| References: [1] Yi, H. E., Chen, J. (2015). Research on line loss data pretreatment in distribution network based on GMDH algorithm. Dianli Xitong Baohu Yu Kongzhi/Power System Protection & Control, 43(9), 42-46.
[2] Kasaeian, A., Ghalamchi, M., Ahmadi, M. H., et al. (2017). GMDH algorithm for modeling the outlet temperatures of a solar chimney based on the ambient temperature. Mechanics & Industry, 18(2), 216.
[3] Yin, W., Hu, W., Hui, F., et al. (2015). Inverse Determination of Material Parameters Based on Decoupled GMDH Algorithm. China Mechanical Engineering, 26(9), 1215-1221.
[4] Chang, F., Hwang, Y. (2015). A self-organization algorithm for real-time flood forecast. Hydrological Processes, 13 (2), 123-138.
[5] Antanasijevi, D., Antanasijevi, J., Pocajt, V., et al. (2016). A GMDH-type neural network with multi-filter feature selection for the prediction of transition temperatures of bent-core liquid crystals. Rsc Advances, 6(102), 99676-99684.
[6] Osanaiye, O., Cai, H., Choo, K. K. R., et al. (2016). Ensemble-based multi-filter feature selection method for DDoS detection in cloud computing. Eurasip Journal on Wireless Communications & Networking, 2016 (1), 130.
[7] Inbarani, H. H., Bagyamathi, M., Azar, A. T. (2015). A novel hybrid feature selection method based on rough set and improved harmony search. Neural Computing & Applications, 26(8), 1859-1880.
[8] Parsaie, A., Haghiabi, A. H. (2015). Predicting the longitudinal dispersion coefficient by radial basis function neural network. Modeling Earth Systems & Environment, 1(4), 1-8.
[9] Najafzadeh, M. (2015). Neuro-fuzzy GMDH systems based evolutionary algorithms to predict scour pile groups in clear water conditions. Ocean Engineering, 99, 85-94.
[10] Bodyanskiy, Y., Tyshchenko, O., Kopaliani, D. (2015). A hybrid cascade neural network with an optimized pool in each cascade. Soft Computing, 19(12), 3445-3454. |
