前向模糊推理的菇房异常环境预警系统

Mushroom abnormal environmental early warning system based on forward fuzzy reasoning

为了提高食用菌菇房环境监测水平,降低菇房异常环境发生造成的食用菌生产损失,抛弃了常用的阈值方法判断菇房异常环境,提出一种基于前向模糊推理的菇房异常环境推理方法,该方法首先通过物联网技术对菇房环境进行实时数据采集,通过数据预处理方法去除原始感知数据中的异常值,采用加权平均法的数据融合技术融合同一菇房内多传感器数据,通过前向模糊推理方法对菇房异常环境进行推理。最终设计和实现了菇房异常环境预警系统,该系统采用B/S的系统架构,可方便用户随时随地查看菇房环境情况,接收异常环境预警信息。系统在经过一段时间的测试运行后,证明系统采用前向模糊推理方法可准确推断出菇房异常环境的发生,同时有效减少误发预警信息次数。

In order to improve level of edible mushroom room environment monitoring, reduce edible fungus production loss caused by mushroom house abnormal circumstances ,abandon commonly used threshold method to judge mushroom house abnormal environment, put forward a kind of mushroom room abnormal environmental reasoning method based on forward fuzzy reasoning, through the lnternet of things （loT） technology, mushroom house environment real-time data acquisition is carried out, and through data preproeessing method, remove the outliers in original sensing data, data fusion technology of weighted average method is used to fuse muhisensor data inside the same mushroom room, through forward fuzzy reasoning method, reasoning of mushroom abnormal environment is carried out. Design and implement mushroom house abnormal environmental early warning system, the system adopts B/S system architectme, which is convenient for users to view mushroom room environment anywhere, receive abnormal environment early warning information. After test operation for a period of time, it is proved that the system uses forward fuzzy reasoning method can accurately infer occurrence of abnormal environment of mushroom house,at the same time effectively reduce false alert information.