摘要： 建立一种基于改进PSO算法的随机投入产出模型，在随机变量分别服从正态分布和指数分布时比较其优化结果，利用改进粒子群算法和标准粒子群算法对模型进行实例求解。仿真实验结果表明，考虑随机变量服从指数分布更符合实际经济运行状况，且计算得到的各行业产出大于随机变量服从正态分布时的情况。
关键词:
投入产出,
正态分布,
指数分布,
改进PSO算法,
随机变量
Abstract: A stochastic input-output model is established by considering the direct consumption coefficient matrix and ultimate demands as stochastic variables. The stochastic variables are assumed to satisfy normal distribution and exponential distribution respectively to compare the optimization results. The improved Particle Swarm Optimization(PSO) algorithm and the standard one are used to complete an example respectively. Calculation results demonstrate the stochastic variables satisfying exponential distribution is more appropriate to the actual economic activities, and the outputs under exponential distribution are larger than that under normal distribution.
Key words:
input-output,
normal distribution,
exponential distribution,
improved Particle Swarm Optimization(PSO) algorithm,
stochastic variables
中图分类号:
王峰, 李树荣. 基于改进PSO算法的随机投入产出模型?[J]. 计算机工程, 2011, 37(9): 29-31,37.
WANG Feng, LI Shu-Rong. Stochastic Input-Output Model Based on Improved PSO Algorithm[J]. Computer Engineering, 2011, 37(9): 29-31,37.