A Reconfigurable Custom Machine for Accelerating Cellular Genetic Algorithms

U.Porto Journal of Engineering
doi 10.24840/2183-6493_002.002_0002
Full Text
Abstract

Available in full text

Date
Authors
Publisher

University of Porto

Related search

Accelerating McMc Algorithms

Wiley Interdisciplinary Reviews: Computational Statistics
StatisticsProbability
2018English

Accelerating Data Centers With Reconfigurable Logic

2015English

Optimum Machine Capabilities for Reconfigurable Manufacturing Systems

International Journal of Advanced Manufacturing Technology
ControlSystems EngineeringIndustrialMechanical EngineeringManufacturing EngineeringComputer Science ApplicationsSoftware
2018English

Machine-Coded Genetic Operators and Their Performances in Floating-Point Genetic Algorithms

International Journal of Advanced Mathematical Sciences
2017English

Machine Learning for Information Retrieval: Neural Networks, Symbolic Learning, and Genetic Algorithms

Journal of the American Society for Information Science
1995English

Some Experiments on the Use of Genetic Algorithms in a Boltzmann Machine

English

Optical Character Recognition Based on Genetic Algorithms and Machine Learning

International Journal of Computer Applications
2017English

A Diversification Operator for Genetic Algorithms

OPSEARCH
Management ScienceComputer Science ApplicationsInformation SystemsOperations ResearchManagement Information Systems
2012English

A Genetic Approach for Accelerating Communication Performance by Node Mapping

IEICE Transactions on Information and Systems
Electronic EngineeringPattern RecognitionHardwareComputer VisionElectricalArchitectureArtificial IntelligenceSoftware
2018English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy