Search Results - (( developing development action algorithm ) OR ( java optimization techniques algorithm ))
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Hybrid genetic algorithm for improving fault localization
Published 2018“…Genetic algorithm (GA) is well known in finding an optimal solution to a problem while local search is capable of removing duplication. …”
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Scalable approach for mining association rules from structured XML data
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Recently, various techniques based on different algorithms have been developed. …”
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Improving Class Timetabling using Genetic Algorithm
Published 2006“…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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An enhancement of multi-factor weighted approach technique in prioritizing test cases by comparing similarity distance
Published 2025“…Therefore, numerous factors and techniques have been used to optimize the prioritization process. …”
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Adaptive artificial neural network for power system security assessment and control action
Published 2012“…Finally, a software tool based on an adaptive neural network for power system security assessment was developed. The idea of the AANN approach presented in this thesis is to generalise the security assessment method with the consideration of remedial action for any operating point. …”
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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective
Published 2023“…Sustainable development is a problem-solving method that simultaneously accounts for the economic, environmental, and social impacts of actions. …”
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Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement
Published 2016“…In previous work, an Adaptive Linear Neuron (ADALINE) based extraction algorithm has been developed to generate reference currents. …”
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Simulation of an adaptive artificial neural network for power system security enhancement including control action
Published 2015“…The developed method is proved to be a steady-state security assessment tool for supplying possible control actions to mitigate an insecure situation resulting from credible contingency. …”
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The application of suitable sports games for junior high school students based on deep learning and artificial intelligence
Published 2025“…This study intends to develop a Spatial Temporal-Graph Convolutional Network (ST-GCN) action detection algorithm based on the MediaPipe framework. …”
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Design and Implementation of Intelligent Interoperability Framework for Heterogeneous Subsystems in Smart Home Environment
Published 2011“…By inheriting the capabilities of XML SOAP technology and Web Services, three new algorithms based on Event-Condition-Action (ECA) paradigm have been developed to facilitate efficient interoperation of the heterogeneous subsystems. …”
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