Abstract
In this paper, the neural network structure, process flow, and error transmit are analyzed and the land reclamation suitability evaluation model based on BP neural network is built. The input layer was configured 7 according to soil parameters, the output layer was configured 4 according to soil degrees, and the hidden layer was configured 9 according to experience. The network was configured as 7-9-4 network structure and trained, tested, and validated in Levenberg-Marquardt algorithm. Experiments show that the soil degree recognized by BP neural network was equated with the actual soil degree. It proves the feasibility of BP neural network in land reclamation of transmission and transformation.
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Wu, X., Ming, HT., Qin, XH., Zhu, WJ. (2014). Research on Transmission and Transformation Land Reclamation Based on BP Neural Network. In: Patnaik, S., Li, X. (eds) Proceedings of International Conference on Soft Computing Techniques and Engineering Application. Advances in Intelligent Systems and Computing, vol 250. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1695-7_33
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DOI: https://doi.org/10.1007/978-81-322-1695-7_33
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