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Advances in Computational Algorithms and Data Analysis [electronic resource] / edited by Sio-Iong Ao, Burghard Rieger, Su-Shing Chen.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Lecture Notes in Electrical Engineering ; 14 | Lecture Notes in Electrical Engineering ; 14Editor: Dordrecht : Springer Netherlands, 2009Descripción: VIII, 588 p. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9781402089190
Trabajos contenidos:
  • SpringerLink (Online service)
Tema(s): Formatos físicos adicionales: Sin títuloClasificación CDD:
  • 005.1 23
Clasificación LoC:
  • Libro electrónico
Recursos en línea:
Contenidos:
Springer eBooksResumen: 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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Scaling Exponent for the Healthy and Diseased Heartbeat -- CLUSTAG & WCLUSTAG: Hierarchical Clustering Algorithms for Efficient Tag-SNP Selection -- The Effects of Gene Recruitment on the Evolvability and Robustness of Pattern-Forming Gene Networks -- Comprehensive Genetic Database of Expressed Sequence Tags for Coccolithophorids -- Hybrid Intelligent Regressions with Neural Network and Fuzzy Clustering -- Design of DroDeASys (Drowsy Detection and Alarming System) -- The Calculation of Axisymmetric Duct Geometries for Incompressible Rotational Flow with Blockage Effects and Body Forces -- Fault Tolerant Cache Schemes -- Reversible Binary Coded Decimal Adders using Toffoli Gates -- Sparse Matrix Computational Techniques in Concept Decomposition Matrix Approximation -- Transferable E-cheques: An Application of Forward-Secure Serial Multi-signatures -- A Hidden Markov Model based Speech Recognition Approach to Automated Cryptanalysis of Two Time Pads -- A Reconfigurable and Modular Open Architecture Controller: The New Frontiers -- An Adaptive Machine Vision System for Parts Assembly Inspection -- Tactile Sensing-based Control System for Dexterous Robot Manipulation -- A Novel Kinematic Model for Rough Terrain Robots -- Behavior Emergence in Autonomous Robot Control by Means of Evolutionary Neural Networks -- Swarm Economics -- Machines Imitating Humans -- Reinforced ART (ReART) for Online Neural Control -- The Bump Hunting by the Decision Tree with the Genetic Algorithm -- Machine Learning Approaches for the Inversion of the Radiative Transfer Equation -- Enhancing the Performance of Entropy Algorithm using Minimum Tree in Decision Tree Classifier -- Numerical Analysis of Large Diameter Butterfly Valve -- Axial Crushing of Thin-Walled Columns with Octagonal Section: Modeling and Design -- A Fast State Estimation Method for DC Motors -- Flatness based GPI Control for Flexible Robots -- Estimation of Mass-Spring-Dumper Systems -- MIMO PID Controller Synthesis with Closed-Loop Pole Assignment -- Robust Design of Motor PWM Control using Modeling and Simulation -- Modeling, Control and Simulation of a Novel Mobile Robotic System -- All Circuits Enumeration in Macro-Econometric Models -- Noise and Vibration Modeling for Anti-Lock Brake Systems -- Investigation of Single Phase Approximation and Mixture Model on Flow Behaviour and Heat Transfer of a Ferrofluid using CFD Simulation -- Two Level Parallel Grammatical Evolution -- Genetic Algorithms for Scenario Generation in Stochastic Programming -- New Approach of Recurrent Neural Network Weight Initialization -- GAHC: Hybrid Genetic Algorithm -- Forecasting Inflation with the Influence of Globalization using Artificial Neural Network-based Thin and Thick Models -- Pan-Tilt Motion Estimation Using Superposition-Type Spherical Compound-Like Eye.

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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