Search Results - (( using task based algorithm ) OR ( using optimization ((path algorithm) OR (bat algorithm)) ))
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…Thus, this study investigates the use of Bat algorithm along with back-propagation neural network (BPNN) algorithm in-order to gain optimal weights to solve the local minima problem and also to enhance the convergence rate. …”
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Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm
Published 2022“…In this study, a new proposed hybrid optimization algorithm, called Extended Bat Algorithm (EBA) is used for optimizing the PID controller for the wheel mobile robot. …”
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Book Chapter -
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Optimal path planning algorithm for swarm robots using bat algorithm with mutation (bam)
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Undergraduates Project Papers -
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…This thesis presents a new approach to optimize the performance of a dual beam optical scanning system in terms of its scanning combinations and speed, using Genetic Algorithm (GA). …”
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Thesis -
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Revolutionizing crowd safety: A breakthrough hybrid whale-bat chaotic algorithm (WOABCM) for optimized evacuation simulations
Published 2024“…The Whale-Bat Chaotic Algorithm (WOABCM) is a revolutionary tool for optimizing pathfinding navigation in crowd evacuation scenarios. …”
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Autonomous mobile robots path planning with integrative edge cloud-based ant colony optimization
Published 2025“…In recent years, Automated Mobile Robots (AMRs) have gained significant attention in industry and research applications, requiring efficient path-planning algorithms to optimize task performance. …”
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Finding the optimal road routes between two locations in East Kuala Lumpur by using A* Algorithm based on GPS data / Ilina Syazwani Musa
Published 2007“…In this paper, we will use A* algorithm in road route in East Kuala Lumpur based on GPS data on the Garmin platform. …”
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Thesis -
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The Hybrid of WOABAT-IFDO Optimization Algorithm and Its Application in Crowd Evacuation Simulation
Published 2023“…This paper proposes a new hybrid of nature inspired optimization algorithm (IFDO-WOABAT) based on the latest optimization algorithm namely Improved Fitness Dependent Optimization (IFDO) with Whale-Bat Optimization algorithm (WOABAT). …”
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Proceeding -
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Ant colony optimization (ACO) algorithm for CNC route problem
Published 2012“…The amount of phenomenon on the shortest path proves that ACO-based approach is capable to optimize the route taken for CNC machine in order to drill the holes on PCB. …”
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Undergraduates Project Papers -
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Optimised multi-robot path planning via smooth trajectory generation
Published 2024“…A MPSO algorithm, without path smoothening, is used for comparison. …”
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Final Year Project / Dissertation / Thesis -
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An application of Floyd-Warshall Algortihm in finding shortest path of order picker in warehouse / Saidatul Aisyah Roslan, Siti Norhakimah Mohd Yatim and Siti Sarah Sulaiman
Published 2019“…For the result, shortest path for the order pickers in iterations. The algorithm used can help the order picker to have the shortest path, but it have no direct path. …”
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Student Project -
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Multi agent quality of service routing based on scheme ant colony optimization algorithm
Published 2014“…The important new aspect of ACR-QoS is the combination of constraint-based routing and DiffServ architecture, in Swarm Intelligence (SI) structure where a set of artificial ants is used to determine the optimal path for each class to construct class-based routing tables. …”
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Thesis -
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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