Abstract: The detection of fire is complex and significant in its early age.Aiming at the shortcomings of traditional fire detection method，a new intelligent fire detection system based on Weighted Support Vector Regression（WSVR） is presented.WSVR algorithm overcomes the disadvantages of neural network such as over learning etc.，and the problem of no considering the importance of each sample in the standard SVR.The experiment results show that the intelligent fire detection system is surperior to the detection systems based on neural network and the standard SVR，it has notable detection effect and well application foreground.

Key words: fire detection, Weighted Support Vector Regression（WSVR）, parameter optimization, neural network

摘要： 火灾的早期探测是较为复杂且具有重要意义的研究课题。针对传统火灾探测方法存在的不足，提出了一种基于加权支持向量回归的火灾智能探测系统，加权支持向量回归算法克服了神经网络过学习等不足，及标准支持向量回归中未考虑各样本重要性的差异问题，实验结果表明此火灾智能探测系统优于基于神经网络和标准支持向量回归的探测系统，探测效果显著，具有良好的应用前景。

关键词: 火灾探测, 加权支持向量回归, 参数优化, 神经网络