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Artificial Intelligence Methods in the Environmental Sciences

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Cover of 'Artificial Intelligence Methods in the Environmental Sciences'

Table of Contents

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    Book Overview
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    Chapter 1 Environmental Science Models and Artificial Intelligence
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    Chapter 2 Basic Statistics and Basic AI: Neural Networks
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    Chapter 3 Performance Measures and Uncertainty
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    Chapter 4 Decision Trees
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    Chapter 5 Introduction to Genetic Algorithms
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    Chapter 6 Introduction to Fuzzy Logic
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    Chapter 7 Missing Data Imputation Through Machine Learning Algorithms
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    Chapter 8 Nonlinear Principal Component Analysis
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    Chapter 9 Neural Network Applications to Solve Forward and Inverse Problems in Atmospheric and Oceanic Satellite Remote Sensing
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    Chapter 10 Implementing a Neural Network Emulation of a Satellite Retrieval Algorithm
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    Chapter 11 Neural Network Applications to Developing Hybrid Atmospheric and Oceanic Numerical Models
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    Chapter 12 Neural Network Modeling in Climate Change Studies
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    Chapter 13 Neural Networks for Characterization and Forecasting in the Boundary Layer via Radon Data
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    Chapter 14 Addressing Air Quality Problems with Genetic Algorithms: A Detailed Analysis of Source Characterization
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    Chapter 15 Reinforcement Learning of Optimal Controls
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    Chapter 16 Automated Analysis of Spatial Grids
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    Chapter 17 Fuzzy Logic Applications
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    Chapter 18 Environmental Optimization: Applications of Genetic Algorithms
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    Chapter 19 Machine Learning Applications in Habitat Suitability Modeling
Attention for Chapter 1: Environmental Science Models and Artificial Intelligence
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Chapter title
Environmental Science Models and Artificial Intelligence
Chapter number 1
Book title
Artificial Intelligence Methods in the Environmental Sciences
Published by
Springer, Dordrecht, January 2009
DOI 10.1007/978-1-4020-9119-3_1
Book ISBNs
978-1-4020-9117-9, 978-1-4020-9119-3
Authors

Sue Ellen Haupt, Valliappa Lakshmanan, Caren Marzban, Antonello Pasini, John K. Williams, Haupt, Sue Ellen, Lakshmanan, Valliappa, Marzban, Caren, Pasini, Antonello, Williams, John K.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 25%
Student > Ph. D. Student 3 25%
Unspecified 1 8%
Student > Bachelor 1 8%
Student > Master 1 8%
Other 1 8%
Unknown 2 17%
Readers by discipline Count As %
Earth and Planetary Sciences 3 25%
Mathematics 2 17%
Unspecified 1 8%
Environmental Science 1 8%
Computer Science 1 8%
Other 1 8%
Unknown 3 25%