The Prediction of the Error Rate in the Data Transmission Based on Improved Chaotic Optimization Neural Network

Abstract:

As the slurry continuous wave changes according to the measurement of drilling (MWD) date, the precision of error rate prediction is low and the process of transferring data will be affected by signals. Based on the BP neural networks extensive mapping ability and chaos optimization algorithms global convergent ability, we structure a kind of improved chaos optimization of BP neural network algorithm. This algorithm can avoid several problems, such as the convergent speed of BP neural network is slow and the BP neural network is easy to sink into local minimum. With the powerful ability of generalization and prediction, this kind of algorithm can also be used to predict the data transmission error rate in slurry continuous wave. Under the condition of small samples, we create a model of data transmission in slurry continuous wave, which is based on improved chaos optimization of BP neural network. Simulate experiment has tested this algorithms feasibility and effectiveness

• Periodical: Applied Mechanics and Materials (Volumes 380-384)
• Pages: 1829-1833
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.380-384.1829
• Online since: August 2013
• Authors: Xin Ping Liu, Jun Peng Xu, Hui Liu, Xiao Ling Wu
• Keywords: Improved Chaotic Optimization Neural Network, Optimal Design Measurement while Drilling, Precision of Error Rate Prediction

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