论文部分内容阅读
针对传统瓦斯预测专家系统中知识获取的“瓶颈”问题,引入粗糙集理论,并利用粗糙集的约简方法消除知识库中冗余属性,实现了知识库的精简,有效地维护和完善了知识库的结构和性能。文章详细介绍了知识获取的过程,并以采集到的实时数据进行仿真实验,实验结果证明提高了瓦斯预测专家系统知识获取的效率。
Aiming at the bottleneck problem of knowledge acquisition in traditional gas forecasting expert system, this paper introduces rough set theory, and uses the rough set reduction method to eliminate the redundant attributes in the knowledge base, thus simplifies and effectively maintains and improves the knowledge base The structure and performance of the knowledge base. The paper introduces the process of knowledge acquisition in detail, and carries on the simulation experiment with the collected real-time data. The experimental results prove that the efficiency of knowledge acquisition of the gas prediction expert system is improved.