The Algorithm Study of Sensor Compensation in MWD Instrument Based on Genetic Elman Neural Network

In order to improve the measurement precision and stability of MWD Instrument, we create Elman neural network model and utilize self-adaptive genetic algorithm to optimize weights threshold value of the right of Elman network, which overcomes the disadvantages of traditional method, such as training for a long time, easy to fall into local optimal solution. Simulation results show that the error accuracy increases 3 orders of magnitude, compared with Elman network, the compensation effect is very stable.