The ant colony optimization algorithm (ACA) has the powerful ability of searching the global optimal solution, and back propagation (BP) algorithm has the feature of rapid convergence on the local optima. The proper hybrid of the two algorithms (ACA-BP) may accelerate the evolving speed of neural networks and improve the forecasting precision of the neural networks. The ACA-BP scheme adopts ACA to search the optimal combination of weights in the solution space, and then uses BP algorithm to obtain the accurate optimal solution quickly. The neural network structure used in this paper has the distinction of being determined by Optimal Brain Surgery. The ACA-BP and BP algorithms were applied to predict bottom hole pressure in underbalanced drilling. Experiment results show that the proposed ACA-BP scheme is more efficient and effective than the BP algorithm.
کلید واژگان :ANN, ant colony algorithm, back propagation, bottom hole circulating pressure, two-phase fluid, underbalanced drilling
ارزش ریالی : 600000 ریال
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