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Economical zigbee underground coal mining localization system with RSSI Bayesian classification fuzzy network algorithm

机译:RSSI贝叶斯分类模糊网络算法经济Zigbee地下煤矿本地化系统

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Mining safety issue has always been an important part related to this industry.From simple radio speaker to wireless mobile device, artificial intelligent enhance localization technology with more efficient solution.Bayes theory with associated algorithms has been applied in previous research from and as well as fuzzy network, K-nn(k nearest neighborhood),ML(maxim likelihood) estimation methods have been unitized to catch better solutions.In this paper, a IEEE 802.15.4 standard device with RSSI(received signal strength indicator) measurement combine Bayesian with RSS distribution model builds the main kernel with after fuzzy network classifier, which reach the accuracy of 2meters(maxim) for over 90% availably and precision.
机译:采矿安全问题一直是与该行业有关的重要组成部分。通过简单的无线电扬声器到无线移动设备,人工智能增强本地化技术,具有更高效的解决方案。与相关算法的比喻理论已应用于以前的研究,以及模糊网络,K-NN(K最近邻域),ML(Maxim似然)估计方法已被联合起来以捕获更好的解决方案。在本文中,具有RSSI(接收信号强度指示器)测量的IEEE 802.15.4标准设备与RSS相结合分配模型在模糊网络分类器之后建立主内核,该分类为2米(Maxim)的准确性,可用和精度超过90%。

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