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Economic Modeling Using Artificial Intelligence Methods

Overview of attention for book
Cover of 'Economic Modeling Using Artificial Intelligence Methods'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction to Economic Modeling
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    Chapter 2 Techniques for Economic Modeling: Unlocking the Character of Data
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    Chapter 3 Automatic Relevance Determination in Economic Modeling
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    Chapter 4 Neural Approaches to Economic Modeling
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    Chapter 5 Bayesian Support Vector Machines for Economic Modeling: Application to Option Pricing
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    Chapter 6 Rough Sets Approach to Economic Modeling: Unlocking Knowledge in Financial Data
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    Chapter 7 Missing Data Approaches to Economic Modeling: Optimization Approach
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    Chapter 8 Correlations Versus Causality Approaches to Economic Modeling
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    Chapter 9 Evolutionary Approaches to Computational Economics: Application to Portfolio Optimization
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    Chapter 10 Real-Time Approaches to Computational Economics: Self Adaptive Economic Systems
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    Chapter 11 Multi-agent Approaches to Economic Modeling: Game Theory, Ensembles, Evolution and the Stock Market
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    Chapter 12 Control Approaches to Economic Modeling: Application to Inflation Targeting
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    Chapter 13 Modeling Interstate Conflict: The Role of Economic Interdependency for Maintaining Peace
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    Chapter 14 Conclusions and Further Work
Attention for Chapter 3: Automatic Relevance Determination in Economic Modeling
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Chapter title
Automatic Relevance Determination in Economic Modeling
Chapter number 3
Book title
Economic Modeling Using Artificial Intelligence Methods
Published by
Springer, London, January 2013
DOI 10.1007/978-1-4471-5010-7_3
Book ISBNs
978-1-4471-5009-1, 978-1-4471-5010-7
Authors

Tshilidzi Marwala

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 67%
Student > Bachelor 1 33%
Readers by discipline Count As %
Computer Science 2 67%
Mathematics 1 33%

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