Learning from Data for Aquatic and Geotechnical Environments

Author:   Biswa Bhattacharya
Publisher:   Taylor & Francis Ltd
ISBN:  

9780415391702


Pages:   254
Publication Date:   22 December 2005
Format:   Paperback
Availability:   In Print   Availability explained
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Learning from Data for Aquatic and Geotechnical Environments


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Overview

The book presents machine learning as an approach to building models that learn from data, and that can be used to complement the existing modelling practice in aquatic and geotechnical environments. It provides concepts of learning from data, and identifies segmentation (clustering), classification, regression and control as the learning tasks. A unified methodology based on the concepts of machine learning, information theory and statistics is presented that can be followed to build models using data as well as expert knowledge. Several machine learning methods are used to extract features to build data-driven models in geotechnics. A set of regression models are built to predict sediment transport rates and assess harbour sedimentation. Controllers that replicate the control strategy of model-based optimal controllers of water systems are built for situations where fast and accurate decisions are needed. The models built demonstrate excellent performance; they may complement or even replace the existing models and can be used in practice. The performance of the models proves the effectiveness of the methodology and machine learning in general.

Full Product Details

Author:   Biswa Bhattacharya
Publisher:   Taylor & Francis Ltd
Imprint:   CRC Press
Weight:   0.589kg
ISBN:  

9780415391702


ISBN 10:   0415391709
Pages:   254
Publication Date:   22 December 2005
Audience:   College/higher education ,  Professional and scholarly ,  Tertiary & Higher Education ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

1 Introduction 2 Learning tasks and methods 3 Unsupervised learning in segmentation problems 4 Learning classification in geotechnical problems 5 Learning regression in sedimentation problems 6 Learning to control water systems 7 Conclusions and recommendations

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Biswa Bhattacharya

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