Search Results - (( developing e path algorithm ) OR ( java optimization learning algorithm ))
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Investigating and developing the best method in shortest path for implementing a geographical information system (e-map) for Peninsular Malaysia
Published 2005“…A development of GIS database is also involved in prototype covering the road network in Peninsular Malaysia (the e-map) will be developed to show the viability or validity of the findings. …”
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Meta-Heuristic Algorithms for Learning Path Recommender at MOOC
Published 2021“…We have developed Metaheuristic algorithms includes the Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), to solve the proposed model. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. …”
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Cyclic Path Planning Of Hyper-Redundant Manipulator Using Whale Optimization Algorithm
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Development of Path Loss Models for Smooth and Convex Surfaces Terrains in Malaysian Environment
Published 2004“…This study describes the development of path loss prediction model for smooth and convex surfaces terrains in Malaysian environment. …”
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Resource-Efficient Coverage Path Planning for UAV-Based Aerial IoT Gateway
Published 2023“…The EECPP is composed of two algorithms: the Stop Point Prediction Algorithm using K-Means, and Path Planning Algorithm using Particle Swarm Optimization. …”
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Computationally-efficient path planning algorithms in obstacle-rich environments based on visibility graph method
Published 2018“…Cun·ent studies have been focused on developing path planning algorithms to satisfy the criteria of path planning namely minimum path length, low computation time and complete, i.e., it gives positive result if a path is available or negative if otherwise. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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