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An efficient and optimal clustering algorithm for real-time forest fire prediction with

机译:一种高效,最优的聚类实时森林火灾预测算法

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Grouping of forest fire images into meaningful categories to reveal useful information is a challenging task. In order to overcome this challenge, data mining techniques can be used with wireless sensor network which can detect and forecast forest fire more promptly than the satellite-based detection approach. This paper proposes an efficient image clustering algorithm using real time data for predicting of the occurrence of forest fire, with a new mechanism for secure information transmission in wireless sensor networks by minimizing the threat attacks caused by malicious nodes in wireless sensor networks.
机译:将森林火灾图像分组为有意义的类别以揭示有用的信息是一项艰巨的任务。为了克服这一挑战,数据挖掘技术可以与无线传感器网络一起使用,与基于卫星的检测方法相比,无线传感器网络可以更迅速地检测和预测森林火灾。本文提出了一种有效的图像聚类算法,该算法利用实时数据来预测森林火灾的发生,并提出了一种新的机制,可以通过最大程度地减少无线传感器网络中恶意节点造成的威胁攻击,来确保无线传感器网络中信息的安全传输。

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