Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence

Released on by Ashutosh Kumar Dubey
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  • Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence Book Detail

  • Author : Ashutosh Kumar Dubey
  • Release Date : 2022-11-11
  • Publisher : Elsevier
  • Genre : Science
  • Pages : 500
  • ISBN 13 : 0323997155
  • File Size : 55,55 MB
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Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence by Ashutosh Kumar Dubey PDF Summary

Book Description: Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence covers computer-aided artificial intelligence and machine learning technologies as related to the impacts of climate change and its potential to prevent/remediate the effects. As such, different types of algorithms, mathematical relations and software models may help us to understand our current reality, predict future weather events and create new products and services to minimize human impact, chances of improving and saving lives and creating a healthier world. This book covers different types of tools for the prediction of climate change and alternative systems which can reduce the levels of threats observed by climate change scientists. Moreover, the book will help to achieve at least one of 17 sustainable development goals i.e., climate action. - Includes case studies on the application of AI and machine learning for monitoring climate change effects and management - Features applications of software and algorithms for modeling and forecasting climate change - Shows how real-time monitoring of specific factors (temperature, level of greenhouse gases, rain fall patterns, etc.) are responsible for climate change and possible mitigation efforts to achieve environmental sustainability

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Visualization for Artificial Intelligence

Visualization for Artificial Intelligence

File Size : 93,93 MB
Total View : 4460 Views
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This book explores how visualization provides an effective way of improving not only the interpretability but also the generalization capabilities of machine le