predicting navigation satellite clock bias using agenetic wavelet neural network
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摘要: 针对卫星钟差难以用精确模型来进行预报问题首先通过遗传算法优化适合非线性时间序列预报的小波神经网络的网络参数得到预报性能更好的遗传小波神经网络gwnn 然后根据钟差数据的特点对钟差进行预处理建立了一种能够高精度近实时预报钟差的gwnn钟差预报算法 使用gps卫星钟差进行一天内的预报实验证明了本方法的有效性 结果表明通过本方法得到的预报钟差较igs超快预报钟差在精度上有了较大的改善Abstract: aiming to solve satellite clock bias scbthat is difficult to formulate for predictionthispaper emplo ys a genetic al gorithm to optimize the network parameters of a wavelet neural networksuitable for prediction nonlinear time series．firstagenetic wavelet neural network gwnnwithbetter prediction performance was obtained．secondl ythe scb values were pre processed based ontheir characteristics and a gwnn model was established to accuratel y predict scb in near real time．finall ythe paper carries out scb prediction tests within one day using the scb data from gps satellites to validiate the proposed model．the results show that the proposed prediction model outper－forms igs ultra－ra pid predicted scb products
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Keywords:
- atellite clock bias /
- genetic al gorithm /
- wavelet neural network /
- prediction
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