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Titlebook: Impact of Climate Change on Hydro-Energy Potential; A MCDM and Neural Ne Mrinmoy Majumder,Apu K. Saha Book 2016 The Author(s) 2016 Artifici

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樓主: Enclosure
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發(fā)表于 2025-3-23 09:42:13 | 只看該作者
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發(fā)表于 2025-3-23 15:33:58 | 只看該作者
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發(fā)表于 2025-3-23 20:50:50 | 只看該作者
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發(fā)表于 2025-3-24 00:39:53 | 只看該作者
Methodology, Networks are used to solve the problem in an objective and cognitive manner. Among these Group Method of Data Handling was found to be widely popular in solving problems from different sectors. In neural networks four parameters are required to be estimated viz, Activation functions between input a
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發(fā)表于 2025-3-24 02:28:25 | 只看該作者
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發(fā)表于 2025-3-24 07:04:44 | 只看該作者
Conclusions,dered in the study. The model which have 9 inputs and the data of output parameters transformed by Arc Tangent function was found to be a better alternative to predict performance efficiency of hydropower plants among the 28 different configurations developed for the present study. The model accurac
17#
發(fā)表于 2025-3-24 11:39:13 | 只看該作者
Book 2016ision making and neural network are used to predict the impact of the change cognitively by an index. The results from the study show that the hydro-energy potential of the Asian region is mostly vulnerable with respect to other regions of the World. The model results also encourage further applicat
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發(fā)表于 2025-3-24 16:08:23 | 只看該作者
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發(fā)表于 2025-3-24 22:40:21 | 只看該作者
Artificial Neural Networks,ions of the model was developed. The better model was selected with the help of Root Mean Square Error and Correlation Coefficient. The chosen model was used to find the climatic vulnerability of six different hydropower plants from North and South America, Asia, Europe, Africa and Oceania.
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發(fā)表于 2025-3-25 01:48:57 | 只看該作者
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