Ecological environment management system based on artificial intelligence and complex numerical optimization

2021 ◽  
Vol 80 ◽  
pp. 103627
Author(s):  
Lei Niu ◽  
Longhang Xiao
Author(s):  
Shagufta Parveen M.A. Ansari ◽  
Joseph Oduor Odongo ◽  
M.Z.M. Nomani ◽  
Ghazal Salahuddin ◽  
Mohammed Faez Hasan ◽  
...  

2022 ◽  
Vol 14 (2) ◽  
pp. 912
Author(s):  
Wenhan Ren ◽  
Jing Ni ◽  
Yu Chen

China’s management of marine ecological environments has experienced a development process that has gone from weak to strong. However, whether there are problems such as lack of systems, invalid systems, and system conflicts in the current management of marine ecological environments, and how to conduct collaborative governance among various complex subjects, remain to be answered. This paper first summarizes how China’s marine ecological environment management policy has evolved, which can be divided into five stages: the foundation stage (1949–1980), the initial establishment stage (1981–1995), the steady advancement stage (1996–2005), the deepening adjustment stage (2006–2010), and the strategic development stage (2011–present), and analyzes its characteristics at different stages. Then, this paper further explores the inherent dilemmas in the Chinese marine ecological environment management system. Finally, combined with the practical experience of marine ecological environment management in developed countries, this paper fully considers the division of responsibilities and mutual checks and balances of different subjects, flexibly configures various policy tools, and explores the mechanism of collaborative governance of marine ecological environment from the levels of government, market, the public and social organizations, so as to gradually improve the modern marine ecological environment management system and provide a reference for the government’s governance activities.


2021 ◽  
pp. 1-10
Author(s):  
Xuying Sun ◽  
Yu Zhang

The importance of the management of ideological and political theory courses in colleges and universities is objective to the importance of ideological and political theory courses. At present, the management of ideological and political theory courses in colleges and universities has big problems in both macro and micro aspects. This paper combines artificial intelligence technology to build an intelligent management system for ideological and political education in colleges and universities based on artificial intelligence, and conducts classroom supervision through intelligent recognition of student status. The KNN outlier detection algorithm based on KD-Tree is proposed to extract the state information of class students. Through data simulation, it can be known that the KD-KNN outlier detection algorithm proposed in this paper significantly improves the efficiency of the algorithm while ensuring the accuracy of the KNN algorithm classification. Through experimental research, it can be seen that the construction of this system not only clarifies the direction of management from a macro perspective, but also reveals specific methods of management from a micro perspective, and to a certain extent effectively solves the problems in the management of ideological and political theory courses in colleges and universities.


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