Search Results - (( developing implementation learning algorithm ) OR ( using simulation optimization algorithm ))
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. 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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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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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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Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA
Published 2014“…The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model.…”
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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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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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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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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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Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function
Published 2019“…This study aims to explore the potential of implementing multi-agent-based Genetic Algorithm (GA) with interactive metamodel to acquire regular optimisation on dynamic characteristic of traffic flow. …”
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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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Automatic nutrient mixer and pH Level for hydroponic application / Hariz Akmal Azizan
Published 2024“…Future work could involve integrating advanced machine learning algorithms to optimize nutrient dosing and implement self-harvesting mechanisms, thereby enhancing plant production and contributing to the development of more efficient and sustainable hydroponic systems for agricultural practices.…”
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Student Project -
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A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit...
Published 2024“…Besides, the performance of the Renewable Energy (RE)-based system has to be enriched with regard to settling time, accuracy, speed, and efficiency. Hence, to optimize the cost of integrating RES‘s through newly developed maximum power point tracking (MPPT) based optimization method such as grasshopper optimization algorithm (GOA) has been introduced. …”
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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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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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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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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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