Temperature forecasting using artificial neutral networks (ANN)
@article{Kumar2013TemperatureFU,
title={Temperature forecasting using artificial neutral networks (ANN)},
author={Pankaj Kumar and P. S. Kashyap and Javed},
journal={Journal of Hill Agriculture},
year={2013},
volume={4},
pages={110-112}
}The objective of this paper is to develop an artificial neural network (ANN) model which can be used to predict weekly mean temperatures in Pantnagar, Uttarakhand, India. In order to determine the optimal network architecture, various network architectures were designed; different training algorithms were used; the number of neuron and hidden layer and transfer functions in the hidden layer/output layer were changed. Training of the network was performed by using Levenberg–Marquardt feed…
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References
SHOWING 1-4 OF 4 REFERENCES
SOFM-MLP: a hybrid neural network for atmospheric temperature prediction
- Computer ScienceIEEE Trans. Geosci. Remote. Sens.
- 2003
A novel neural architecture that combines a self-organizing feature map (SOFM) and MLPs to realize a hybrid network named SOFM-MLP with better performance and the use of appropriate features can not only reduce the number of features drastically, but also can improve the prediction accuracy.
Short‐term flood forecasting with a neurofuzzy model
- Computer Science
- 2005
The forecasts by the neurofuzzy model at higher lead times are found to be better than those from the neural network model or the fuzzy model, implying that the neuro fuzzymodel seems to be well suited to exploit the information to model the nonlinear dynamics of the rainfall‐runoff process.