Improved fire type identification method of extreme learning machine

The invention provides an improved fire type identification method of an extreme learning machine. At first, a carbon monoxide sensor, a carbon dioxide sensor, a temperature sensor, a smoke sensor, and a current sensor acquire feature data representing different fire source performance features; in order to facilitate the later data processing and accelerate the identification speed, the acquired data is subjected to processing; and then the processed data is input into an optimized IELM network model for identification to obtain an output matrix; and at the end, the fire comburent types can be determined based on the output matrix. According to the improved fire type identification method of the extreme learning machine, the fire types can be effectively identified, the adaptability is good, the anti-interference capability is high, and the identification correct rate is high. 种改进的极限学习机的火灾种类识别方法，首先采用氧化碳传感器、二氧化碳传感器、温度传感器、烟雾传感器、电流传感器获取代表不同火灾源表现特性的特征数据；为了后面处理数据方便和加快识别速度，对采集的数据进行归化处理；然后将处理后的数据输入优化后的IELM网络模型进行识别，