Sensor Compensation Based on Adaptive Ant Colony Neural Networks

Xiu Fang Wang; Chong Chong Liang; Jian Guo Jiang; Li Li Ju

doi:10.4028/www.scientific.net/AMR.301-303.876

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 301-303Sensor Compensation Based on Adaptive Ant Colony...

Sensor Compensation Based on Adaptive Ant Colony Neural Networks

Abstract:

In order to improve work stability and measurement accuracy of drilling inclinometer, and overcome the poor stability of Elman networks and lower compensation precision of genetic Elman neural networks, we combined ant colony algorithm and neural networks, using the Adaptive Ant Colony Algorithm that its pheromone evaporation factorand pheromone update strategy adjust adaptively to optimize Elman neural network weights and thresholds, and applied it to drilling inclinometer sensor compensation. Simulation results show that the compensation effect of adaptive ant colony Elman neural networks is better than that of Elman networks and genetic Elman networks, the compensation accuracy is 10^-8.

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Periodical:

Advanced Materials Research (Volumes 301-303)

Pages:

876-880

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.301-303.876

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Online since:

July 2011

Authors:

Xiu Fang Wang, Chong Chong Liang, Jian Guo Jiang, Li Li Ju

Keywords:

Adaptive Ant Colony Algorithm, Drilling Inclinometer, Elman Network, Sensor Compensation

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