Search Results - (( based optimization method algorithm ) OR ( user evaluation method algorithm ))*
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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS
Published 2012“…Experimental evaluation confirmed that the proposed grid scheduling algorithms possess a high degree of optimality in performance, efficiency and scalability.…”
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Optimal demand response of solar energy generation using Genetic Algorithm / Muhammad Asyraaf Adlan
Published 2025“…The method involves collecting data from the solar energy project of UiTM Kampus Dungun, implementing GA for optimization, and evaluating its performance based on the fitness value and convergence trends. …”
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An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system
Published 2023“…Comparative findings alongside other existing metaheuristic-based algorithms confirmed excellence of the proposed method through its superior performance against the conventional MPA, particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), salp-swarm algorithm (SSA), slime mould algorithm (SMA), flow direction algorithm (FDA), and the formally published adaptive safe experimentation dynamics (ASED)-based methods.…”
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Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals
Published 2018“…Methods/Analysis: In this work, two nature-inspired optimization methods, namely Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) are applied to enhancing the conventional MVDR performance. …”
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PID TUNING OF DC MOTOR USING SWARM ITELLIGENCE ALGORITHM
Published 2012“…In this project, Particle Swarm Optimization (PSO) as one of Swarm Intelligence Algorithm based has proposed to be integrated with PID (Proportional, Integral, Derivative) Controller in order to achieve optimal tuning method. …”
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Final Year Project -
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman
Published 2025“…This study applies Genetic Algorithms (GA) to optimize space distribution for test scheduling, addressing the challenge of managing multiple test sessions across distinct locations. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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Independent task scheduling algorithms in fog environments from users’ and service providers’ perspectives: a systematic review
Published 2025“…To address these issues, a substantial amount of work has been done to determine optimal methods to improve QoS using task scheduling algorithms. …”
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School teacher-subject allocation management system
Published 2024“…So, requirement gathering using multiple methods like interviews and system analysis will be performed the narrow down the constraints used in the algorithm, while also lowering the complexity of the Genetic Algorithm to reduce the time complexity. …”
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Final Year Project / Dissertation / Thesis -
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Smart Routing For Solid Waste Collection
Published 2023“…Finally, the conclusion highlights the accomplishments of the project, including the successful development of the route optimization algorithm and the web-based application. …”
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Final Year Project Report / IMRAD -
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Deep reinforcement learning approaches for multi-objective problem in Recommender Systems
Published 2022“…The current major existing multi-objective recommendation approaches utilize collaborative filtering method as rating predictor to replenish the missing ratings and combined with evolutionary algorithm for only bi-objective optimization. …”
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Block based low complexity iterative QR precoder structure for Massive MIMO
Published 2021“…For the system sum rate, the results of the increase in the number of users with a fixed number of 128 and 512 BS antennas show that the proposed method achieved up to 24% and 35% respectively compared to the regular BD algorithm. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Electroencephalogram signal interpretation system for mobile robot
Published 2013“…The aim of this project is to develop an algorithm that can choose optimal four electrodes for signal recording, and convert one thought into multiple commands with the chosen electrodes. …”
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network
Published 2023“…This thesis proposes a hybrid ML-based intrusion detection system (ML-IDS) and ML-based intelligent routing algorithm (ML-RA) for MPLS network. …”
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Energy-efficient power allocation and joint user association in multiuser-downlink massive MIMO system
Published 2019“…The study aims to maximize the non-convex EE in a downlink (DL) massive MIMO system using a proposed energy-efficient low-complexity algorithm (EELCA) that guarantees optimal power allocation solution based on Newton’s methods and joint user’s association based on the Lagrange’s decomposition method. …”
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Task scheduling in cloud computing environment using hybrid genetic algorithm and artificial bee colony
Published 2022“…During the methodology chapter, a comprehensive investigation has been done to ascertain the proposed method that can be adopted such as algorithms involved, project flow, and simulation. …”
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