基于改进D-S证据理论的室内环境控制决策系统

针对室内环境因子多且相互作用关系复杂，影响室内环境舒适度的控制精准决策，设计了一种基于改进D-S证据理论的室内环境控制决策系统。首先采用箱线图法和均值替代法检测修复异常采集数据，然后利用距离自适应加权融合算法实现同类传感器数据一级融合，最后利用改进D-S证据理论算法，实现全局融合决策。实验结果表明，改进D-S证据理论算法能够有效避免冲突证据带来的融合决策误差，系统可以实现室内环境控制的精准决策，融合决策精度高，具有一定的推广应用价值。

An indoor environment control decision-making system based on improved D-S evidence theory

In order to solve the problem that there are many indoor environment factors and the interaction relationship is complex, which affects the precise decision-making of indoor environment comfort, an indoor environment control decision-making system based on improved D-S evidence theory is designed. Firstly, the boxplot method and the mean substitution method are used to detect and repair the abnormal collected data. Secondly, the distance adaptive weighted fusion algorithm is used to realize the first level fusion of similar sensor data. Finally, the improved D-S evidence theory algorithm is adopted to realize the global fusion decision. The experimental results show that the improved D-S evidence theory algorithm can effectively avoid the fusion decision error caused by the conflict evidence. The system can realize the precise decision of indoor environment control and the fusion decision accuracy is high, which has a certain promotion and application value.