منابع مشابه
Estimation of Reference Evapotranspiration Using Artificial Neural Network Models and the Hybrid Wavelet Neural Network
Estimation of evapotranspiration is essential for planning, designing and managing irrigation and drainage schemes, as well as water resources management. In this research, artificial neural networks, neural network wavelet model, multivariate regression and Hargreaves' empirical method were used to estimate reference evapotranspiration in order to determine the best model in terms of efficienc...
متن کاملA hybrid algorithm for artificial neural network training
Artificial neural network (ANN) training is one of the major challenges in using a prediction model based on ANN. Gradient based algorithms are the most frequent training algorithms with several drawbacks. The aim of this paper is to present a method for training ANN. The ability of metaheuristics and greedy gradient based algorithms are combined to obtain a hybrid improved opposition based par...
متن کاملscour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network
today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...
Incremental Convolutional Neural Network Training
Experimenting novel ideas on deep convolutional neural networks (DCNNs) with big datasets is hampered by the fact that network training requires huge computational resources in the terms of CPU and GPU power and hours. One option is to downscale the problem, e.g., less classes and less samples, but this is undesirable with DCNNs whose performance is largely data-dependent. In this work, we take...
متن کاملAccelerating Recurrent Neural Network Training
An efficient algorithm for recurrent neural network training is presented. The approach increases the training speed for tasks where a length of the input sequence may vary significantly. The proposed approach is based on the optimal batch bucketing by input sequence length and data parallelization on multiple graphical processing units. The baseline training performance without sequence bucket...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Pure and Apllied Mathematics
سال: 2017
ISSN: 1311-8080,1314-3395
DOI: 10.12732/ijpam.v115i4.22