Search Results - (( developing implementation from algorithm ) OR ( learning simulation optimization algorithm ))
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1
Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index
Published 2023“…Electric power plant loads; Learning algorithms; MATLAB; Multiobjective optimization; Optimization; Reactive power; Back tracking; Backtracking search algorithms; Identification method; Load-shedding; Multi-objective functions; Power flow simulation; System contingencies; Under voltage load shedding; Electric load shedding…”
Conference Paper -
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An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…The simulation algorithm and interactive environment thus developed and validated form suitable test and verification platforms for the development of AVC strategies for flexible structures as well as for learning and research purposes.…”
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…This research focuses on the use of binaryencoded genetic algorithm (GA) to implement efficient search strategies for the optimal architecture and training parameters of a multilayer feed-forward ANN. …”
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5
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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6
Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…The results are used to develop the hybrid learning algorithm based on the AdaBoost, Bagging, and RUSBoost methods to predict the damage in the tower based on dynamic frequency domain. …”
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7
Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The proposed algorithm simulates the behavior of the nomads when they are searching for life sources (water or grazing fields). …”
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Parallel CFD Simulations of Multiphase Systems: Jet into a Cylindrical Bath and Rotary Drum on a Rectangular Bath.
Published 2001“…the detailed algorithm for parallelising the code; even the ordinary solution strategies are tedious to learn sometimes. …”
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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 -
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Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam
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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Malicious URL classification using artificial fish swarm optimization and deep learning
Published 2023“…With this motivation, the current article develops an Artificial Fish Swarm Algorithm (AFSA) with Deep Learning Enabled Malicious URL Detection and Classification (AFSADL-MURLC) model. …”
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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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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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Artificial neural network (ANN) as post-processing stage for chemically selective field effect transistor (CHEMFET) sensor selectivity based-on ion concentration / Nurhakimah Abd A...
Published 2016“…This is confirmed based on statistical analysis validation via regression analysis that shows with R-factor of 0.9011. Other than developing supervised learning, this study also was focusing on exploration of unsupervised learning mainly in blind source separation (BSS) algorithm to separate the interface signal. …”
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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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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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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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Conference or Workshop Item -
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Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots
Published 2006“…Experiments were conducted within a 10% noise environment with different task environment complexities to investigate whether the MOEA is effective for controller synthesis. A simulated Khepera robot is evolved by a Pareto-frontier Differential Evolution (POE) algorithm, and learned through a 3-layer feed-forward artificial neural network, attempting to simultaneously fulfill two conflicting objectives of maximizing robot phototaxis behavior while minimizing the neural network's hidden neurons by generating a Pareto optimal set of controllers. …”
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