Wireless sensor network is a typical application of wireless sensor and composed of the huge number of network nodes. It has been widely used in many fields. Neural network was introduced into the wireless sensor network, and the meta-model of neural network was constructed by the neurons with the description for wireless sensor data. A wireless sensor network of the data gathering fusion and extraction was realized based on wireless sensor neural network model and the improved traditional neural network model. Through the various application type of differences influence data output, a predicting model was established by the choice of the main factors. The experimental prototype of one region in fire was carried out based on the forecast of the existing fire data for the training sample and through the network of convergence,the probability of occurrence in a fire was forecasted. The experimental results show that it is a feasible and effective method for data prediction using the wireless sensor network based on neural network.%无线传感器网络是一种由数量庞大的网络节点形成的复杂无线网络,是无线传感器的典型应用,目前已经广泛应用在多个领域当中.将神经网络引入到无线传感器网络当中,通过神经元描述每一个无线传感器数据,构建神经网络元模型.对传统的神经网络模型进行改进,利用无线传感器的神经网络模型,实现无线传感器网络采集数据的融合与提取.通过各种应用类型的差异,选择影响数据输出结果的主要因素,建立一种能够进行预测的模型.以某个区域是否发生火灾为实验原型,对该区域的火灾发生概率进行预测,采用已有的火灾发生数据为训练样本,通过收敛的网络预测火灾发生的概率.实验结果表明,基于神经网络的无线传感器网络数据预测是一种可行、有效的方法.
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