Abstract
In order to evaluate the comprehensive benefits of forest ecological economy, a model based on discrete particle swarm optimization is proposed. First of all, the discrete particle swarm optimization algorithm is defined and introduced into the evaluation parameters of forest ecological and economic benefits for internal processing, and the evaluation model of forest ecological and economic benefits is constructed. Optimize the system evaluation of the model, continuously develop the internal model structure adjustment operation, and finally obtain the experimental data needed by the system. The experimental results show that the model based on the discrete particle swarm optimization algorithm has better convergence, better optimization and robustness, and has higher practical application value. • A discrete optimization model is proposed to evaluate the forest ecological economy benefits. • Optimize the system evaluation and develop internal model structure, obtain the experimental data. • The total amount of carbon emissions is sequenced. • The dominant carbon molecule parameter set is constructed. • The final data is continuously collected to obtain the complete result data.
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