图书馆阅读需求资源利用率优化管理仿真

摘要

This paper proposes an optimization and management method for resource utilization of network reading demand based on improved particle swarm optimization and ant colony.Firstly,the resources of reading demands are classified and decision rules are got through the calculation of C4.5 decision tree algorithm,and then the length and accuracy and coverage rate of decision rules are calculated.The improved particle swarm optimization algorithm and ant colony algorithm are used to optimize and manage utilization of network reading demand resources and the optimal resource list is obtained.Thus,the optimization and management for resource utilization of network reading demands are completed.Simulation results show that this method can improve the utilization of reading resources and evaluate the reading resources effectively.%对图书馆阅读需求资源的优化管理,能够有效提高阅读资源的利用率.对阅读资源利用率的优化管理,需要首先对决策规则的准确率和覆盖率进行计算,获得优选的资源列表,完成资源利用率的优化管理.传统方法先对图书馆资源进行分类,降低资源融合问题的规模,但忽略了获得优选的资源列表,导致资源管理精度偏低.提出基于改进粒子群与蚁群的网络阅读需求资源利用率优化管理方法.首先对阅读需求资源进行分类,通过对C4.5决策树算法进行计算得出决策规则,并对决策规则的长度以及准确率和覆盖率进行计算,以资源分类为基础利用改进粒子群与蚁群算法对网络阅读需求资源进行利用率优化管理,得出优选的资源列表,完成网络阅读需求资源利用率优化管理.实验结果表明,该方法能提高了阅读资源的利用率,并对阅读资源进行有效地评价.