Application of An Improved Wavelet Neural Network Based on PSO Algorithm in Acoustic Logging Data Processing

被引：0
|
作者：
Zhang Wei [1 ]
Shi Yibing [1 ]
Lu Tao [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu 610054, Peoples R China
来源：
PROCEEDINGS OF THE SECOND INTERNATIONAL SYMPOSIUM ON TEST AUTOMATION & INSTRUMENTATION, VOLS 1-2 | 2008年
关键词：
acoustic logging data; wavelet networks; particle swarm optimization algorithm; data compression;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
With the development of acoustic imaging well logging technology, more and more logging data must be transferred to the surface, but the present transmission technique in the logging system can not meet the demand. A large of logging data must be compressed in downhole firstly, then be transmitted up to surface system. So an efficient data compression algorithm is demanded imminently. In this paper, a compression algorithm based on improved wavelet neural network with PSO (particle swarm optimization) algorithm for acoustic waveform data is presented. The experiment shows that the algorithm has fast network convergent velocity and high compression ratio. It can meet the need of the real-time acoustic logging data processing.
引用
收藏
页码：890 / 894
页数：5
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