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Machine Learning for Intelligent Decision Science

Overview of attention for book
Cover of 'Machine Learning for Intelligent Decision Science'

Table of Contents

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    Book Overview
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    Chapter 1 Development of Different Machine Learning Ensemble Classifier for Gully Erosion Susceptibility in Gandheswari Watershed of West Bengal, India
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    Chapter 2 Classification of ECG Heartbeat Using Deep Convolutional Neural Network
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    Chapter 3 Breast Cancer Identification and Diagnosis Techniques
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    Chapter 4 Energy-Efficient Resource Allocation in Data Centers Using a Hybrid Evolutionary Algorithm
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    Chapter 5 Root-Cause Analysis Using Ensemble Model for Intelligent Decision-Making
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    Chapter 6 Spider Monkey Optimization Algorithm in Data Science: A Quantifiable Objective Study
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    Chapter 7 Multi-agent-Based Systems in Machine Learning and Its Practical Case Studies
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    Chapter 8 Computer Vision and Machine Learning Approach for Malaria Diagnosis in Thin Blood Smears from Microscopic Blood Images
Attention for Chapter 4: Energy-Efficient Resource Allocation in Data Centers Using a Hybrid Evolutionary Algorithm
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Citations

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4 Mendeley
Summary Dimensions citations
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Chapter title
Energy-Efficient Resource Allocation in Data Centers Using a Hybrid Evolutionary Algorithm
Chapter number 4
Book title
Machine Learning for Intelligent Decision Science
Published by
Springer, Singapore, January 2020
DOI 10.1007/978-981-15-3689-2_4
Book ISBNs
978-9-81-153688-5, 978-9-81-153689-2
Authors

V. Dinesh Reddy, G. R. Gangadharan, G. S. V. R. K. Rao, Marco Aiello, Reddy, V. Dinesh, Gangadharan, G. R., Rao, G. S. V. R. K., Aiello, Marco

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 50%
Student > Postgraduate 1 25%
Unknown 1 25%
Readers by discipline Count As %
Unspecified 2 50%
Unknown 2 50%

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