Search Results (6)

In China, rapid economic and social development has caused the carrying capacity of water resources in some areas to reach or exceed the limit, threatening the stability of resources and the development of the national economy. In view of the current situation of serious water shortage in Tai’an City, we constructed a comprehensive evaluation model of water resources carrying capacity in Tai’an City by using socio-economic and water resources data from 2016 and 2023. Our method covers multiple dimensions such as natural geography, socio-economy, water quantity, ecological environment, and resource utilization. The analytic hierarchy process (AHP) and entropy weighting methods were applied to determine the weights of the indicators, the set pair analysis theory (SPA) and variable fuzzy set theory (VFS) were used to establish a comprehensive evaluation model of water resources carrying capacity, and the level of water resources carrying capacity and obstacles encountered in improving water resources carrying capacity in Tai’an were evaluated and analyzed. Our results show that Tai’an is generally developing in a coordinated manner across the country, but there are obvious differences in the carrying capacity of water resources in different areas, which require the development of targeted resource management strategies. The study has the potential to advance regional water resources carrying capacity. Full article

Flood disasters are considered to be one of the ten natural disasters that threaten the survival of mankind. They occur frequently and have a serious impact on the national economy. For quicker response to the sudden flood, in this paper, the relevant characteristics of flood forecasting and disaster assessment are comprehensively studied to establish the corresponding models, and a multi-objective culture shuffled complex differential evolution (MOCSCDE) algorithm is proposed to optimize the model parameters. It can achieve better convergence and significantly improve the model accuracy. Then, a river hydrodynamic model is established to simulate the flooding process, and the characteristics of flood evolution, such as water depth, flow speed, duration, and submerged area, are analyzed. Third, based on the above-mentioned flood forecasting and flood evolution calculations, the relative membership function (VFS) is determined via the set pair analysis method (SPA), and the variable fuzzy set model (SPAVFS) is used for flood risk assessment. Finally, through the study of flow forecasting at Zhouqu hydrological station, it is found that the accuracy of the forecast result of the built model is best compared with LSTM and XAJ model, the mean relative error is only 7.6%, and the certainty coefficient can reach 0.96, which surpass the baselines by 20% and 7.9%. Full article

The research on the sustainability evaluation of innovation and entrepreneurship education for clean energy majors in colleges and universities can not only cultivate more and better innovative and entrepreneurial talents for the development of sustainable energy but also provide a reference for the sustainable development of innovation and entrepreneurship education for other majors. To achieve systematic and comprehensive scientific evaluation, this paper proposes an evaluation model based on SPA-VFS and Chaos bat algorithm to optimize GRNN. Firstly, the sustainability evaluation index system of innovation and entrepreneurship education for clean energy major in colleges and universities is constructed from the four aspects of the environment, investment, process, and results, and the meaning of each evaluation index is explained; Then, combined with variable fuzzy set evaluation theory (VFS) and set pair analysis theory (SPA), the classical evaluation model based on SPA-VFS is constructed, and the entropy weight method and rank method are coupled to obtain the index weight. The basic bat algorithm is improved by using Tent chaotic mapping, and the chaotic bat algorithm (CBA) is proposed. The generalized regression neural network (GRNN) model is optimized by CBA, and the intelligent evaluation model based on CBA-GRNN is obtained to realize fast real-time calculation; finally, a numerical example is used to verify the scientificity and accuracy of the model proposed in this paper. This study is conducive to a comprehensive evaluation of the sustainability of innovation and entrepreneurship education for clean energy major in colleges and universities, and is conducive to the healthy and sustainable development of innovation and entrepreneurship education for clean energy major in colleges and universities, so as to provide more innovative and entrepreneurial talents for the clean energy industry. Full article

Rockburst intensity prediction is one of the basic works of underground engineering disaster prevention and mitigation. Considering the dynamic variability and fuzziness in rockburst intensity prediction, variable fuzzy sets (VFS) are selected for evaluation and prediction. Here, there are two problems in the application of traditional VFS: (i) the relative membership degree (RMD) calculation process is complex and time-consuming, and the RMD matrix of all indexes can be only obtained by using the RMD function repeatedly; (ii) unreasonable weights of indicators have great impact on the synthetic relative membership degree (SRMD), so it is difficult to guarantee the correctness of the final prediction result. In view of the above problem, this paper established three simplified feature relationship expressions of RMD based on VFS principle and used the SRMD function to establish a BP neural network model to optimize SRMD. The improved VFS method is more efficient and the prediction results are more stable and reliable than the traditional VFS method. The main advantages are as follows: (1) the improved VFS method has higher computational efficiency; (2) the improved VFS method can verify the correctness of RMD at all times; (3) the improved VFS method has higher prediction accuracy; and (4) the improved VFS method has higher fault tolerance and practicability. Full article

In this study, a new optimized comprehensive drought index system (OCDIS) was developed based on pressure-state-response (PSR) and random forest (RF). Then the pressure, state, response, and integrated agricultural drought risk were evaluated according to the synthetic-weight variable fuzzy set (SW-VFS) model. Finally, the countermeasures in terms of pressure, state, and response were discussed. The proposed index has been implemented in Qujing, Yunnan Province, China. The results showed that of the 10 indices included in the OCDIS, the four most important indices for agricultural drought risk management are reservoir storage capacity, precipitation anomaly percentage, soil moisture, and per capita annual income. The pressure risk and response risk of Malong are relatively higher than other counties. The integrated results indicated that most counties of Quijng have moderate drought risk. The assessment results are consistent with the actual situation of Qujing. The proposed model provides a scientific and objective way to develop the risk index system of agricultural drought. This study can potentially assist government agencies with information on the most important drought impacts and provide the basis for science-informed decision-making. Full article

A new model for risk assessment of agricultural drought based on information diffusion method and variable fuzzy sets (IDM-VFS) was proposed. In addition, an integrated index system of agricultural drought risk was established. In the proposed model, IDM was employed to calculate the agricultural drought risk level classification standards, and then the VFS was adopted to assess the dangerousness, sensitivity, vulnerability, and comprehensive risk of agricultural droughts. In the present study, Nanpan River Basin was employed to assess the agricultural drought risk with the proposed model. The results showed that KaiYuan, ShiZong, QiuBei, and ZhanYi have higher dangerousness, due to water shortage. GuangNan have higher sensitivity and vulnerability because of lower drought resistance level and higher crop planting proportion. The comprehensive agricultural drought risk shows apparent regional characteristics: the central, western and northwestern counties have lower risk than the eastern counties. Moreover, most areas of the Nanpan River Basin are of moderate agricultural drought risk grade. The results are consistent with the actual situation of Nanpan River Basin and verify the model’s effectiveness. The study can provide a scientific reference in drought risk management for local governmental agencies. Full article