Abstract
In this paper, we study the radial neural network algorithm for low-carbon circular economy in forest area, design a coupled development evaluation model, study its algorithmic ideas operation mode and the update formula obtained by standard algorithm, and finally optimize the RBF neural network by particle swarm algorithm. After an in-depth analysis of the particle swarm algorithm, an improved particle swarm algorithm is proposed to improve the search accuracy and capability of the algorithm by nonlinearly adjusting the inertia weights and introducing the average extreme value factor, in response to the problems of premature convergence and poor search capability that appear in the particle swarm algorithm. Through the analysis and evaluation of the interaction between industrial ecosystem and carbon emission, the main influencing factors of carbon emission are identified, and the size and magnitude of the influence of economic growth, industrial structure, energy intensity, and energy structure on carbon emission are determined; the current situation of the industrial ecological structure is evaluated, and the direction of optimization and adjustment of industrial economic structure, energy structure, and ecological structure is clarified. We construct a multidimensional multiconstraint multimodel industrial ecological structure optimization prediction model, set the development scenarios of economy and society, and optimize the prediction of low-carbon industrial ecological structure in forest areas; based on the simulation analysis of the prediction results, we propose the direction of industrial ecological structure adjustment and the path of industrial ecological system construction.
Highlights
We study the radial neural network algorithm for low-carbon circular economy in forest area, design a coupled development evaluation model, study its algorithmic ideas operation mode and the update formula obtained by standard algorithm, and optimize the RBF neural network by particle swarm algorithm
We construct a multidimensional multiconstraint multimodel industrial ecological structure optimization prediction model, set the development scenarios of economy and society, and optimize the prediction of low-carbon industrial ecological structure in forest areas; based on the simulation analysis of the prediction results, we propose the direction of industrial ecological structure adjustment and the path of industrial ecological system construction
Since the carbon emission industrial ecosystem is an artificial ecosystem dominated by human activities, it has dynamic characteristics; that is, its ecosystem equilibrium state will change with the development of the economy and society
Summary
End of data Data ecological structure. e extraction, processing, and supply of fossil energy, raw materials, and food are the producers; the use and utilization of fossil energy, raw materials, and food are the consumers; the waste treatment system and ecological support system are the decomposers. The carbon emission industrial ecosystem is not a natural ecosystem, but an artificial ecosystem is dominated by human activities. Erefore, the analysis of the carbon emission status of the carbon emission industry ecosystem should be analysed under the general framework of the social-economic-natural composite ecosystem in the forest area. Since the carbon emission industrial ecosystem is an artificial ecosystem dominated by human activities, it has dynamic characteristics; that is, its ecosystem equilibrium state will change with the development of the economy and society. It is due to the continuous increase in the intensity of human activities, especially in China, the fossil energy-based energy structure, and the rough and unreasonable industrial structure, coupled with the serious destruction of the natural ecological environment, causing a serious imbalance of the carbon emission industrial ecosystem in forest areas. It is due to the continuous increase in the intensity of human activities, especially in China, the fossil energy-based energy structure, and the rough and unreasonable industrial structure, coupled with the serious destruction of the natural ecological environment, causing a serious imbalance of the carbon emission industrial ecosystem in forest areas. erefore, considering the dynamic characteristics of the carbon emission industrial ecosystem, how to ensure economic growth while effectively controlling carbon emission is a topic that must be solved in front of us
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