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Applied Intelligent Decision Making in Machine Learning : Computational Intelligence in Engineering Problem Solving - Himansu Das

Applied Intelligent Decision Making in Machine Learning

By: Himansu Das (Editor), Jitendra Kumar Rout (Editor), Suresh Chandra Moharana (Editor), Nilanjan Dey (Editor)

Hardcover | 19 November 2020 | Edition Number 1

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The objective of this edited book is to share the outcomes on various research domains to develop efficient, adaptive, and intelligent models to handle the challenges related to decision making. It incorporates the advances of machine intelligent techniques such as data streaming, classification, clustering, pattern matching, feature selection, and deep learning in the decision-making process for several diversified applications such as agriculture, character recognition, landslide susceptibility, recommendation system, forecasting air quality, healthcare, exchange rate prediction, and image dehazing. It also provides a premier interdisciplinary platform for scientists, researchers, practitioners, and educators to share their thoughts in the context of recent innovations, trends, developments, practical challenges and advancements in the field of data mining, machine learning, soft computing, and decision science. It also focuses on the usefulness of applied intelligent techniques in decision-making process in several aspects. To address the aforesaid objectives, this edited book includes thirteen promising chapters contributed by several authors throughout the globe. The contributing authors are trying to solve the aforementioned complex problems using several intelligent machine learning techniques. This allows the researchers to understand the mechanism needed to harness on decision-making process using machine learning techniques for their own respective endeavors.

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Non-FictionEngineering & TechnologyElectronics & Communications EngineeringElectronics EngineeringAutomatic Control EngineeringEnergy Technology & EngineeringElectrical EngineeringComputing & I.T.Computer ScienceSystems Analysis & DesignEnvironmental ScienceDigital Lifestyle & Online World: Consumer & User Guides
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