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  1. 1

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah by Salmah , Fattah

    Published 2022
    “…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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    Thesis
  2. 2

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks by Salmah Fattah

    Published 2022
    “…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisa­tion Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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    Thesis
  3. 3

    Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system by Ali, Hazem I.

    Published 2010
    “…The PSO algorithm is used to optimize the loop-shaping step (subject to QFT constraints), which is performed manually in the standard QFT control design. …”
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    Thesis
  4. 4

    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…The proposed deep reinforcement learning algorithm, which integrates an artificial neural network with traditional reinforcement learning, was formulated based on the optimisation objective by manipulating only the substrate feeding rate. …”
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  5. 5

    Evolutionary algorithm based network coding for optimization of intelligent vehicular ad hoc network by Lee, Chun Hoe

    Published 2017
    “…This project aims to improve the throughput, energy consumption and overhead of vehicular ad hoe network (VANET) by optimising the network coding (NC) using Genetic Algorithm and Particle Swarm Optimisation (GA-PSO). …”
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    Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam by Lai, Vivien Mei Yen

    Published 2023
    “…The Whale Optimisation Algorithm (WOA), Harris Hawks Optimisation (HHO) Algorithm, Lévy Flight WOA (LFWOA) and the Opposition-Based Learning of HHO (OBL-HHO) were proposed to simulate the initial model’s response and optimise the Klang Gate Dam (KGD) release operation with observed inflow, water level (storage), release, and evaporation rate (loss). …”
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    Final Year Project / Dissertation / Thesis
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    Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

    Published 2012
    “…In this study, under environmentfriendliness objective, based on multi-agent genetic algorithms, was developed a geospatial model for the land use allocation. …”
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  9. 9

    Optimised multi-robot path planning via smooth trajectory generation by Loke, Zhi Yu

    Published 2024
    “…Particle swarm optimization (PSO) outperforms conventional methods like artificial potential fields (APF), the Dijkstra algorithm, and the A* algorithm in path planning for mobile robots. …”
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    Final Year Project / Dissertation / Thesis
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    Investigating The Performance Of Metaheuristics To Optimize The Revenue Of Semiconductor Supply Chain by Roslee, Muhammad Sharifuddin

    Published 2022
    “…Investigating the performance of metaheuristics to optimise the revenue of the semiconductor supply chain is the final year project that focuses on to identify the supply chain shortage problem related to semiconductors and to compare among the 20 metaheuristics algorithm optimization programmes capable of optimising the semiconductor supply chain. …”
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    Monograph
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    Forecasting of fine particulate matter based on LSTM and optimization algorithm by Zaini N., Ahmed A.N., Ean L.W., Chow M.F., Malek M.A.

    Published 2024
    “…Long short-term memory based on metaheuristic algorithms, namely particle swarm optimization and sparrow search algorithm (PSO-LSTM and SSA-LSTM), are first developed and applied to determine the significance input combination to the changes of PM2.5 concentration at respective target stations. …”
    Article
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    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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  13. 13

    Optimisation and control of fed-batch yeast production using q-learning by Helen, Chuo Sin Ee

    Published 2013
    “…To cater for the process disturbance, Q-learning with exploration (QLE) has been included in this work for online optimisation. QLE signifies the importance of exploration from time to time based on the developed “past experience” in Q-table to optimise the process. …”
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    Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation by Toha, Siti Fauziah, Abd Latiff, I., Mohamad, M., Tokhi, M Osman

    Published 2009
    “…In this paper, a sound approach for a Twin Rotor Multi-input Multi-Output System (TRMS) parametric modeling is proposed based on dynamic spread factor particle swarm optimization. …”
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    Proceeding Paper
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    Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

    Published 2023
    “…This algorithm named JAABC5ROC is the enhancement of Artificial Bee Colony (ABC) variant, JA-ABC5 by combining with Rate of Change (ROC)\. …”
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    Thesis
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    Cuckoo optimised 2DOF controllers for stabilising the frequency changes in restructured power system with wind-hydro units by Peddakapu, K., M. R., Mohamed, M. H., Sulaiman, Srinivasarao, P., Kishore, D. J. K., P. K., Leung

    Published 2021
    “…Different types of metaheuristic optimisation methods like teaching–learning-based optimisation (TLBO) and cuckoo search algorithms are suggested to acquire the optimal gain values of the proposed controllers. …”
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    Article
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    Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II by M. F. F., Ab Rashid, N. M. Zuki, N. M., A. N. M., Rose

    Published 2016
    “…A full factorial experiment has been conducted to model surface roughness by controlling three variables; spindle speed, feed rate and depth of cut. Multi-objective optimisation has been performed using modified Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) with two levels crossover. …”
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    Conference or Workshop Item
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