References: [1] Ding, S., Su, C., and Yu, J. (2011). An optimizing BP neural network algorithm based on genetic algorithm. Artificial Intelligence Review, 36 (2), 153-162. [2] Zhang, L., Wu, K., Zhong, Y., et al. (2008). A new sub-pixel mapping algorithm based on a BP neural network with an observation model. Neurocomputing, 71 (10), 2046-2054. [3] Yu, F., and Xu, X. (2014). A short-term load forecasting model of natural gas based on optimized genetic algorithm and improved BP neural network. Applied Energy, 134, 102-113. [4] Chau, K. W. (2007). Application of a PSO-based neural network in analysis of outcomes of construction claims. Automation in construction, 16 (5), 642-646. [5] Ren, C., An, N., Wang, J., et al. (2014). Optimal parameters selection for BP neural network based on particle swarm optimization: A case study of wind speed forecasting. Knowledge-Based Systems, 2014, 56, 226-239. [6] Shen, C., Wang, L., and Li, Q. (2007). Optimization of injection molding process parameters using combination of artificial neural network and genetic algorithm method. Journal of Materials Processing Technology, 183 (2), 412-418. [7] Xia, C., Guo, C., and Shi, T. (2010). A neural-network-identifier and fuzzy-controller-based algorithm for dynamic decoupling control of permanent-magnet spherical motor. IEEE Transactions on industrial electronics, 57 (8), 2868-2878. [8] Sedki, A., Ouazar, D., and El Mazoudi, E. (2009). Evolving neural network using real coded genetic algorithm for daily rainfall– runoff forecasting. Expert Systems with Applications, 36 (3), 4523-4527. [9] Li, H. Z., Guo, S., Li, C. J., et al. (2013). A hybrid annual power load forecasting model based on generalized regression neural network with fruit fly optimization algorithm. Knowledge-Based Systems, 37, 378-387. [10] Huang, J., Luo, H., Wang, H., et al. (2009). Prediction of time sequence based on GA-BP neural net. Journal of University of Electronic Science and Technology of China, 5, 029. |