Artificial Organic Networks: Artificial Intelligence Based on Carbon Networks

232 Pages·2014·8.881 MB·English

by  Hiram Ponce-Espinosa, Pedro Ponce-Cruz, Arturo Molina (auth.)

Studies in Computational Intelligence 521
Hiram Ponce-Espinosa
Pedro Ponce-Cruz
Arturo Molina
Artificial Organic
Networks
Artificial Intelligence Based on
Carbon Networks
Studies in Computational Intelligence
Volume 521
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Hiram Ponce-Espinosa
•
Pedro Ponce-Cruz Arturo Molina
•
Artificial Organic Networks
Artificial Intelligence Based on
Carbon Networks
123
Hiram Ponce-Espinosa
Pedro Ponce-Cruz
ArturoMolina
InstitutoTecnológico de Estudios
Superiores deMonterrey
Campus Ciudadde México
Tlalpan Distrito Federal
Mexico
ISSN 1860-949X ISSN 1860-9503 (electronic)
ISBN 978-3-319-02471-4 ISBN 978-3-319-02472-1 (eBook)
DOI 10.1007/978-3-319-02472-1
SpringerChamHeidelbergNewYorkDordrechtLondon
LibraryofCongressControlNumber:2013950734
(cid:2)SpringerInternationalPublishingSwitzerland2014
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To Omar who makes me believe in the
unbelievable
To my parents and grandfather
—Hiram Ponce-Espinosa
To Norma, Pedro and Jamie who are always
very close to my heart
—Pedro Ponce-Cruz
To my lovely family: Silvia, Julio and
Monserrat
—Arturo Molina
Preface
This book was written for undergraduate and graduate students as well as
researchersandscientistsinterestedinartificialintelligencetechniques.Infact,the
intention of this book is to introduce and fully describe the artificial organic
networkstechnique,anovelmachinelearningmethodinspiredonchemicalcarbon
networks. In addition, an organic network-based algorithm named artificial
hydrocarbon networks is presented to show the advantages and the scope of the
technique.
On one hand, the book is complemented with several examples through
chaptersandthedescriptionofreal-worldapplicationsusingartificialhydrocarbon
networks. On the other hand, the text is accompanied with an artificial organic
networkstoolkitimplementedonLabVIEWTMallowingahands-on experienceto
readers.
Theorganizationofthebookisasfollows:Chapter 1introducesanoverviewof
machinelearningandthemodelingproblemwhileChap. 2describeskeyconcepts
oforganicchemistryinordertounderstandthetechnique,Chaps. 3and4describe
the artificial organic networks technique and the artificial hydrocarbon networks
algorithm. Then, Chap. 5 offers some improvements to the basic artificial hydro-
carbon networks algorithm. Finally, Chaps. 6 and 7 provide experimental results
and discuss how to implement the algorithm in real-world applications like audio
filtering, control systems and facial recognition.
Finally, we would like to express our gratitude to all those who provided
supportandrevieweddetailsoverandover,thosewhoreadandofferedcomments
allowed us to quote their remarks, and those who assisted us in the editing,
proofreadinganddesigningstages.AspecialacknowledgementtotheTecnologico
de Monterrey.
Mexico City, Mexico, August 2013 Hiram Ponce-Espinosa
Pedro Ponce-Cruz
Arturo Molina
vii
Contents
1 Introduction to Modeling Problems . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 The Modeling Problem. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Review of Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.1 Learning Algorithms. . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2.2 Classification Algorithms. . . . . . . . . . . . . . . . . . . . . . . 6
1.3 Nature-Inspired Computing. . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.3.1 Metaheuristic Algorithms. . . . . . . . . . . . . . . . . . . . . . . 8
1.3.2 Evolutionary Algorithms . . . . . . . . . . . . . . . . . . . . . . . 9
1.3.3 Biologically Inspired Algorithms . . . . . . . . . . . . . . . . . 9
1.3.4 Chemically Inspired Algorithms . . . . . . . . . . . . . . . . . . 14
1.4 Comparison of Algorithms for Modeling Problems . . . . . . . . . . 17
1.4.1 Complexity and Stability in Modeling Problems. . . . . . . 17
1.4.2 Artificial Organic Networks and Modeling Problems. . . . 20
1.5 Motivation of Artificial Organic Networks. . . . . . . . . . . . . . . . 24
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2 Chemical Organic Compounds. . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.1 The Importance of Organic Chemistry. . . . . . . . . . . . . . . . . . . 32
2.2 Basic Concepts of Organic Compounds . . . . . . . . . . . . . . . . . . 33
2.2.1 Structural Definitions. . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.2.2 Chemical Definitions. . . . . . . . . . . . . . . . . . . . . . . . . . 36
2.3 Covalent Bonding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
2.3.1 Characterization of Covalent Bonds . . . . . . . . . . . . . . . 40
2.4 Energy in Organic Compounds. . . . . . . . . . . . . . . . . . . . . . . . 42
2.4.1 Energy Level Scheme . . . . . . . . . . . . . . . . . . . . . . . . . 42
2.4.2 Measures of Energy . . . . . . . . . . . . . . . . . . . . . . . . . . 43
2.5 Classification of Organic Compounds . . . . . . . . . . . . . . . . . . . 45
2.5.1 Hydrocarbons. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
2.5.2 Alcohols, Ethers, and Thiols. . . . . . . . . . . . . . . . . . . . . 46
2.5.3 Amines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
2.5.4 Aldehydes, Ketones, and Carboxylic Acids . . . . . . . . . . 47
2.5.5 Polymers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
2.5.6 Carbohydrates, Lipids, Amino Acids, and Proteins . . . . . 48
2.5.7 Nucleic Acids. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
ix
x Contents
2.6 Organic Compounds as Inspiration . . . . . . . . . . . . . . . . . . . . . 49
2.6.1 Motivation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
2.6.2 Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3 Artificial Organic Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.1 Overview of Artificial Organic Networks. . . . . . . . . . . . . . . . . 53
3.1.1 The Metaphor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.1.2 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
3.2 Artificial Organic Compounds. . . . . . . . . . . . . . . . . . . . . . . . . 56
3.2.1 Components. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.2.2 Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
3.3 Networks of Artificial Organic Compounds . . . . . . . . . . . . . . . 66
3.3.1 The Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
3.3.2 The Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
3.3.3 Mixtures of Compounds. . . . . . . . . . . . . . . . . . . . . . . . 66
3.4 The Technique of Artificial Organic Networks . . . . . . . . . . . . . 67
3.4.1 Levels of Energy in Components . . . . . . . . . . . . . . . . . 67
3.4.2 Formal Definition of Artificial Organic Networks. . . . . . 68
3.4.3 Model of Artificial Organic Networks. . . . . . . . . . . . . . 69
3.5 Implementation Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
3.5.1 The Search Topological Parameters Problem . . . . . . . . . 70
3.5.2 The Build Topological Structure Problem . . . . . . . . . . . 71
3.5.3 Artificial Organic Networks-Based Algorithms. . . . . . . . 72
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
4 Artificial Hydrocarbon Networks . . . . . . . . . . . . . . . . . . . . . . . . . 73
4.1 Introduction to Artificial Hydrocarbon Networks. . . . . . . . . . . . 73
4.1.1 Chemical Inspiration. . . . . . . . . . . . . . . . . . . . . . . . . . 73
4.1.2 Objectives and Scope . . . . . . . . . . . . . . . . . . . . . . . . . 74
4.2 Basics of Artificial Hydrocarbon Networks. . . . . . . . . . . . . . . . 75
4.2.1 Components. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
4.2.2 Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.2.3 The Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
4.2.4 Mathematical Formulation . . . . . . . . . . . . . . . . . . . . . . 101
4.3 Metrics of Artificial Hydrocarbon Networks. . . . . . . . . . . . . . . 102
4.3.1 Computational Complexity. . . . . . . . . . . . . . . . . . . . . . 102
4.3.2 Stability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
4.4 Artificial Hydrocarbon Networks Practical Features. . . . . . . . . . 108
4.4.1 Partial Knowledge Representation. . . . . . . . . . . . . . . . . 108
4.4.2 Practical Issues in Partial Knowledge Extraction. . . . . . . 110
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
Contents xi
5 Enhancements of Artificial Hydrocarbon Networks. . . . . . . . . . . . 113
5.1 Optimization of the Number of Molecules . . . . . . . . . . . . . . . . 113
5.1.1 The Hess’ Law. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
5.1.2 Boiling and Melting Points in Hydrocarbons . . . . . . . . . 114
5.1.3 Enthalpy in Artificial Hydrocarbon Networks. . . . . . . . . 115
5.2 Extension to the Multidimensional Case. . . . . . . . . . . . . . . . . . 119
5.2.1 Components and Interactions . . . . . . . . . . . . . . . . . . . . 120
5.2.2 Multidimensional AHN-Algorithm . . . . . . . . . . . . . . . . 124
5.3 Recursive Networks Using Aromatic Compounds . . . . . . . . . . . 127
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
6 Notes on Modeling Problems Using Artificial Hydrocarbon
Networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
6.1 Approximation Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
6.1.1 Approximation of Univariate Functions. . . . . . . . . . . . . 132
6.1.2 Approximation of Multivariate Functions. . . . . . . . . . . . 137
6.2 Clustering Problems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
6.2.1 Linear Classifiers . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
6.2.2 Nonlinear Classifiers. . . . . . . . . . . . . . . . . . . . . . . . . . 145
6.3 Guidelines for Real-World Applications. . . . . . . . . . . . . . . . . . 149
6.3.1 Inheritance of Information . . . . . . . . . . . . . . . . . . . . . . 150
6.3.2 Catalog Based on Artificial Compounds . . . . . . . . . . . . 152
6.3.3 Using Metadata. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
7 Applications of Artificial Hydrocarbon Networks . . . . . . . . . . . . . 155
7.1 Filtering Process in Audio Signals. . . . . . . . . . . . . . . . . . . . . . 155
7.1.1 Background and Problem Statement . . . . . . . . . . . . . . . 156
7.1.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
7.1.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . 159
7.2 Position Control of DC Motor Using AHN-Fuzzy
Inference Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
7.2.1 Background and Problem Statement . . . . . . . . . . . . . . . 166
7.2.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
7.2.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . 177
7.3 Facial Recognition Based on Signal Identification
Using AHNs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
7.3.1 Background and Problem Statement . . . . . . . . . . . . . . . 183
7.3.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
7.3.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . 187
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189