Abstract
This paper proposes a Hopfield neural network guided evolutionary algorithm for aircraft penetration path planning. The combination of the algorithms benefits from the advantages of each and is intended to achieve a fast and adaptive path searching mechanism. The HNN works as guidance for the EA path planner by restricting the searching area around the gradient of the states of the network. Meanwhile the complex penetration factors are well integrated into the algorithm by EA so making the combined algorithm applicable to penetration path planning. Extensive simulations are conducted to demonstrate the effectiveness of the propose algorithm.
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Wang, N., Wang, L., Gu, X., Chen, J., Shen, L. (2010). Hopfield Neural Network Guided Evolutionary Algorithm for Aircraft Penetration Path Planning. In: Zeng, Z., Wang, J. (eds) Advances in Neural Network Research and Applications. Lecture Notes in Electrical Engineering, vol 67. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12990-2_27
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DOI: https://doi.org/10.1007/978-3-642-12990-2_27
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