基于模糊聚类和模糊积分的森林蓄积量预测模型

Prediction Model of Fuzzy Clustering and Fuzzy Integral Based on Forest Stock Volume

以塞罕坝机械林场的资料为基本数据源,通过模糊聚类分析蓄积估测的重要因子,利用区间值带符号模糊测度的Choquet模糊积分作为组合算子,给出一种基于模糊积分的非线性组合预测森林蓄积量的模型,采用粒子群算法和遗传算法求解该模型,结果说明了粒子群算法在求解该模型时,比遗传算法的收敛速度较快,而且能搜索到比遗传算法更优的解,估测的森林蓄积量与真实值更贴近。

This paper in Saihanba mechanical forest farm data as basic data source, through the important factor of fuzzy clustering analysis of stock estimation, Vsing the interval-valued fuzzy measure with the symbol as a combination operator of Choquet fuzzy integral, gives a forecast of forest volume model based on nonlinear combination of fuzzy integral is solved by particle swarm algorithm and genetic algorithm for the model, the results showed that not only the algorithm for solving the model better than the genetic algorithm has a faster convergence speed, but also can search the better than the genetic algorithm solution, estimating forest volume and close to the true value.