Advances in Computational Algorithms and Data Analysis

Advances in Computational Algorithms and Data Analysis contains revised and extended research articles written by prominent researchers participating in a large international conference on Advances in Computational Algorithms and Data Analysis, which was held in UC Berkeley, California, USA, under t...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Ao, Sio-Iong. (Editor), Rieger, Burghard. (Editor), Chen, Su-Shing. (Editor)
Format: Electronic
Language:English
Published: Dordrecht : Springer Netherlands, 2009.
Series:Lecture Notes in Electrical Engineering, 14
Subjects:
Online Access:https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4020-8919-0
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520 # # |a Advances in Computational Algorithms and Data Analysis contains revised and extended research articles written by prominent researchers participating in a large international conference on Advances in Computational Algorithms and Data Analysis, which was held in UC Berkeley, California, USA, under the World Congress on Engineering and Computer Science by the International Association of Engineers (IAENG). IAENG is a non-profit international association for the engineers and the computer scientists, found originally in 1968. The book covers a variety of subjects in the frontiers of computational algorithms and data analysis, including topics like Expert system, Machine learning, Intelligent Decision Making, Fuzzy systems, Knowledge-based systems, Knowledge extraction, Large database management, Data analysis tools, Computational Biology, Optimization algorithms, Experiment designs, Complex system identification, Computational Modelling , and industrial applications. Advances in Computational Algorithms and Data Analysis offers the states of arts of tremendous advances in computational algorithms and data analysis. The selected articles are representative in these subjects sitting on the top-end-high technologies. The volume serves as an excellent reference work for researchers and graduate students working on computational algorithms and data analysis. 
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