Search Results - (( using allocation problem algorithm ) OR ( simulation optimization learning algorithm ))
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Development of deep reinforcement learning based resource allocation techniques in cloud radio access network
Published 2022“…The first proposed algorithm aims to optimize the EE by controlling the on/off status of RRH via a deep Q network (DQN) and subsequently solving a power optimization problem. …”
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Final Year Project / Dissertation / Thesis -
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Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers
Published 2022“…Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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Article -
3
Distributed learning based energy-efficient operations in small cell networks
Published 2023“…Simulation results demonstrate improved performance in power consumption, load, sum rate, utility, learning rate, convergence, and energy efficiency for small base stations (SBSs) and user equipment (UEs) compared to four benchmarked algorithms, including WMMSE, game theory, Q-learning, and DRL. …”
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Thesis -
4
Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…Simulated Kalman Filter (SKF) solves optimization problems by finding the estimate of the optimum solution. …”
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Conference or Workshop Item -
5
A simulation-metaheuristic approach for finding the optimal allocation of the battery energy storage system problem in distribution networks
Published 2023“…This study will use Teaching Learning-Based Optimization (TLBO) as the main optimizer for the problem simulation. …”
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Article -
6
Maximizing deep learning-based energy efficiency in 5G downlink MIMO-NOMA systems by using MLP-CNN.
Published 2024“…It can be utilized with multiple convolutional and hidden layers, trained using specific algorithms to solve power allocation problems. …”
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Article -
7
Deep reinforcement learning online offloading for SWIPT multiple access edge computing network
Published 2021“…This method no longer needs to solve combinatorial problems. Simulation results are presented to demonstrate that the proposed algorithm is able to approach near-optimal performance and superior in decreasing tasks computation time compared with existing optimization methods, enabling real time optimal resource allocation and offloading achievable in a fast-fading wireless environment.…”
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Proceedings -
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Opposition-based learning simulated kalman filter for Numerical optimization problems
Published 2016“…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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Research Book Profile -
9
Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition
Published 2024“…These DRL-based algorithms optimize the local and global maximum power point (MPP) using deep Q-learning and deep deterministic policy gradient (DDPG). …”
Conference Paper -
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Modification of the ant colony optimization algorithm for solving multi-agent task allocation problem in agricultural application
Published 2024“…To solve the task allocation problem, the capability list of the agents was also adjusted using common UAV capabilities in agricultural application. …”
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Article -
12
Performances Of Metaheuristic Algorithms In Optimizing Tool Capacity Allocations
Published 2014“…To achieve the best allocation, optimization methods, such as metaheuristic algorithms are commonly used. …”
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Thesis -
13
Automated scheduling of hostel room allocation using genetic algorithm
Published 2020“…This paper proposes a hierarchical heuristics approach to cope with hostel room allocation problem. The proposed approach involves selecting eligible students using rank based selection method and allocating selected students to the most suitable hostel room possible via the implementation of a genetic algorithm (GA). …”
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Conference or Workshop Item -
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Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms
Published 2025Subjects:Article -
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…In the first proposed algorithm, SA is used to optimize the rule's discovery activity by an ant. …”
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Thesis -
16
Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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Thesis -
17
Exam hall allocation using genetic algorithm / Norisyani Binti Fauzai
Published 2021“…In this project an automated exam hall allocation prototype was developed using the genetic algorithm since this algorithm is commonly used to produce high-quality optimization solutions. …”
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Thesis -
18
Enhancing simulated kalman filter algorithm using current optimum opposition-based learning
Published 2019“…Simulated Kalman filter (SKF) is a new population-based optimization algorithm inspired by estimation capability of Kalman filter. …”
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Article -
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Opposition- based simulated kalman filters and their application in system identification
Published 2017“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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Thesis -
20
Pressure vessel design simulation using hybrid harmony search algorithm
Published 2019“…Recently the development of optimization algorithm is rapidly increased. Among several optimization algorithms, Harmony Search (HS) has been recently proposed for solving engineering optimization problems. …”
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