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Hybrid Artificial Intelligent Systems (HAIS) try to deal with the
complexity of real world phenomena using a multidisciplinary
approach and a plurality of techniques. Logistics Management and
Optimization through Hybrid Artificial Intelligence Systems offers
the latest research within the field of HAIS, surveying the broad
topics and collecting case studies, future directions, and cutting
edge analyses. Using biologically-inspired algorithms such as ant
colony optimization and particle swarm optimization, this text
includes solutions and heuristics for practitioners and academics
alike, offering a vital resource for staying abreast in this
ever-burgeoning field.
This volume comprises eight well-versed contributed chapters
devoted to report the latest findings on the intelligent approaches
to multimedia data analysis. Multimedia data is a combination of
different discrete and continuous content forms like text, audio,
images, videos, animations and interactional data. At least a
single continuous media in the transmitted information generates
multimedia information. Due to these different types of varieties,
multimedia data present varied degrees of uncertainties and
imprecision, which cannot be easy to deal by the conventional
computing paradigm. Soft computing technologies are quite efficient
to handle the imprecision and uncertainty of the multimedia data
and they are flexible enough to process the real-world information.
Proper analysis of multimedia data finds wide applications in
medical diagnosis, video surveillance, text annotation etc. This
volume is intended to be used as a reference by undergraduate and
post graduate students of the disciplines of computer science,
electronics and telecommunication, information science and
electrical engineering. THE SERIES: FRONTIERS IN COMPUTATIONAL
INTELLIGENCE The series Frontiers In Computational Intelligence is
envisioned to provide comprehensive coverage and understanding of
cutting edge research in computational intelligence. It intends to
augment the scholarly discourse on all topics relating to the
advances in artifi cial life and machine learning in the form of
metaheuristics, approximate reasoning, and robotics. Latest
research fi ndings are coupled with applications to varied domains
of engineering and computer sciences. This field is steadily
growing especially with the advent of novel machine learning
algorithms being applied to different domains of engineering and
technology. The series brings together leading researchers that
intend to continue to advance the fi eld and create a broad
knowledge about the most recent state of the art.
Contaminants of Emerging Concern in Water and Wastewater: Advanced
Treatment Processes presents the state-of-the-art in the design and
use of adsorbents, membranes, and UV/oxidation processes, along
with the challenges that will need to be addressed to close the gap
between development and implementation in water/wastewater
treatment applications. Chapters cover adsorbent and membrane
design and performance, direct comparison of performance data
between new (inorganic and metal organic nanoporous materials) and
classic adsorbents and membranes, a list of advantages,
disadvantages, and challenges related to performance limitations,
regenerability, and upscaling. In addition, users will find
sections on the identification of potential site and off-site
applications that are listed according to adsorbent and membrane
types, transformation of CECs in low- and/or medium-pressure UV
irradiation processes used for disinfection, the oxidation of CECs
by chlorine and ozone, and a comparison of advanced oxidation
processes for the treatment of a variety of CECs in water and
wastewater.
The Mexican International Conference on Arti?cial Intelligence
(MICAI), a yearly international conference organized by the Mexican
Society for Arti?cial Intelligence (SMIA), is a major international
AI forum and the main event in the academic life of the country's
growing AI community. The proceedings of the previous MICAI events
were published by Springer in its Lecture Notes in Arti?cial
Intelligence (LNAI) series, vol. 1793,2313,2972,3787,4293,4827, and
5317. Since its foundation the conference has been growing in
popularity and improving quality. This volume contains the papers
presented at the oral sessions of the 8th Mexican International
Conference on Arti?cial Intelligence, MICAI 2009, held November
9-13, 2009, in Guanajuato, Mexico. The conference received for ev-
uation 215 submissions by 646 authors from 21 countries. This
volume contains revised versionsof 63 articles, which after
thorough and careful revision were- lected by the international
Program Committee. Thus the acceptance rate was 29.3% This book is
structured into 18 sections, 17 of which correspond to a c- ference
track and are representative of the main current areas of interest
for the AI community; the remaining section comprises invited
papers. The conference featured excellent keynote lectures by
leading AI experts: Patricia Melin, Instituto Tecnologico de
Tijuana, Mexico Dieter Hutter, DFKI GmbH, Germany Josef Kittler,
Surrey University, UK Ramon Lopez de Mantaras, IIIA-CSIC, Spain
Jose Luis Marroquin, CIMAT, Mexico In addition to the oral
technical sessions and keynote lectures, the conf- ence program
included tutorials, workshops, and a poster session, which were
published in separate proceedings volumes."
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Evolutionary Multi-Criterion Optimization - Third International Conference, EMO 2005, Guanajuato, Mexico, March 9-11, 2005, Proceedings (Paperback, 2005 ed.)
Carlos Coello Coello, Arturo Hernandez Aguirre, Eckart Zitzler
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R2,971
Discovery Miles 29 710
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Ships in 10 - 15 working days
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Multicriterion optimization refers to problems with two or more
objectives (n- mally in con?ict with each other) which must be
simultaneously satis?ed. Multicriterion optimization problems have
not one but a set of solutions (which represent trade-o's among the
objectives), which are called Pareto optimal - lutions. Thus, the
main goal in multicriterion optimization is to ?nd or to -
proximate the set of Pareto optimal solutions. Evolutionary
algorithms have been used for solving multicriterion optimization
problems for over two decades, gaining an increasing popularity
over the last 10 years. The 3rd International Conference on
Evolutionary Multi-criterion Optimi-
tion(EMO2005)washeldduringMarch9 11,2005, inGuanajuato, M
exico.This
wasthethirdinternationalconferencededicatedentirelytothisimportanttopic,
followingthesuccessfulEMO2001andEMO2003conferences, whichwereheldin
Z] urich, SwitzerlandinMarch2001, andinFaro, PortugalinApril2003,
respectively. The EMO 2005 scienti?c program included two keynote
addresses, one given by Peter Fleming on an engineering design
perspective of many-objective op- mization, and the other given by
Milan Zeleny on the evolution of optimality. In addition, three
tutorials were presented, one on metaheuristics for multiobj-
tivecombinatorialoptimizationbyXavierGandibleux,
anotheronmultiobjective evolutionary algorithms by Gary B. Lamont,
and a third one on performance assessment of multiobjective
evolutionary algorithms by Joshua D. Knowle
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