The student’s political and ideological practices is a vital portion of education, and it is related to optimization of task based on fundamental scenario in establishing morality. In order to establish a scientific, reasonable and operable evaluation model for students’ ideological education, and evaluate the status of college students’ ideological education. In this paper, firstly, in view of the shortcomings of evaluation objectives, single evaluation methods, lack of pertinence of evaluation indicators and subjectivity of evaluation standards in the current evaluation system of university students’ ideological and political education, the basic principles for constructing evaluation models of university students’ ideological and political education are put forward. Secondly, in case to meet changing needs of the times, an artificial neural network algorithm based on artificial intelligence data mining and a traditional multi-layer fuzzy evaluation model are designed to evaluate the ideological and political education of college students. This newly proposed model integrates learning, association, recognition, self-adaptive and fuzzy information processing, and at the same time, it overcomes their respective shortcomings. Finally, an example analysis is carried out with a nearby university as an example. The evaluation results display that the evaluation model of students’ ideological education established in this paper is in good agreement with the previous evaluation results. It fully shows that the comprehensive evaluation model of fuzzy neural network for college students’ ideological and political education established in this paper is scientific and effective.

An artificial intelligence data mining technology based evaluation model of education on political and ideological strategy of students

It will be a huge challenge for China to achieve carbon neutrality by 2060. At present, China needs to understand its own carbon neutrality status and then scientifically plan a path to achieve carbon neutrality. In order to evaluate the carbon neutrality capacity of China’s provinces, this paper firstly constructs an evaluation indicator system, which includes 20 indicators at six levels. Then, a combination of subjective and objective weighting methods, as well as an improved technique for order preference by similarity to an ideal solution (TOPSIS) model, are used to calculate evaluation results. On this basis, the reasons for their different carbon neutrality capacities are analyzed. The results show that the use of renewable energy, maintaining ecological environmental quality, and low-carbon technology are important factors affecting China’s carbon neutrality capacity, and according to the evaluation results, China’s provinces are divided into three categories. Finally, corresponding suggestions for speeding up the pace of carbon neutrality are put forward.

Evaluation of Provincial Carbon Neutrality Capacity of China Based on Combined Weight and Improved TOPSIS Model

It is acknowledged that construction safety is pivotal to the project management objectives. Meanwhile, the concept of resilience provides an effective and pragmatic countermeasure to improve the safety management level of construction projects. However, the “resilience” has not gained considerable attention in the construction safety management system. In this context, the paper aims to develop the key safety management factors for construction projects from the resilience perspective. Firstly, the theoretical framework and key safety management factors of construction safety management system based on the resilience theory are proposed. The importance of each factor is then obtained by using the method of structural equation modeling (SEM). The results indicate that information management, material and technology management, organization management and personnel management would improve the safety and resilience of the project. Specifically, improving the resilience of information flow to strengthen the interaction among elements of the system can enhance the safety management level. These findings can be used as references for construction safety managers to improve the abilities of preventing safety accidents and recovering after safety accidents.

https://www.mdpi.com/1660-4601/17/17/6167/pdf

Developing Key Safety Management Factors for Construction Projects in China: A Resilience Perspective.

The rapid urbanization of the Yangtze River Delta urban agglomeration has led to the convergence of population, land and capital. The coordination between land development intensity and urban resilience has become a key issue in the post-urbanization period. From the perspective of regional overall and coordinated development, we constructed an evaluation index system of land development intensity and urban resilience. Then, the comprehensive evaluation model, coupling coordination degree model and panel Tobit regression model were adopted to systematically study the temporal and spatial differentiation of and influencing factors on the coupling coordination degree between land development intensity and urban resilience in the Yangtze River Delta urban agglomeration from 2009 to 2019. The results show that from 2009 to 2019, the land development intensity exhibited a slow and fluctuating increase, while the urban resilience displayed continuous growth, and the level of land development intensity generally lagged behind that of urban resilience. From 2009 to 2019, the average coupling coordination degree between land development intensity and urban resilience in the Yangtze River Delta urban agglomeration increased from 0.5177 to 0.6626, which generally changed from bare coordination to moderate coordination. In terms of spatial distribution, the coastal cities and cities along the Yangtze River were characterized by high coupling coordination degrees, which formed a “T” shape distribution pattern. In addition, the coupling coordination types showed certain spatio-temporal heterogeneity among cities. Finally, land economic benefit, green industrial development, scientific and technological innovation, social management and infrastructure all had significant impacts on the coupling and coordination between land development intensity and urban resilience in the Yangtze River Delta urban agglomeration.

/pdf/coupling-coordination-and-influencing-factors-of-land-2jz6fmzb.pdf

Coupling Coordination and Influencing Factors of Land Development Intensity and Urban Resilience of the Yangtze River Delta Urban Agglomeration

Research on land subsidence is a global topic. In recent years, the environmental problems caused by coal mining have received great attention. In particular, mining land subsidence caused damage to villages, buildings, farmland, etc., which seriously threatened the mining area’s living environment and ecological environment. This study proposes a pressure-state-response concept model based on mining land subsidence to build an evaluation index system in coal mines. Based on this index system, given the uncertainty in the evaluation process, the cloud model is used to represent the index weight and comprehensive evaluation calculations, which fully consider the randomness and ambiguity in the evaluation process. The mining land subsidence of several mining areas in China was evaluated and classified into three grades (slight-medium-strong). The cloud model assessment results are compared with the result of the probability integration method and the actual situation. The assessment results of the cloud model are closer to the actual situation than the probability integration method. This shows that the established mining land subsidence evaluation method based on the cloud model in this study is reasonable and feasible. The mining width and height ratio, depth and height ratio, and coal seam dip angle affect mining land subsidence. Therefore, improving the mining method to deal with the goaf reasonably and optimizing the mining design to control the influence range of mining are essential measures to reduce mining land subsidence and protect the ecological environment of mining areas.

Assessment of coal mining land subsidence by using an innovative comprehensive weighted cloud model combined with a PSR conceptual model

To scientifically and quantitatively evaluate the current city safety resilience and improve the city safety resilience level, this project puts forward the concept and degree of city safety resilience based on the systematic analysis of the city safety resilience curve and establishes the framework of a city safety resilience evaluation index system, including predisaster prevention, disaster-bearing carrier, emergencies and emergency management. The Delphi method and cloud model are used to construct the city safety resilience evaluation model, and the weight and application of the model are analyzed and discussed. The research results show that the theory and method of Chinese city safety resilience evaluation based on the Delphi method and cloud model have important guiding significance for improving the city safety resilience level.

Research on Evaluation Index System of Chinese City Safety Resilience Based on Delphi Method and Cloud Model.

With the rapid development of computer technology, artificial intelligence has been paid more and more attention, and artificial intelligence technology has become one of the most popular technologies. In this paper, artificial intelligence is used as the technical means to combine artificial intelligence with hybrid courses, and the plant landscape course is taken as an example. In the plant landscape course, Superstar is used as the online course platform, and students can learn at anytime and anywhere through mobile phones, ipads, computers and other electronic products. It also analyzes the online learning of students in all aspects. In short, artificial intelligence plays an important role in the reform of modern education and teaching.

Design of Data Mining Hybrid Teaching System based on Artificial Intelligence Era Algorithm

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Research on Evaluation Index System of Chinese City Safety Resilience Based on Delphi Method and Cloud Model.

Design of Data Mining Hybrid Teaching System based on Artificial Intelligence Era Algorithm