Social Risk Early Warning of Environmental Damage of Large-Scale Construction Projects in China Based on Network Governance and LSTM Model

Abstract

With the improvement of citizens’ risk perception ability and environmental protection awareness, social conflicts caused by environmental problems in large-scale construction projects are becoming more and more frequent. Traditional social risk prevention management has some defects in obtaining risk data, such as limited coverage, poor availability, and insufficient timeliness, which makes it impossible to realize effective early warning of social risks in the era of big data. This paper focuses on the three environments of diversification of stakeholders, risk media, and big data era. The evolution characteristics of the social risk of environmental damage of large-scale construction projects are analyzed from the four stages of incubation, outbreak, mitigation, and regression in essence. On this basis, a social risk early warning model is constructed， and the multicenter network governance mode of social risk of environmental damage in large-scale construction projects and practical social risk prevention strategies in different stages are put forward. Experiments show that the long short-term memory neural network model is effective and feasible for predicting the social risk trend of environmental damage of large-scale construction projects. Compared with other classical models, the long short-term memory model has the advantages of strong processing capability and high early warning accuracy for time-sensitive data and will have broad application prospects in the field of risk control research. By using the network governance framework and long short-term memory model, this paper studies the environmental mass events of large-scale construction projects on the risk early warning method, providing reference for the government to effectively prevent and control social risk of environmental damage of large-scale construction project in China.

Research on Multiple Optimization of Engineering Management Models under the Concept of Environmental Protection

“…The implementation of the concept of environmentally friendly construction depends on the implementation of various technologies and economic benefits, such as a building; although the initial cost of environmentally friendly construction is higher than the conventional 5% to 10%, the operation and maintenance costs of the traditional building in the later stage is nearly 20 times higher than that of environmentally friendly construction. Therefore, the idea of "environmentally friendly construction" is significant in terms of economic, social, and ecological benefits [13][14][15].…”

Megapolis Residents’ Readiness to Participate in Megaprojects Under the Conditions of the Digitalization of the Economy and the Use of Artificial Intelligence

“…Failure to consider these factors entails the negative socio-economic effect of megaprojects on the regional infrastructure (Frolova et al, 2016) and the residents of the locations where large-scale transformation and work takes place (Aung et al, 2021). In the conditions of the digitalization of society and the introduction of artificial intelligence, this factor poses a threat to the strategies of not only development but the very existence of society (Wang et al, 2021;Nkansah-Dwamena & Raschke, 2021) and generates social and ecological risks (Fang et al, 2021;Rybakova et al, 2019). This is contradictory to the Sustainable Development Goals (SDGs) (Ridho et al, 2018;Kramarenko et al, 2020).…”