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1
Improvement and application of particle swarm optimization algorithm
Published 2025“…This method combines CPTD with the Genetic Algorithm and PSO (GAPSO), resulting in an effective strategy for dynamic formation reconfiguration and path optimization. …”
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2
Fuzzy adaptive emperor penguin optimizer for global optimization problems
Published 2023“…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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3
A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…To summarise, metaheuristic algorithms can give a superior optimization approach than the traditional artificial neural network method, providing the computing time is within an acceptable range. …”
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4
Agreement options for negotiation on material location decision of housing development
Published 2020“…Decision algorithms are based on the cooperative game theory to develop the agreement options and coalition formation. …”
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5
Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…To address the noise problem in multi-view data, this study enhances the gbs method and develops a new self-weighted graph multi-view clustering algorithm (swmcan). …”
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6
Development Of Generative Computer-Aided Process Planning System For Lathe Machining
Published 2019“…To validate the generated tool-path, G-codes generated in media package file (MPF) file format and verified through CNC lathe machine. Indeed, the developed algorithm was able to determine the minimum unit production cost of lathe machining part model. …”
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7
Inter-cell and intra-cell facility layout models under different demand environments in cellular manufacturing systems
Published 2012“…To solve the model, an algorithm based on Simulated Annealing (SA) is developed in C/C++ namely SA1. …”
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8
An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem
Published 2022“…Emperor Penguin Optimizer (EPO) is a recently developed population-based meta-heuristic algorithm that simulates the huddling behavior of emperor penguins. …”
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9
Normalized Relational Storage for Extensible Markup Language (XML) Schema
Published 2011“…The algorithm is based on computing a set of minimum covers for all functional dependencies on a universal relation when given XML Functional Dependencies (XFDs) and the schema information. …”
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Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul
Published 2006“…Four levels of analysis are traversed in order of decreasing abstraction: computational, algorithmic, implementational and formational. As each level is traversed, a biological plausibility argument is gradually strengthened. …”
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11
Optimization of emulsion polymerization of styrene and methyl methacrylate (MMA)
Published 2013“…Using gPROMS, the system analyzed the data, created models, developed algorithms, manipulated and plotted based on the functions and data. …”
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Undergraduates Project Papers -
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Modular deep neural network in reducing overfitting to enhance generalization / Mohd Razif Shamsuddin
Published 2024“…Most of those research results varies as it uses different data, different network design, different parameters and optimizing algorithm. This research aims to experiment a new DNN model that functions modularly by looking into several features that will affect the NN training dynamics. …”
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13
Smart student timetable planner
Published 2025“…A Genetic Algorithm forms the core scheduling engine, generating optimized timetables that respect both hard constraints, such as avoiding clashes, and soft constraints, such as personal preferences.The final output of this project is a functional web-based timetable planner that successfully enhances scheduling efficiency, reduces the likelihood of errors, and improves the overall academic planning experience. …”
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Final Year Project / Dissertation / Thesis -
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Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian
Published 2009“…This optimal state estimate and corrected data base are then used by the security monitoring and operation and control functions of the center.Most state estimation programs in practical use are formulated as overdetermined systems (Pozrikidis, 2008) of nonlinear equations and solved as weighted least square problems (refer to section 2.1.1).This research involves finding the least squares solution of the power system state estimation problem, HTR-1HDx = HTR-1 [z - f (x)] (refer to section 2.3.1) and to develop a program to implement the said algorithm. …”
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15
Opposition-based Whale Optimization Algorithm
Published 2018“…In order to improve solution accuracy and reliability, this paper proposes a new algorithm based on WOA. The new algorithm called Opposition-based Whale Optimization (OWOA). …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
Published 2015“…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
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Conference or Workshop Item -
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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19
An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network
Published 2020“…Based on the performance evaluation, GACS outperforms both Genetic Algorithm (GA)-based cluster optimization algorithm and Cuckoo Search (CS)-based multi-hop optimization algorithm.…”
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