Search Results - (( java implementation phase algorithm ) OR ( using partial learning algorithm ))
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…All the algorithm for the engine has been developed by using Java script language. …”
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Thesis -
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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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Ensemble Dual Algorithm Using RBF Recursive Learning for Partial Linear Network
Published 2011“…A new learning algorithm called the ensemble dual algorithm for estimating the mass-flow rate of the flow after leakage is proposed. …”
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Book Section -
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Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training
Published 2020“…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic
Published 2004“…The ECDRQ Routing Algorithm integrates the ECQ and Dual Reinforcement Q (DRQ) Routing Algorithms with Alternative Q Value Approach to minimise the effect of partially learning cycle. …”
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Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar
Published 2006“…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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8
Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications
Published 2020“…The solution provided by deep learning for a differential equation is in a closed analytical form which is differentiable and could be used in any subsequent computation. …”
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Conference or Workshop Item -
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Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing
Published 2022“…The proposed AI algorithm integrates two deep learning models which are object detection algorithm and reinforcement learning. …”
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Final Year Project / Dissertation / Thesis -
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Solving the optimal path planning of a mobile robot using improved Q-learning
Published 2019“…In order to address this limitation, the concept of partially guided Q-learning is introduced wherein, the flower pollination algorithm (FPA) is utilized to improve the initialization of Q-learning. …”
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Indoor occupancy detection using machine learning and environmental sensors / Akindele Segun Afolabi ... [et al.]
Published 2025“…Furthermore, it is necessary to develop models that are robust enough to achieve acceptable performance in situations where partial data from sensors are available. In this paper, we experimentally determined the Machine Learning (ML) models that are most robust for use in indoor occupancy detection. …”
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Improved rsync algorithm to minimize communication cost using multi-agent systems for synchronization in multi-learning management systems
Published 2017“…To meet this requirement, a new Multi LMS (MLMS) model using Sharable Content Object Reference Model (SCORM) specifications to share learning materials among different higher learning institutions (HLIs) has been presented. …”
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A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition
Published 2024“…Therefore, a modified PSO hybridized with adaptive local search (MPSO-HALS) is designed as a robust, real-time MPPT algorithm. A modified initialization scheme that leverages grid partitioning and oppositional-based learning is incorporated to produce an evenly distributed initial population across P-V curve. …”
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Analysis & design low power multiplier using TSMC 0.18µm CMOS technology
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Learning Object -
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Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting
Published 2021“…Next, a newly developed hybrid deep learning (DL) algorithm is proposed to predict the daily water level in selected rivers that flow through Kelantan. …”
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16
Reinforcement learning based techniques in uncertain environments: problems and solutions
Published 2015“…Reinforcement learning (RL) is a well-known class of machine learning algorithms used in planning and controlling of autonomous agents. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Thus, using neural network-based semi-supervised stream data learning is inadequate due to capture the changes in the distribution and characteristics of various classes of data while avoiding the effect of the outdated stored knowledge in neural networks (NN). …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…The initial population is produced by generating quasi-random numbers using Rsequence followed by adapting the partial opposition-based learning concept to improve the diversity of the worst half in the population of hawks. …”
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