Results 241 to 250 of about 779,800 (277)
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2018
Artificial neural networks are perhaps the most common method amongst intelligent methods in geophysics and are becoming increasingly popular. Because they are universal approximations, these tools can approximate any continuous function with any arbitrary precision.
Alireza Hajian, Peter Styles
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Artificial neural networks are perhaps the most common method amongst intelligent methods in geophysics and are becoming increasingly popular. Because they are universal approximations, these tools can approximate any continuous function with any arbitrary precision.
Alireza Hajian, Peter Styles
openaire +2 more sources
The paper “Artificial Neural Networks: An Overview” explains how ANNs work by mimicking the human brain. It covers their basic structure—input, hidden, and output layers—and describes types like Feed Forward, Recurrent, and Convolutional Neural Networks. The paper also shows how ANNs are used in machine learning, data security, and pattern recognition.
Ajay K B, Teja A
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Ajay K B, Teja A
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2016
The present investigation tries to achieve the objective of representation of climatic vulnerability to the hydropower plants by the adaptation of a two step approach. In the first step the Multi Criteria Decision Making was used to identify the priority value of the priority parameters.
Mrinmoy Majumder, Apu K. Saha
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The present investigation tries to achieve the objective of representation of climatic vulnerability to the hydropower plants by the adaptation of a two step approach. In the first step the Multi Criteria Decision Making was used to identify the priority value of the priority parameters.
Mrinmoy Majumder, Apu K. Saha
openaire +1 more source
1998
While the learning systems based on artificial neural networks became popular only in the early eighties, they have a much longer research history and some of these methods have evolved towards quite mature techniques.
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While the learning systems based on artificial neural networks became popular only in the early eighties, they have a much longer research history and some of these methods have evolved towards quite mature techniques.
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Deep neural networks for the evaluation and design of photonic devices
Nature Reviews Materials, 2020Jiaqi Jiang +2 more
exaly
Artificial Neural Networks-Based Machine Learning for Wireless Networks: A Tutorial
IEEE Communications Surveys and Tutorials, 2019Mingzhe Chen +2 more
exaly