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Neural Network Prediction of Signal Strength for Irregular Indoor Environments

机译:不规则室内环境的信号强度神经网络预测

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摘要

A neural-network based approach for modelling propagation inside complex indoor environments is presented. Selection of the neural network model, initialization, and training and performance evaluation are studied in details. Furthermore, in order to determine optimal access point arrangement the neural network propagation model is merged with the particle swarm optimization method. In the case of simple indoor environments the developed propagation model is equally accurate as the deterministic methods, while in the case of complex environments the proposed method shows superior properties. Finally, the calculated results were tested in direct comparison with the measurements for both simple and complex indoor environments.
机译:提出了一种基于神经网络的复杂室内环境传播建模方法。详细研究了神经网络模型的选择,初始化以及训练和性能评估。此外,为了确定最佳的接入点布置,将神经网络传播模型与粒子群优化方法合并。在简单的室内环境中,开发的传播模型与确定性方法一样准确,而在复杂的环境中,建议的方法显示出优越的性能。最后,在简单和复杂的室内环境下,将计算结果与测量结果进行直接比较。

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