Search Results - (( using optimization learning algorithm ) OR ( using action method 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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Particle swarm optimization with deep learning for human action recognition
Published 2021“…This paper proposes a deep learning framework for human action recognition to overcome the drawbacks of the current state-of-the-art methods. …”
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Deep Reinforcement Learning For Control
Published 2021“…The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. …”
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Prediction analysis of COVID-19 in Selangor by using Backpropagation Algorithm with Conjugate Gradient Method
Published 2024“…Backpropagation is a form of artificial neural network (ANN) algorithm that may be used to resolve issues in prediction analysis. …”
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Prediction analysis of COVID-19 in Selangor by using backpropagation algorithm with conjugate gradient method
Published 2024“…Backpropagation is a form of artificial neural network (ANN) algorithm that may be used to resolve issues in prediction analysis. …”
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A simplified adaptive neuro-fuzzy inference system (ANFIS) controller trained by genetic algorithm to control nonlinear multi-input multi-output systems
Published 2011“…A real-coded genetic algorithm (GA) was utilized to optimize the premise and the consequent parameters of the ANFIS controller, instead of the hybrid learning methods that are widely used in the literature. …”
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A simplified PID-like ANFIS controller trained by genetic algorithm to control nonlinear systems
Published 2010“…Moreover, the GA was used to find the optimal settings for the input and output scaling factors for this controller, instead of the widely used trial and error method. …”
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Hierarchical extreme learning machine based reinforcement learning for goal localization
Published 2017“…In this paper, reinforcement learning (RL) method was utilized to find optimal series of actions to localize the goal region. …”
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Proceeding Paper -
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HELM based Reinforcement Learning for Goal Localization
Published 2016“…In this paper, reinforcement learning method was utilized to find optimal series of actions to localize the goal region. …”
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Proceeding Paper -
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Multi-Objectives Optimization Of Energy Consumption Of IKM Bintulu Buildings Towards Energy Saving
Published 2017“…The algorithm is classified as optimization and without optimization method that been used to simulate to find the weight fitness of chromosome which the input is intensified as air conditioning temperature and lighting illuminance (Lux). …”
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Study on tourism development using CRITIC method for tourist satisfaction
Published 2025“…This paper presents a novel approach for evaluating tourist satisfaction and developing optimized strategies by integrating the CRITIC method, deep learning with Multilayer Perceptron (MLP), and Genetic Algorithms (GA). …”
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Intelligent traffic lights using Q-learning
Published 2022“…Q-learning derives benefits from past experiences and determines the optimal course of action based on them. …”
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Proceeding Paper -
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Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin
Published 2021“…Instead of randomly selecting the inputs, the test generator learns how to act in an optimal way that explores new states by using new actions to gain more rewards. …”
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Exploring clusters of rare events using unsupervised random forests
Published 2022“…Given highly imbalanced data, most learning algorithms face the challenge of accurately predicting rare events, while such cases are the ones that carry importance and useful knowledge. …”
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A Data Mining Approach to Enhancing Birth and Death Registration Processes
Published 2025“…The optimal number of clusters of clusters for birth and death data is determined as three using elbow and silhouette validation methods. …”
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A genetically trained simplified ANFIS controller to control nonlinear MIMO systems
Published 2011“…In addition, the real-coded genetic algorithm (GA) has been utilized to train this MIMO ANFIS controller, instead of the hybrid learning methods that are widely used in the literature. …”
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Conference or Workshop Item