New fuzzy neural network–Markov model and application in mid- to long-term runoff forecast
| العنوان: | New fuzzy neural network–Markov model and application in mid- to long-term runoff forecast |
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| المؤلفون: | Biao Shi, Chang Hua Hu, Xin Hua Yu, Xiao Xiang Hu |
| المصدر: | Hydrological Sciences Journal. 61:1157-1169 |
| بيانات النشر: | Informa UK Limited, 2016. |
| سنة النشر: | 2016 |
| مصطلحات موضوعية: | 010504 meteorology & atmospheric sciences, Markov chain, Artificial neural network, Computer science, Stochastic process, Generalization, 0208 environmental biotechnology, 02 engineering and technology, Markov model, computer.software_genre, 01 natural sciences, Hybrid algorithm, 020801 environmental engineering, Convergence (routing), Data mining, computer, Predictive modelling, 0105 earth and related environmental sciences, Water Science and Technology |
| الوصف: | In this paper, a mid- to long-term runoff forecast model is developed using an ideal point fuzzy neural network–Markov (NFNN-MKV) hybrid algorithm to improve the forecasting precision. Combining the advantages of the new fuzzy neural network and the Markov prediction model, this model can solve the problem of stationary or volatile strong random processes. Defined error statistics algorithms are used to evaluate the performance of models. A runoff prediction for the Si Quan Reservoir is made by utilizing the modelling method and the historical runoff data, with a comprehensive consideration of various runoff-impacting factors such as rainfall. Compared with the traditional fuzzy neural networks and Markov prediction models, the results show that the NFNN-MKV hybrid algorithm has good performance in faster convergence, better forecasting accuracy and significant improvement of neural network generalization. The absolute percentage error of the NFNN-MKV hybrid algorithm is less than 7.0%, MSE is les... |
| تدمد: | 2150-3435 0262-6667 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::2ba4acb81f374520c5d9aa990866901f https://doi.org/10.1080/02626667.2014.986486 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi...........2ba4acb81f374520c5d9aa990866901f |
| قاعدة البيانات: | OpenAIRE |
PDF full text from Publisher | تدمد: | 21503435 02626667 |
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