Evaluating the capability of municipal solid waste separation in China based on AHP-EWM and BP neural network

Fault monitoring method of domestic waste incineration slag sorting device based on back propagation neural network

The main monitoring points of traditional sorting equipment fault monitoring methods are usually limited to the inlet and outlet, making it difficult to monitor the internal equipment, which may affect the accuracy of fault monitoring. Therefore, a new fault monitoring method based on back propagation neural network has been studied and designed, which is mainly applied to the sorting device of domestic waste incineration slag. The fault monitoring modeling variables of the domestic waste incineration slag sorting device are selected to determine the operation status of the sorting device. Based on back propagation neural network, a fault monitoring model for the sorting device of municipal solid waste incinerator slag is constructed, and the fault data of the sorting device is trained in the model, so that the fault data of the sorting device can be optimized faster, thus improving the accuracy of fault monitoring. Through comparative experiments with traditional methods, it has been confirmed that this fault monitoring method based on back propagation neural network has significant advantages in detection performance, demonstrating its potential in practical applications.

Integrated evaluation of the performance of phosphogypsum recycling technologies in China

The Chinese government is implementing policies, such as the "Guidance on comprehensive utilization of bulk solid waste for the 14th Five-Year Plan period", to stimulate phosphogypsum (PG) reduction and recycling. Thus, the comprehensive evaluation of PG recycling technologies for sustainable development is crucial. This study proposes a novel multi-criteria decision analysis (MCDA) method that considers the criteria of resources, environment, economy, and society and risk attitudes of decision-makers and integrates game theory (GT) and utility theory for criteria weighting and ranking to assess industrial-scale PG recycling technologies in China. The results demonstrate that GT provides more reasonable criteria weights than individual weighting methods. PG-based lightweight plaster is the top performer in the resource and environmental dimensions owing to its exceptional resource and energy efficiency. PG utilized for dry-mix mortar and organic fertilizer production exhibited the best utility performance of 0.74 and 0.73, respectively. Measures, such as subsidies and product publicity, should be implemented to promote these technologies. However, technologies with poor performance, such as PG used for the co-production of sulfuric acid and fertilizer or cement, may require optimization or substitution for the sustainable recycling of PG. The proposed MCDA method is robust and can serve as a reliable decision-making tool for other waste-recycling technologies. However, caution must be exercised when determining risk attitude using the MCDA method as it may vary with the number of technologies and affect the final rankings.

Evaluation of Heterogeneity in Tectonically Deformed Coal Reservoirs Based on the Analytic Hierarchy Process-Entropy Weight Method Coupling Model: A Case Study

This article presents a comprehensive analysis of the factors influencing the heterogeneity of tectonic coal reservoirs, focusing on the metamorphic degree and pore-fracture parameters of tectonic coal. To ensure a reliable evaluation, the AHP-EWM coupling evaluation model (analytic hierarchy process and entropy weight method), which integrates the strengths of both evaluation models and minimizes the potential errors associated with a single model, was employed to assess the heterogeneity index of coal reservoirs in the Panguan syncline. According to the findings of the AHP-EWM model, it was observed that the comprehensive index of coal heterogeneity consistently increases as the degree of coal deformation increases. Notably, a critical value of I = 0.48 was identified as the threshold for the comprehensive index of brittle and ductile deformation coal heterogeneity. Furthermore, the pore-fracture characteristic was determined to have the greatest effect on the heterogeneity of coal reservoirs, followed by the metamorphic degree. This research contributes significantly to the identification of high-quality coalbed methane reservoirs in the Panguan syncline of western Guizhou, serving as a valuable point of reference.

Using the Sustainable Development Capacity of Key Counties to Guide Rural Revitalization in China

Counties are the basic unit for addressing unbalanced development in a region, revitalizing rural areas, and promoting the integrated development of urban and rural areas. Despite the importance of county-level research, few studies have been conducted research at such a small scale. To address this gap in knowledge, this study constructs an evaluation system to measure the county sustainable development capacity (CSDC) of counties in China, identify constraints to development, and provide policy suggestions to promote the counties' long-term stable development. Specifically, the CSDC indicator system was based on the regional theory of sustainable development and included economic aggregation capacity, social development capacity, and environmental carrying capacity. This framework was applied to 103 key counties to receive assistance in pursuing rural revitalization in 10 provinces in western China. The AHP-Entropy Weighting Method and TOPSIS model were employed to inform the scores of CSDC and its secondary indicators, and ArcGIS 10.8 was used to portray the spatial distribution of CSDC and to classify these key counties into categories that guided specific policy recommendations. The results demonstrate a high degree of unbalanced and inadequate development in these counties and that rural revitalization efforts can be targeted to increase the speed of development. It is crucial to follow the recommendations that conclude this paper to promote sustainable development in areas that have been lifted out of poverty and to revive rural areas.

Study on Water Resource Carrying Capacity of Zhengzhou City Based on DPSIR Model

Based on the driving force-pressure-state-impact-response (DPSIR) model, a comprehensive evaluation index system is constructed. The index weight is determined by the combination weighting method in combination with the data of 2010-2019. The TOPSIS model is used to comprehensively analyze the water resource carrying capacity of Zhengzhou as the central city in China with a developed economy and relatively short water resources. The study results are as follows. (1) During the sample period, the comprehensive evaluation value of water resources carrying capacity of Zhengzhou increases from 0.4183 in 2010 to 0.5560 in 2019, with an overall fluctuating rise. Simultaneously, the water resource carrying capacity grade improves from Grade III (normal carrying capacity) to Grade II (good carrying capacity). (2) The contribution of each subsystem to the comprehensive evaluation value increases year by year. Among them, S subsystem and I subsystem make the largest contribution to the comprehensive carrying capacity. R subsystem makes a relatively stable contribution to the overall carrying capacity. Affected by GDP growth rate and uneven temporal-spatial distribution of water resources in Zhengzhou, the D subsystem and P subsystem of water resource carrying capacities show the fluctuating change. Finally, based on the above conclusions, this paper puts forward the countermeasures and suggestions to improve the level of water resource carrying capacity of Zhengzhou.

Research on adaptive combined wind speed prediction for each season based on improved gray relational analysis

The stability of the power grid and the operational security of the power system depend on the precise prediction of wind speed. In consideration of the nonlinear and non-stationary characteristics of wind speed in different seasons, this paper employs the weight of wind resource index calculated by triangular fuzzy analytic hierarchy process (TF-AHP), criteria importance through inter-criteria correlation (CRITIC), and entropy weight method (EWM) to improve gray correlation analysis (GRA) and obtain the gray correlation degree of each season. In addition, a wind speed prediction model is provided that includes single-layer and two-layer weighting and is based on both deep and shallow machine learning models. At first, we establish each quarter's wind resource characteristics at typical monthly intervals of 10 min, 30 min, 60 min, and 120 min. The GRA's TF-AHP-CRITIC-EWM, enhanced with subjective and objective weights, is used to assess the available wind resources in each season and to compute the forecasted combination of wind speed for each season. As the final prediction results, the prediction values of each layer model are evaluated independently. For the intervals with considerable errors, we apply wavelet denoising and replacement combination. The simulation findings show that the proposed combined model surpasses earlier benchmark models in terms of goodness of fit, prediction accuracy, and generalizability.

Evaluating the Comprehensive Benefit of Urban Renewal Projects on the Area Scale: An Integrated Method

Globally, the challenges facing cities regarding urban decay, insufficient urban function, and fragmented urban development are enormous. Under this context, urban renewal provides opportunities to address these challenges and enhance urban sustainability. Thus, promoting urban renewal projects and improving their performance is a global topic. In many circumstances, urban renewal is planned and initiated on the project scale, but on the area scale, overall coordination of the projects can bring about comprehensive benefits to urban areas on a macro view. In practice, it still lacks a systematic evaluation approach to obtain a clear picture of such comprehensive benefits. In academia, the existing research studies are mainly focused on single-project evaluation. An integrated framework that provides a holistic assessment of area-scale project benefits is missing. Few fully consider the coupling coordination benefits between several urban renewal projects from an area-scale perspective. Thus, this paper aims to propose a framework for integrating an indicator evaluation system through a hybrid entropy weight method with Back Propagation (BP) neural network methods to evaluate the comprehensive benefit of urban renewal projects on the area scale, which is the level at which most development area-scale renewal projects take place in a city. The feasibility and effectiveness of this proposed framework are then verified in a case study of Chongqing, China. The results indicate that the proposed method that integrated multi-project characteristics can contribute to a bigger picture of benefit evaluation of urban renewal based on an area scale perspective. This therefore provides not only guidance for urban planners and policymakers to make better decisions, but also new insight for benefit evaluation in the field of urban development.

Establishment of an indicator framework for global One Health Intrinsic Drivers index based on the grounded theory and fuzzy analytical hierarchy-entropy weight method

BACKGROUND

One Health has become a global consensus to deal with complex health problems. However, the progress of One Health implementation in many countries is still relatively slow, and there is a lack of systematic evaluation index. The purpose of this study was to establish an indicator framework for global One Health Intrinsic Drivers index (GOH-IDI) to evaluate human, animal and environmental health development process globally.

METHOD

First, 82 studies were deeply analyzed by a grounded theory (GT) method, including open coding, axial coding, and selective coding, to establish a three-level indicator framework, which was composed of three selective codes, 19 axial codes, and 79 open codes. Then, through semi-structured interviews with 28 health-related experts, the indicators were further integrated and simplified according to the inclusion criteria of the indicators. Finally, the fuzzy analytical hierarchy process combined with the entropy weight method was used to assign weights to the indicators, thus, forming the evaluation indicator framework of human, animal and environmental health development process.

RESULTS

An indicator framework for GOH-IDI was formed consisting of three selective codes, 15 axial codes and 61 open codes. There were six axial codes for "Human Health", of which "Infectious Diseases" had the highest weight (19.76%) and "Injuries and Violence" had the lowest weight (11.72%). There were four axial codes for "Animal Health", of which "Animal Epidemic Disease" had the highest weight (39.28%) and "Animal Nutritional Status" had the lowest weight (11.59%). Five axial codes were set under "Environmental Health", among which, "Air Quality and Climate Change" had the highest weight (22.63%) and "Hazardous Chemicals" had the lowest weight (17.82%).

CONCLUSIONS

An indicator framework for GOH-IDI was established in this study. The framework were universal, balanced, and scientific, which hopefully to be a tool for evaluation of the joint development of human, animal and environmental health in different regions globally.

Safety Risks of Primary and Secondary Schools in China: A Systematic Analysis Using AHP–EWM Method

Owing to the frequent accidents in primary and secondary schools (PSS) in China in the past decades, a systematic analysis of indicators influencing safety risks in PSS is critical to identifying preventive measures. A two-hierarchy structure of indicators was identified by analyzing various cases, intensive interviews, and related previous literature. A combination of the analytic hierarchy process and the entropy weight method was developed to synthetically assess the primary and secondary risk indicators through a case study of Ma Shan School in China. The results are as follows: (1) the primary risk indicators, namely, natural disasters, public health, facility safety, accidental injury, public security, school bullying, and individual health constitute the evaluation framework of the safety risks in PSS. (2) Public health risks and accidental injury risks are the most critical factors that should be prioritized. In addition to providing academic implications, several managerial implications are proposed for these stakeholders to reduce the safety risks in PSS.