Search Results - (( using optimization method algorithm ) OR ( using action learning algorithm ))

Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…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 by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…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 by Bakar, Nurul Asyikin Abu

“…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 by Noor Amirah Ajmal Khan, Siti Mahani Marjugi

“…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 by Ajmal Khan, Noor Amirah, Marjugi, Siti Mahani

“…Backpropagation is a form of artificial neural network (ANN) algorithm that may be used to resolve issues in prediction analysis. …”
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm by Abd Rahman, Mohd Shahrizan, Jamaludin, Nor Azliana Akmal, Zainol, Zuraini, Tengku Sembok, Tengku Mohd

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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 by Lutfy, Omar F., Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce

“…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 by Lutfy, Omar Farouq, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Abbas, Kassim A.

“…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 by AlDahoul, Nouar, Htike, Zaw Zaw, Akmeliawati, Rini

“…In this paper, reinforcement learning (RL) method was utilized to find optimal series of actions to localize the goal region. …”
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HELM based Reinforcement Learning for Goal Localization by AlDahoul, Nouar, Htike@Muhammad Yusof, Zaw Zaw

“…In this paper, reinforcement learning method was utilized to find optimal series of actions to localize the goal region. …”
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Multi-Objectives Optimization Of Energy Consumption Of IKM Bintulu Buildings Towards Energy Saving by Othman, Muhamad Naim

“…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 by Yang, Xi, Ali, Noor Azman, Hon Tat, Huam

“…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 by Mohd Yusop, Muhammad Aminuddin, Mansor, Hasmah, Gunawan, Teddy Surya, Nasir, Haidawati,

“…Q-learning derives benefits from past experiences and determines the optimal course of action based on them. …”
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Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin by Husam , N. S. Yasin

“…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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Discovering optimal features using static analysis and a genetic search based method for Android malware detection by Ahmad Firdaus, Zainal Abidin, Nor Badrul, Anuar, Ahmad, Karim, Mohd Faizal, Ab Razak

“…To evaluate the best features determined by GS, we used five machine learning classifiers, namely, Naïve Bayes (NB), Functional Trees (FT), J48, Random Forest (RF), and Multilayer Perceptron (MLP). …”
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Discovering optimal features using static analysis and a genetic search based method for Android malware detection by Firdaus, Ahmad, Anuar, Nor Badrul, Karim, Ahmad, Razak, Mohd Faizal Ab

“…To evaluate the best features determined by GS, we used five machine learning classifiers, namely, Naïve Bayes (NB), functional trees (FT), J48, random forest (RF), and multilayer perceptron (MLP). …”
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Exploring clusters of rare events using unsupervised random forests by Z A Omar, Chin, Su Na, Siti Rahayu Mohd. Hashim, N Hamzah

“…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 by Erfan, Hasmin

“…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 Hybrid Machine Learning and Optimisation-Based Model for Predicting the Success of Business-To-Consumer Software Development Projects in Indonesia by Setiawan, Rudi

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A genetically trained simplified ANFIS controller to control nonlinear MIMO systems by Lutfy, Omar F., Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce

“…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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