Cognitive Data Models for Sustainable Environment

This PDF book is become immediate popular in Computers genre. Cognitive Data Models for Sustainable Environment is written by famous author Siddhartha Bhattacharyya and Ready to Download in ePUB, PDF or Kindle formats. Released by Academic Press in 2021-09-19. Click Download Book button to get book file and read directly from your devices. Here is a quick description and cover image of Cognitive Data Models for Sustainable Environment book.

Cognitive Data Models for Sustainable Environment
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Publisher : Academic Press
Release Date :
ISBN : 9780128240397
Pages : 316 pages
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Cognitive Data Models for Sustainable Environment by Siddhartha Bhattacharyya Book PDF Summary

Cognitive Models for Sustainable Environment reviews the fundamental concepts of gathering, processing and analyzing data from batch processes, along with a review of intelligent and cognitive tools that can be used. The book is centered on evolving novel intelligent/cognitive models and algorithms to develop sustainable solutions for the mitigation of environmental pollution. It unveils intelligent and cognitive models to address issues related to the effective monitoring of environmental pollution and sustainable environmental design. As such, the book focuses on the overall well-being of the global environment for better sustenance and livelihood. The book covers novel cognitive models for effective environmental pollution data management at par with the standards laid down by the World Health Organization. Every chapter is supported by real-life case studies, illustrative examples and video demonstrations that enlighten readers. Explores the development and application of science, engineering and technology in achieving a sustainable lifestyle for humanity Provides tools, connections and proactive solutions to take sustainability programs to the next level Offers perspectives for design, development and commissioning of intelligent applications Provides reviews on the latest intelligent technologies and algorithms related to state-of-the-art methodologies of monitoring and mitigation of environmental pollution


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