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Solving the minimum dominating set problem of partitioned graphs using a hybrid bat algorithm
Published 2020“…This paper investigates the swarm intelligence behaviour represented by a population-based approach called the bat algorithm (BA) to find the smallest set of nodes that dominate the graph. …”
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Designing and Developing an Intelligent Congkak
Published 2011“…This issues can solved by programming the Congkak system based on previous work on Mancala and NN system, and then recording the performance of the related algorithm. …”
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Thesis -
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Modeling of static and dynamic components of bio-nanorobotic systems
Published 2012“…The first modeling technique applies graph algorithms to compute a new set of optimal weighted structural properties of C60 and C70 fullerenes. …”
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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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African Buffalo Optimization (ABO): A New Metaheuristic Algorithm
Published 2015“…The African Buffalo Optimization (A.B.0) algorithm simulates the African buffalos' behaviour by encapsulation in a mathematical model; which solves a number of discrete optimization problems using graph-based route planning, job scheduling and it extends Swarm Intelligence paradigms. …”
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Hybrid bat algorithm for minimum dominating set problem
Published 2017“…In this paper, the stochastic search represented by hybrid swarm intelligence algorithm to find the smallest set of nodes that dominate the graph. …”
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Heuristic factors in ant system algorithm for course timetabling problem
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Conference or Workshop Item -
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VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.
Published 2012“…The Genetic Algorithm is an area in the field of Artificial Intelligence that is founded on the principles of biological evolution. …”
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Industry 5.0 and Education 5.0: Transforming Vocational Education through Intelligent Technology
Published 2024“…By analyzing the research gaps in personalized learning paths, emotion-driven learning, crossdisciplinary integration, and long-term learning behavior analysis, the paper proposes four improved algorithms: the adaptive learning path generation algorithm, the emotion-driven personalized learning algorithm, the cross-disciplinary knowledge graph algorithm, and the long-term learning behavior prediction algorithm. …”
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Optimization of Maximum Power Point Tracking (MPPT) of Photovoltaic System using Artificial Intelligence (AI) Algorithms
Published 2013“…Studies on the conventional and intelligent algorithms are conducted and a comparison between their efficiencies and drawbacks is presented. …”
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Attack graph construction for enhancing intrusion prediction based on vulnerabilities metrics
Published 2023“…For this issue, this study proposes using intelligent agents to reduce the reachability time in calculating between the nodes and use the naïve approach prune algorithm to remove unnecessary edges, minimizing the attack graph's complexity. …”
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Attack prediction to enhance attack path discovery using improved attack graph
Published 2022“…In order to overcome this limitation, this present study recommends the use of intelligent agents to reduce reachability time by calculating between the nodes, as well as using the A*prune algorithm to remove useless edges and reduce attack graph complexity. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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A Robust Graph Theoretic Solution of Routing in Intelligent Networks
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Machine learning: tasks, modern day applications and challenges
Published 2019“…Machine learning algorithms learned from available data. Further, this learning laid the foundation to develop AI for the various systems around us. …”
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