Modern Approach to Artificial Intelligence

216 Pages·2014·30.59 MB·English

Modern Approach to
Artificial Intelligence
Volume II
Akira Hanako
Modern Approach to Artificial Intelligence
Volume II
"This page is Intentionally Left Blank"
Modern Approach to Artificial
Intelligence
Volume II
Edited by Akira Hanako
Published by College Publishing House,
5 Penn Plaza,
19th Floor,
New York, NY 10001, USA
Modern Approach to Artificial Intelligence: Volume II
Edited by Akira Hanako
© 2018 College Publishing House
International Standard Book Number: 978-1-9789-1443-8
This book contains information obtained from authentic and highly regarded sources. Copyright for all individual chapters
remain with the respective authors as indicated. A wide variety of references are listed. Permission and sources are indicat-
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Contents
Preface VII
Chapter 1 Artificial-Intelligence-Based Techniques to Evaluate Switching
Overvoltages during Power System Restoration 1
Iman Sadeghkhani, Abbas Ketabi and Rene Feuillet
Chapter 2 A Novel Reinforcement Learning Architecture for Continuous
State and Action Spaces 9
Víctor Uc-Cetina
Chapter 3 A Novel Approach to Improve the Performance of Evolutionary
Methods for Nonlinear Constrained Optimization 19
Alireza Rowhanimanesh and Sohrab Efati
Chapter 4 Radial-Basis-Function-Network-Based Prediction of Performance and
Emission Characteristics in a Bio Diesel Engine Run on WCO Ester 26
Shiva Kumar, P. Srinivasa Pai and B. R. Shrinivasa Rao
Chapter 5 Basin Hopping as a General and Versatile Optimization Framework
for the Characterization of Biological Macromolecules 33
Brian Olson, Irina Hashmi, Kevin Molloy and Amarda Shehu
Chapter 6 A Stochastic Hyperheuristic for Unsupervised Matching of Partial
Information 52
Kieran Greer
Chapter 7 Work Out the Semantic Web Search: The Cooperative Way 60
Dora Melo, Irene Pimenta Rodrigues and Vitor Beires Nogueira
Chapter 8 Conservative Intensional Extension of Tarski’s Semantics 69
Zoran Majkić
Chapter 9 Reinforcement Learning in an Environment Synthetically
Augmented with Digital Pheromones 79
Salvador E. Barbosa and Mikel D. Petty
Chapter 10 Simulation of Land-Use Development, Using a Risk-Regarding
Agent-Based Model 102
F. Hosseinali, A. A. Alesheikh and F. Nourian
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VI Contents
Chapter 11 Power Transformer Differential Protection Based on Neural Network
Principal Component Analysis, Harmonic Restraint and Park’s Plots 113
Manoj Tripathy
Chapter 12 Selection for Reinforcement-Free Learning Ability as an Organizing
Factor in the Evolution of Cognition 122
Solvi Arnold, Reiji Suzuki and Takaya Arita
Chapter 13 Contribution to Semantic Analysis of Arabic Language 135
Anis Zouaghi, Mounir Zrigui, Georges Antoniadis
and Laroussi Merhbene
Chapter 14 Soccer Ball Detection by Comparing Different Feature Extraction
Methodologies 143
Pier Luigi Mazzeo, Marco Leo, Paolo Spagnolo and Massimiliano Nitti
Chapter 15 Predicting Asthma Outcome Using Partial Least Square Regression
and Artificial Neural Networks 155
E. Chatzimichail, E. Paraskakis and A. Rigas
Chapter 16 CardioSmart365: Artificial Intelligence in the Service of
Cardiologic Patients 162
Efrosini Sourla, Spyros Sioutas, Vasileios Syrimpeis,
Athanasios Tsakalidis and Giannis Tzimas
Chapter 17 Preference Comparison of AI Power Tracing Techniques for
Deregulated Power Markets 174
Hussain Shareef, Saifunizam Abd. Khalid, Mohd Wazir Mustafa and
Azhar Khairuddin
Chapter 18 A Novel Method for Training an Echo State Network with
Feedback-Error Learning 183
Rikke Amilde Løvlid
Chapter 19 QUEST Hierarchy for Hyperspectral Face Recognition 192
David M. Ryer, Trevor J. Bihl, Kenneth W. Bauer and Steven K. Rogers
Permissions
List of Contributors
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Preface
Artificial intelligence is the term given to the intelligence that is seen to be exhibited by machines or software. It has
emerged as an independent academic field of study. One can define this arena as the study and design of intelligent
agents, where an intelligent agent is a system that comprehends its environment and takes actions that increase its
chances of success. The term is also applicable to the task of developing systems gifted with the logical processes
that are characteristic of humans, such as the ability to discover meaning, reason, generalize and learn from
experience. The field is based on the foundational claim that the central property of humans, that is, intelligence,
can be so accurately expressed that a machine can be made to simulate and imitate it. Artificial Intelligence research
is a highly technical and specialized field, and can be divided into various branches. The goals of AI research
include planning, learning, reasoning, natural language processing or communication, knowledge, perception as
well as the ability to move and manipulate objects. The field of artificial intelligence is an interdisciplinary one, in
which numerous scientific and social science disciplines converge such as psychology, computer science, linguistics,
neuroscience, philosophy as well as other specialized fields such as artificial psychology. This is a highly scientific
field that is undergoing constant and rapid changes and thus needs skilled researchers and engineers in its ranks.
This book lists and discusses the research compiled on the advances that artificial intelligence has undergone
recently. I am thankful to those scientists and researchers whose toil and hard work helped make this effort a
success as well as those outside the scientific community who have been unwavering in their support.
Editor
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1

Arti�cial�Intelligence��ased �echni�ues to
Evaluate Switching Overvoltages during Power
System Restoration
ImanSadeghkhani,1AbbasKetabi,2andReneFeuillet3
1DepartmentofElectricalEngineering,IslamicAzadUniversity,NajafabadBranch,Najafabad85141-43131,Iran
2DepartmentofElectricalEngineering,UniversityofKashan,Kashan87317-51167,Iran
3GrenobleElectricalEngineeringLab(G2ELab),GrenobleINP,BP46,38402SaintMartind’HèresCedex,France
CorrespondenceshouldbeaddressedtoImanSadeghkhani;[email protected]
AcademicEditor:RichardMitchell
ispaperpresentsanapproachtothestudyofswitchingovervoltagesduringpowerequipmentenergization.Switchingactionis
oneofthemostimportantissuesinthepowersystemrestorationschemes.isactionmayleadtoovervoltageswhichcandamage
someequipmentanddelaypowersystemrestoration.Inthiswork,switchingovervoltagescausedbypowerequipmentenergization
areevaluatedusingarti�cial-neural-network-(ANN-)basedapproach.Bothmultilayerperceptron(MLP)trainedwithLevenberg-
Marquardt(LM)algorithmandradialbasisfunction(RBF)structurehavebeenanalyzed.Inthecasesoftransformerandshunt
reactorenergization,theworstcaseofswitchingangleandremanent�uxhasbeenconsideredtoreducethenumberofrequired
simulationsfortrainingANN.Also,forachievinggoodgeneralizationcapabilityfordevelopedANN,equivalentparametersofthe
networkareusedasANNinputs.DevelopedANNistestedforapartialof39-busNewEnglandtestsystem,andresultsshowthe
effectivenessoftheproposedmethodtoevaluateswitchingovervoltages.
1.Introduction of switching operations on long transmission lines, or the
switching of capacitive devices, and may result in arrester
Inrecentyears,duetoeconomiccompetitionandderegula- failures.Ferroresonanceisanonharmonicresonancecharac-
tion,powersystemsarebeingoperated closerandcloser to terizedbyovervoltageswhosewaveformsarehighlydistorted
theirlimits.Atthesametime,powersystemshaveincreased andcancausecatastrophicequipmentdamages[1,5].
insizeandcomplexity.Bothfactorsincreasetheriskofmajor Overvoltage will put the transformer into saturation,
poweroutages.Aerablackout,powerneedstoberestored causingcoreheatingandcopiousharmoniccurrentgenera-
asquicklyandreliablyaspossible,and,consequently,detailed tion. Circuit breaker called upon to operate during periods
restorationplansarenec[1–4]. of high voltage will have reduced interrupting capability.
One of the major concerns in power system restoration At some voltage, even the ability to interrupt line-charging
is the occurrence of overvoltages as a result of switching currentwillbelost[6–8].
procedures.esecanbeclassi�edastransientovervoltages, ispaperpresentsthearti�cialneuralnetwork(ANN)
sustained overvoltages, harmonic resonance overvoltages, applicationforestimationofpeakanddurationofovervolt-
andovervoltagesresultingfromferroresonance.Steady-state ages under switching transients during transformer, shunt
overvoltages occur at the receiving end of lightly loaded reactor,andtransmissionlinesenergization.
transmissionlinesasaconsequenceofline-chargingcurrents In[6],switchingovervoltagesduringsingle-phasetrans-
(reactive power balance). Excessive sustained overvoltages former have been evaluated using multilayer perceptron
may lead to damage of transformers and other power sys- (MLP) trained with Levenberg-Marquardt (LM) algorithm.
tem equipment. Transient overvoltages are a consequence In this paper, three-phase transformer has been analyzed.
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