonic mean criterion of information theory to synthesize the subjective weight and objective weight of the indicator to obtain the comprehensive weight of the indicators. After weighted prediction indicators, a rock burst intensity-grade prediction model is constructed based on the support vector machine, and the hyperparameters of three types of support vector machines are improved by using the Bayesian optimization algorithm. Then, the prediction accuracy of different models is calculated by the random cross-validation method, and the feasibility and effectiveness of the rock burst intensity-grade prediction model is verified. In order to evaluate the generalization and engineering applicability of the proposed model, 20 groups of rock burst case data from the Maluping mine and Daxiangling tunnel are introduced to predict the rock burst intensity grade. The results show that the accuracy of the rock burst intensity-grade prediction model based on comprehensive weighting and BOA-SVM is as high as 93.30%, which is of higher accuracy and better effect than the ordinary model, and can provide warning information with a higher fault tolerance rate, which provides a new way of thinking for rock burst intensity-grade prediction.

Application Research of the Project Bid Evaluation Model Based on MATLAB

Bid evaluation, an important part of bidding activities, is the most critical part to determine the quality of bidding. For large volume and complex technology projects, the comprehensive evaluation method is usually used in China. It is known that the selection of bid evaluation method has a great influence on the quality of bidding. In the face of the basic situation of China, although the comprehensive evaluation method is basically competent for the bidding work, it still has the defects of human factors in the evaluation of the bid. Therefore, it is essential to improve the bidding evaluation method. This paper mainly evaluates the bid evaluation activities of construction projects based on the comprehensive weighted evaluation method. Through the accumulation of relevant theoretical and practical research results, the author sorts out the advantages and disadvantages of various evaluation methods and analyzes the scientificity, fairness, and practicability of the established project bidding as well as the evaluation model in the evaluation of bidders through the actual project bidding and evaluation case. Combined with the mathematical model and case analysis, the bid evaluation activity is solved by the computer program, and the conventional bid evaluation results and the mathematical model evaluation results are compared to get more accurate bid evaluation results.

Hydropower Unit State Evaluation Model Based on AHP and Gaussian Threshold Improved Fuzzy Comprehensive Evaluation

Because a single monitoring index cannot fully reflect the overall operating status of the hydropower unit, a comprehensive state evaluation model for hydropower units based on the analytic hierarchy process (AHP) and the Gaussian threshold improved fuzzy evaluation is proposed. First, the unit equipment was divided into a hierarchical system, and a three-tier structure system (target layer-project layer-index layer) of the unit was constructed, and the weight of each component in the system was determined by the comprehensive weighting method. Secondly, according to the characteristics of the normal distribution of the historical health data of the unit, the upper and lower limits of the index were determined based on the Gaussian threshold principle, the real-time monitoring index degradation degree was calculated according to the index limit, and the degradation degree was applied to the fuzzy evaluation model to obtain the fuzzy judgment matrix. The result of assessment was divided into four sections: good, qualified, vigilant, and abnormal. Finally, combined with the unit hierarchical structure system, the weighted calculation of the fuzzy judgment matrix of each indicator, the overall fuzzy judgment matrix of the upper-level indicators of the unit was obtained, and the operating status of the unit was judged according to the matrix. Taking a real power plant unit as an example, the model was verified, and compared with other evaluation methods, the effectiveness and advantages of the proposed method were verified. In addition, the method proposed in this paper effectively solved the problems of index weighting and index limit determination in the existing model of unit condition evaluation.

Risk Assessment and Zonation of Roof Water Inrush Based on the Analytic Hierarchy Process, Principle Component Analysis, and Improved Game Theory (AHP–PCA–IGT) Method

With the large-scale mining of deeply buried coal seams, the risk of roof water inrush increases during mining. In order to ensure safe mining, it is necessary to predict the risk potential of water inrush from the roof aquifer. This study introduces a coupling evaluation method, including the analytic hierarchy process (AHP), principal component analysis (PCA), and improved Game theory (IGT). This paper takes the water inrush from the roof aquifer of the 11-2 coal seam in Kouzidong mine as the research object. An evaluation index system is constructed by selecting six evaluation factors, including the aquitard effective thickness, aquiclude thickness, the ratio of sandstone to mudstone, rock quality designation, fault fractal dimension, and wash water quantity of geological log. The comprehensive weighting method based on IGT is used to optimize the subjective and objective weighting values obtained by AHP and PCA methods in turn, and an AHP–PCA–IGT evaluation model is established to divide and evaluate the water inrush risk zonation of the roof aquifer. The risk degree of the water inrush gradually decreases from the center to the north–south, and the main areas with relatively high risks and higher risks are distributed in a small part of the western and eastern regions. Finally, combining various drilling data examples, drilling pumping tests, and water inrush sites, the accuracy of the predicted results is validated through the vulnerability fitting percentage (VFP). The predictions are basically consistent with the actual results, and this study lays a theoretical foundation for the prevention and control of water inrush hazards.

Comprehensive Evaluation of Mine Safety Based on Improved Game Theory

In order to better evaluate the mine safety, this paper uses the improved comprehensive weighting method based on game theory to comprehensively evaluate the mine safety. Firstly, this paper uses the analytic hierarchy process to subjectively weight the indicators and uses the entropy weight method to objectively weight the indicators, and analyzes the weights of the indicators including personnel, environment, management and equipment. Then, the game theory method is used to coordinate the proportion of the two weights, and the final comprehensive weight is obtained. In the scoring part, the triangular fuzzy number method is used to synthesize the qualitative and quantitative indicators and score them. Finally, the final score is obtained by combining the comprehensive weight and the comprehensive score. In the case analysis, the safety of the three mines is analyzed by this method. By comparing the scores of each other, the level of safety and the shortcomings of each mine can be judged.

Does industrial upgrading improve eco-efficiency? Evidence from China's industrial sector

Promoting industrial upgrading is the fundamental path for China to realize the coordination of industrial development and ecological protection. This paper firstly measures the industrial upgrading index (IUI) and eco-efficiency of 37 sub-industries in China's industrial sector based on the comprehensive weighting method and super-efficiency slacks-based measure model, and then for the first time, examines the impact of industrial upgrading on China's industrial eco-efficiency and its differences among industries and influential mechanisms using the panel data models. The following main conclusions are obtained. First, both the IUI and eco-efficiency of China's whole industrial sector showed an upward trend from 2005 to 2019. Second, there are significant gaps in the IUI and eco-efficiency among industries, and these gaps gradually increase in 2005–2019. Third, industrial upgrading significantly improves China's industrial eco-efficiency, and the results of robustness test also support this conclusion. Fourth, industrial upgrading positively affects the eco-efficiency of both high-pollution and low-pollution industries, and the positive effect on low-pollution industries is slightly greater than that on high-pollution industries. Fifth, industrial upgrading improves industrial eco-efficiency by enhancing production efficiency and energy utilization efficiency and optimizing energy consumption structure.

Study on Forest Health Assessment of eastern Qilian Mountains in Qinghai Province

A total of 17 indexes including forest structure, productivity, stability and soil quality were established in the eastern Qilian Mountains. The weights of the indexes were determined by side analysis and entropy weight method. The health status of forest resources in eastern Qilian Mountains of Qinghai Province was evaluated by comprehensive weighting method. The results showed that the distribution and health level of forest resources in the eastern Qilian Mountains of Qinghai province were sub-health.

Automatic Detection of Eddies Based on Remote Sensing SAR Images

A series of problems such as climate change, population explosion and energy crisis make people have to focus on the development of new energy. The 21st Century Maritime Silk Road region, with its large population and well-developed industry, is well suited for the development of new energy, especially offshore wind energy resources. Aiming at the regionalization problem of offshore wind power stations in this region, this paper uses the analysis data of ERA5, GSHHS data, combined with authoritative geography humanities data, combined with subjective and objective comprehensive weighting method, and establishes a comprehensive risk assessment system which is different from previous ones. The results show that wind energy resources, natural environment and geography humanities factors have a certain impact on the location of offshore wind power stations in the 21st century Maritime Silk Road region. Therefore, it is meaningful and necessary to add these indicators into the location index system of offshore wind power stations in the 21st Century Maritime Silk Road region.

Risk Assessment of Water and Sand Inrush in Mining under Thick Loose Layer Based on Comprehensive Weight-Cloud Model

Many deep mining mines in southwestern Shandong Province of China are covered with thick loose layers. When mining near the loose layers, there is a risk of water and sand inrush, which threatens the personal safety of miners. The prediction of sudden water and sand inrush is difficult due to the comprehensive influence of many factors, and the influencing factors are fuzzy and random. To solve this problem, in this paper, a new risk assessment method of water and sand inrush based on comprehensive weight and cloud model was proposed. Seven factors are selected as indexes: the aquifer thickness, the thickness ratio of sand layer to clay layer, the thickness of bottom clay layer, the coal seam thickness, the percentage of core recovery, the geological structure, and the bedrock thickness. The assessment index system is established, and the index is divided into three grades. A comprehensive weighting method, which combines analytic hierarchy process (AHP), entropy weight method (EWM), and minimum entropy principle, is used to reasonably assign the weight of index. Based on the cloud generator equation, the membership function is obtained. The assessment result of the assessment object is obtained by combining the membership degree and the weight of index. The comprehensive weight-cloud model assessment method is applied to the risk assessment of water and sand inrush in the 6311-2 working face in the sixth mining area of Baodian Coal Mine. According to the assessment results, the following conclusions can be drawn: (1) the bedrock thickness and the coal seam thickness are the main factors of water and sand inrush under loose layer mining; (2) the assessment results obtained by the comprehensive weight-cloud model method are consistent with the actual situation. The assessment method can provide scientific reference for the safe mining under the thick loose layer in the deep mines of southwest Shandong.

Sustainability Evaluation of Chinese Capital Cities Based on Urban Geographic Environment Index

Environmental assessments are important tasks for the long-term, sustainable development of cities. With the rapid urbanization in China, it is crucial to establish a City Sustainability Index (CSI) and evaluate the environmental conditions in major cities. However, most of the existing major sustainability indices/indicators are not able to assess cities at diverse levels of development using common axes of evaluation. In this work, we incorporate urban built-up areas extracted from high-resolution remote sensing images as indicators to measure the degree of urban development in city sustainability evaluation and propose a comprehensive index, i.e., the Urban Geographic Environment Index (UGEI). In order to eliminate the impact of urban development levels, UGEI mainly consists of area-averaged indices which are calculated from original indices and urban built-up areas. We adopt a comprehensive weighting method by using the analytic hierarchy process (AHP) method to weigh the high-level indicators and using the entropy weighting method to weigh low-level indicators. We evaluate the environmental conditions of 30 China’s provincial capitals from the aspects of pressure, state, response, and overall status. In addition, we analyze how diverse types of indicators affect the values of UGEIs. The major findings are as follows: (1) About half of the provincial capitals in China have poor sustainability in environmental conditions, and more environmental protection measures should be taken in developing cities; (2) the environmental conditions of the provincial capitals in China present a four-region distribution pattern, namely, the northeastern coastal region, northwest inland region, southwest region, and southeast region; (3) and indices based on urban built-up extents can be common axes of evaluation for cities at diverse levels of development. The proposed UGEI can serve as an effective and reliable index for sustainability evaluation in environmental conditions.

Evaluation of the Development Potential of Urban Underground Space Using Set Pair Analysis and the Comprehensive Weight Method

Recently, a series of urban diseases have seriously impacted the development of large and medium cities. The development of urban underground space (UUS) is widely regarded as an effective solution. Due to the irreversibility of underground space resources, it is important to formulate scientific and reasonable development planning based on evaluation of the development potential of urban underground space (DPUUS). In this work, from the perspective of society, economy, and environment, an evaluation model of the DPUUS was established, and nine indexes were selected, including population density, vehicle possessive quantity per 100 capita, policy support, GDP per capita, GDP per km2, land price, geographical position, geological conditions, and natural disasters. The comprehensive weight method (CWM) combined with subjective and objective weights was used to determine the final weight of the evaluation index. Set pair analysis (SPA) and the credible degree recognition criterion (CDRC) were applied to determine the DPUUS grade of each city, which can provide a new idea for DPUUS.

Evaluation and prediction of ecological carrying capacity in the Qilian Mountain National Park, China

With increasing human impacts on the ecosystem in natural protected areas, there is an urgent need to undertake an assessment of ecological carrying capacity taken as a benchmark for assessing regional sustainability. Based on satellite remote sensing and socio-economic statistical data from 2000 to 2019, this study distinguished the controlling factors for the spatial and temporal patterns of ecological carrying capacity in the Qilian Mountain National Park, one of the 10 pilot national parks in China. The ecological carrying capacity index (ECCI) was developed by using the Driver-Pressure-State-Impact-Response framework and a comprehensive weight method. The results showed that the multiyear averaged ECCI was low in the south and west but was high in central and eastern regions. The spatial distribution of the ECCI was constrained by soil resources, ecosystem quality, land use/cover and water environment. At the regional scale, the ECCI decreased from 2000 to 2014, especially in Tianzhu, where farmland expansion and severe droughts reduced habitat quality and ecosystem function. However, the ECCI increased significantly from 2014 to 2019, which was attributed to a warm moist climate and the implementation of eco-environmental protection policies. Forest and grassland coverage, soil and water conservation, waste water treatment amount and terrestrial water reserves accounted for 35%, 26%, 20% and 8%, respectively, of the temporal variability in the ECCI. Concurrent with national park development, the ECCI is predicted to increase in most areas from 2020 to 2029 by back-propagation artificial neural networks, except for Sunan, Shandan and Menyuan, possibly owing to increasing conflicts between humans and the environment. The findings of this study provide evidence about the effectiveness of government policies in promoting regional sustainability by altering ecosystem composition and function. In addition, the dominant drivers for the temporal variability of ecological carrying capacity varied in space according to stepwise regression analysis, calling for region-specific management strategies in mountain protected areas and their surroundings.

An Improved Unascertained Measure-Set Pair Analysis Model Based on Fuzzy AHP and Entropy for Landslide Susceptibility Zonation Mapping

Landslides are one of the most destructive and common geological disasters in the Tonglvshan mining area, which seriously threatens the safety of surrounding residents and the Tonglvshan ancient copper mine site. Therefore, to effectively reduce the landslide risk and protect the safety of the Tonglvshan ancient copper mine site, it is necessary to carry out a systematic assessment of the landslide susceptibility in the study area. Combining the unascertained measure (UM) theory, the dynamic comprehensive weighting (DCW) method based on the fuzzy analytic hierarchy process (AHP)-entropy weight method and the set pair analysis (SPA) theory, an improved UM-SPA coupling model for landslide susceptibility assessment is proposed in this study. First, a hierarchical evaluation index system including 10 landslide conditioning factors is constructed. Then, the dynamic comprehensive weighting method based on the fuzzy AHP-entropy weight method is used to assign independent comprehensive weights to each evaluation unit. Finally, we optimize the credible degree recognition criteria of UM theory by introducing SPA theory to quantitatively determine the landslide susceptibility level. The results show that the improved UM-SPA model can produce landslide susceptibility zoning maps with high reliability. The whole study area is divided into five susceptibility levels. 5.8% and 10.16% of the Tonglvshan mining area are divided into extremely high susceptibility areas and high susceptibility areas, respectively. The low and extremely low susceptibility areas account for 30.87% and 34.14% of the total area of the study area, respectively. Comparison with the AHP and Entropy-FAHP models indicates that the improved UM-SPA model (AUC = 0.777) shows a better performance than the Entropy-FAHP models (AUC = 0.764) and the conventional AHP (AUC = 0.698). Therefore, these results can provide reference for emergency planning, disaster reduction and prevention decision-making in the Tonglvshan mining area.

Laser sintering of polyether sulfone/carbon black composite powders using near-infrared laser

Low-cost miniaturized laser sintering equipment remains lacking at present; therefore, the development of laser sintering technology and its widespread applications are significantly hindered. Traditional laser sintering equipment is composed of a carbon dioxide laser, water cooling system, powder-box-heating device, and thermal insulation device. Such requirements are the main factors limiting the miniaturization and economic efficiency of laser sintering equipment. Herein, a laser-sintered material was fabricated by sintering using a near-infrared laser light source with a wavelength of 1064 nm without heating, and its microstructure and properties were systematically studied. Polyether sulfone (PES) and carbon black (CB) powders were selected as the raw materials for preparing PES/CB composites by mechanical mixing. For synthesizing the PES/CB composite powders, the CB powder content was varied within the range of 0.25%–1.5%. The PES/CB powders with different component ratios were subjected to laser sintering treatment, and the corresponding microstructural evolutions of the sintered parts were analyzed. The effects of different component ratios on the mechanical properties and dimensional accuracy of the sintered part were investigated, and the optimal content of CB powders of the PES/CB composite material was determined. Additionally, the effects of laser power (10–18 W), scanning speed (1200–1600 mm/s), and scanning spacing (0.04–0.08 mm) on the forming quality of the sintered parts of the PES/CB composite powders were evaluated. The processing parameters of the laser sintering of PES/CB composite powders were explored using orthogonal experimental tests and optimized using the comprehensive weighted method.

Fuzzy dynamic MCDM method based on PRSRV for financial risk evaluation of new energy vehicle industry

The financial risk evaluation of new energy vehicle (NEV) industry is conducive to the popularization of NEVs, to encourage more investment into the NEV industry, and to promote the improvement of the risk control system. When evaluating the performance of NEV industry in China, it is usually full of uncertainty and dynamic. q-Rung orthopair fuzzy set (q-ROFS) has the characteristics of non-membership and membership with adjustable parameterization q, which is a very effective mathematical model to capture uncertainty. In this paper, the q-rung orthopair fuzzy (q-ROF) distance measure based triangle orthocenter is given. Then, q-ROF score function (SF) based distance measure is proposed for disposing of comparison issue. Moreover, we present nonlinear comprehensive weighting method by integrating subjective weight information and objective weight information (determining by water-filling theory). In order to solve the counter-intuitive phenomena and dynamic trend issue, the dynamic q-ROF aggregation operators are investigated and their properties are proved. Whereafter, q-ROF multi-criteria decision making (MCDM) approach based projection ranking by similarity to referencing vector (PRSRV) is proposed for evaluating financial risk of NEV industry, along with the sensitivity analysis. Finally, a comparison with some existing MCDM methods states that the presented method has strong data adaptability.

Multi-dimensional safety risk assessment on coal mines under the profitability dilemma

China is a major coal producer, with huge differences in coal production and safety situations between the South and the North. Taking province A as an example, its coal enterprises have low output, poor efficiency, backward equipment, and low-quality personnel. The output accounts for 0.08% of the country, and the number of deaths accounts for 2.2% of the country, the safety situation of coal enterprises in province A is severe. In order to study the safety risk situation of coal mines under difficult conditions, this paper screens 98 factor indexes including multiple subjects such as enterprise managers, front-line workers, government supervisors, external environment, work quality, stress factors, economic factors, and other dimensions. For different data, the indicator weights were calculated using triangular fuzzy number, entropy weight method, CRITIC method, and three rough set methods in a total of six methods. The comprehensive weights of the indicators were obtained using the proposed new comprehensive weight method. The current situation of safety work of four coal mining enterprises and three levels of government supervision departments was evaluated, and the evaluation results were compared with other existing data to verify the reliability of the evaluation system. The horizontal comparison of the evaluation results indicates the main problems of each subject; the longitudinal comparison points out the problems that need to be solved with the assistance of higher-level enterprises and the central government, and corresponding suggestions for coal mining enterprises and government departments are put forward to reduce the safety risks of troubled coal mining enterprises.

Data-driven multi-criteria decision support method for electric vehicle selection

Electric vehicles (EVs) are becoming one of the most popular forms of low-carbon transportations due to growing awareness of environmental protection and vigorous promotion of governments. Automakers have launched a variety of EVs in an attempt to capture the market, raising the question of how to improve the competitiveness of the EVs they have launched. Meanwhile, choosing among various EVs has become a problem for consumers. This paper proposes a sentiment analysis-based multi-criteria decision-making (MCDM) method. The group opinion for each alternative can be derived by transforming the sentiment analysis results of online auto reviews into hesitant intuitionistic fuzzy elements (HIFEs). A comprehensive weighting method that integrates the best-worst method and the maximizing deviation method is developed to identify the weights of criteria. Through extended ORESTE (Organísation, rangement et Synthése de données relarionnelles, in French) based on hesitant intuitionistic fuzzy Chebyshev distance, the ranking of candidate EV series can be obtained. The proposed method can help consumers make EV purchase choices, and the results of sentiment analysis can be useful for companies to explore consumers' demand for EVs.

基于主体功能区的长江经济带绿色发展评价与问题区域识别

PDF HTML阅读 XML下载 导出引用 引用提醒 基于主体功能区的长江经济带绿色发展评价与问题区域识别 DOI: 10.5846/stxb202204221098 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 中国科学院战略性先导科技专项（A类）（XDA23040504）；2022年江苏省研究生科研与实践创新计划项目（1812000024808） Green development evaluation and problem areas identification of the Yangtze River Economic Belt from the perspective of major function oriented zones Author: Affiliation: Fund Project: 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:长江经济带已成为我国推进绿色发展的重要阵地。基于主体功能区视角，构建以水系统为纽带的长江经济带绿色发展评价指标体系，采用综合加权法、空间自相关、耦合协调度模型等方法探究2018年长江经济带130个城市绿色发展及各子系统耦合协调水平的空间格局，并对绿色发展的问题区域进行分类识别。结果表明：（1）长江经济带绿色发展水平呈由下游、中游至上游递减趋势；各主体功能区绿色发展指数表现为优化开发区 > 限制开发区 > 重点开发区。（2）绿色发展各子系统耦合协调度值位于0.365-0.656之间，多处于濒临失调和勉强协调的临界区间，耦合协调水平整体偏低。（3）从长江经济带整体来看，长江中上游地区绝大部分城市绿色发展主要受资源利用和产业发展水平偏低，及由此带来的生态和生活问题限制，且长江中上游地区各省会或直辖市对区域内其他城市绿色发展带动能力不足。从主体功能区视角来看，优化开发区以生态问题为主，仅上海和嘉兴两市；重点开发区以生态和生产问题为主，集中于武汉都市圈和成渝双城经济圈内部；限制开发区以生产和生活问题为主，主要位于省际边界型城市地区。最后综合问题识别结果，分别对长江经济带各主要问题区域绿色发展路径提出具体对策建议。 Abstract:The Yangtze River Economic Belt has become an important region for promoting green development in China. From the perspective of major function oriented zones, the green development evaluation index system of the Yangtze River Economic Belt with the water system as the link was constructed. The spatial pattern of green development and the level of coupling and coordination of each subsystem in 130 cities in the Yangtze River Economic Belt in 2018 was explored by using the comprehensive weighting method, spatial autocorrelation and coupling and coordination model, and the problem areas of green development were identified by classification. The results show that:1) the green development level of Yangtze River Economic Belt indicates a decreasing trend from downstream, midstream to upstream. The green development index of each major function oriented zone is shown as optimized development zone>restricted development zone>key development zone. 2) The value of coupling coordination of green development subsystems is between 0.365-0.656, which is mostly in the critical range of near disorder and barely coordinated, and the overall level of coupling coordination is low. 3) From the perspective of the Yangtze River Economic Belt as a whole, the green development of most cities in the middle and upper reaches of the Yangtze River is mainly limited by the low level of resource utilization and industrial development, and the consequently ecological and living problems. The ability of each provincial capital or municipality directly under the central government in the middle and upper reaches of the Yangtze River to drive the green development of other cities in the region is insufficient. From the perspective of major function oriented zones, the optimized development zones are dominated by ecological issues, with only Shanghai and Jiaxing; the key development zones are dominated by ecological and production issues, concentrated within the Wuhan metropolitan area and the Chengdu-Chongqing economic circle; and the restricted development zones are dominated by production and living issues, mainly located in inter-provincial border city areas. Finally, the problem identification results are integrated and specific countermeasures are proposed for the green development path of each major problem area in the Yangtze River Economic Belt respectively. 参考文献 相似文献 引证文献