【摘要】 为提高火灾报警系统的正确率,提出一种多传感器火灾探测系统的数据融合算法。采用模糊神经网络建立了数据融合决策模型,并用改进的BP算法对网络进行学习和训练,自动调整模糊系统参数。根据国家标准试验火数据进行网络训练,系统误差小于试验火标准误差要求,表明了算法的有效性和可行性。与其他方法探测结果进行比较,体现了所设计的算法的优越性。更多还原

【Abstract】 In order to improve the veracity of fire alarming system,a data fusion algorithm used multi-sensor fire detect system is proposed. The agorithm applies fuzzy neural network to set up data fusion model,and uses an improved BP algorithm to study and train network,which makes the model can adjust fuzzy system parameter automatically.The network is trained using country testing fire data,system error is less than standard error,which shows the validity and feasibility of the algorithm.And it also shows the advantages of this algorithm when compares with other method.更多还原