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基于RBF神经网络的功率预测

于 2022-04-17 发布 文件大小:7.80 kB
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神经网络的并行结构和并行处理机制,使得信息处理速度快,能够满足信息的实时处理要求。将神经网络用于多传感器数据融合技术,首先要根据系统的要求以及传感器的特点选择合适的神经网络模型(常见的神经网络模型有BP网络、Hop-field网络、Elman网络、RBF网络等),然后再根据已有的多传感器数据和系统的融合知识采用一定的学习方法,对建立的神经网络系统进行离线学习,确定网络的联接权值和联接结构,最后把得到的网络用于实际的数据融合当中。

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