
Applied Natural Computing in Power Systems 
Call for Chapters
Nadia Nedjah,
Leandro dos Santos Coelho,
Viviana Cocco Mariani,
Luiza de Macedo Mourelle (Eds.)
The soft computing, quantum computing and chaos theory approaches differ
from the respective conventional computing techniques in that they are
tolerant of imprecision, uncertainty, partial truth, and approximation.
The soft computing techniques comprises of fuzzy systems, artificial neural
networks, swarm intelligence, probabilistic reasoning and metaheuristic
techniques such as evolutionary algorithms (genetic algorithms, evolutionary
programming, differential evolution, evolution strategies, genetic
programming), tabu search, among others.
On the other hand, quantum computing is a research field that includes
concepts like quantummechanical computers and quantum algorithms. So far,
many efforts on quantum computers have progressed actively due to its
superiority to classical computers on various specialized problems. There
are some wellknown quantum algorithms, such as Grover's database search
algorithm and Shor's quantum factoring algorithm. In this context, recently,
quantuminspired evolutionary algorithms (QEAs) have attracted much
attention and wide applications. QEAs can be useful to treat the balance
between exploration and exploitation more easily compared to conventional
evolutionary algorithms.
Other emergent approach in design of intelligent systems is the chaos
theory. Chaos is a kind of characteristic of nonlinear systems, which is a
bounded unstable dynamic behavior that exhibits sensitive dependence on
initial conditions and includes infinite unstable periodic motions.
Recently, the combination of optimization methods, intelligent systems,
quantum approaches and concepts of chaotic systems are modern issues in
nonlinear science and has attracted interests from various fields.
For this book, we seek original contributions on any aspect related to
optimization, modeling, nonlinear identification, control, automation, among
others using soft computing, quantum computing and chaos theory approaches.
Applications of mentioned design and optimization methodologies in power
systems to realworld system are welcome. The topics of interest include,
but not limited to:
 Intelligent systems and bioinspired approaches in tuning of
stabilizers parameters and automatic voltage regulators
 Quantuminspired evolutionary algorithms in power systems
 Soft computing, quantum computing and chaos theory approaches in
load frequency controller designs in power systems
 Power transformers diagnosis using emergent bioinspired approaches
 Computational intelligence for fault diagnosis of power plant,
optimal reactive power flow, economic power dispatch, alarm processing,
short term scheduling, and environmental/economic power dispatch
 Multiobjective algorithms using global optimization methodologies
based on quantum computing, chaotic systems, and intelligent systems
 Intelligent systems applied to reliability engineering approaches in
electrical power systems
 Bioinspired approaches in design of distribution, transmission and
generation systems
 Optimal capacitor placement in distribution systems using soft
computing, quantum computing and chaos theory approaches
 Applications of intelligent systems, quantum computing, and chaotic
approaches in shortterm electric load forecasting.

The time schedule for this publication is as follows:
 Manuscript submission: May 28, 2010
 Authors Notification: August 30, 2010
 Cameraready submission: September 25, 2010
If you intend to contribute to this book, please send an email to Dr. Viviana Cocco Mariani, informing the title of the chapter and its abstract.
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