Search Results - (( based operation learning algorithm ) OR ( simulation optimization method algorithm ))

Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition by Yew W.H., Fat Chau C., Mahmood Zuhdi A.W., Syakirah Wan Abdullah W., Yew W.K., Amin N.

“…In this study, MATLAB models of a DRL-based MPPT algorithm were developed, tested, and compared to simulation based on two established MPPT algorithms-the Particle Swarm Optimization (PSO), and the Perturb and Observe (P&O). …”

Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

“…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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Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…This approach demonstrates the ability of the GOOSE algorithm to simulate complex systems and enhances the robustness and adaptability of the simulation tool by integrating essential behaviours into the computational framework. …”

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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System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Comprehensive review of drones collision avoidance schemes: challenges and open issues by Rezaee, Mohammad Reza, Abdul Hamid, Nor Asilah Wati, Hussin, Masnida, Ahmad Zukarnain, Zuriati

“…Additionally, our analysis delves into machine learning techniques, discusses metrics and simulation tools to validate collision avoidance systems, and delineates local and global algorithmic perspectives. …”
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower by Gatea, Sarah Jabbar

“…The modal frequencies of the tower are evaluated under various conditions of damage in concrete and connection in different parts of the tower by using finite element simulation. 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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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

“…Apart from that, having low values in four of the performance criteria: RMSE, MAE, NSE, and RSR, have further strengthened the credibility of the results. As for the optimization process, the reservoir operation rule was derived using a meta-heuristic algorithm at the monthly interval. …”
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To develop an efficient variable speed compressor motor system by Mohd. Yatim, Abdul Halim, Mulyo Utomo, Wahyu

“…To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. …”
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Optimization-driven extreme learning machine for floating photovoltaic power prediction: A teaching learning-based approach by Mohd Redzuan, Ahmad, Nor Farizan, Zakaria, Mohd Shawal, Jadin, Mohd Herwan, Sulaiman

“…This study presents a novel Teaching–Learning-Based Optimization enhanced Extreme Learning Machine (TLBO-ELM) framework that achieves optimal parameter configuration without algorithmic tuning while maintaining computational efficiency for real-time deployment. …”
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A new modern scheme for solving fractal–fractional differential equations based on deep feedforward neural network with multiple hidden layer by Admon, Mohd Rashid, Senu, Norazak, Ahmadian, Ali, Majid, Zanariah Abdul, Salahshour, Soheil

“…Thus, this research aims to extend the application of ANN to solve FFDE with power law kernel in Caputo sense (FFDEPC) by develop a vectorized algorithm based on deep feedforward neural network that consists of multiple hidden layer (DFNN-2H) with Adam optimization. …”
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Deep reinforcement learning based resource allocation strategy in cloud-edge computing system by Ahmed Adhoni, Zameer, Habelalmateen, Mohammed, DR Janardhana, DR Janardhana, Abdul Sattar, Khalid Nazim, Audah, Lukman

“…In this work, the research focus on the simulation testing of the MAL-DRL algorithm against classical Random Allocation (RA) and singe agent DRL methods. …”
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Deep reinforcement learning based resource allocation strategy in cloud-edge computing system by Ahmed Adhoni, Zameer, Habelalmateen, Mohammed I, D R, Janardhana, Abdul Sattar, Khalid Nazim, Audah, Lukman

“…In this work, the research focus on the simulation testing of the MAL-DRL algorithm against classical Random Allocation (RA) and singe agent DRL methods. …”
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Deep learning-based item classification for retail automation by Ling, Ji Xiang

“…This project focuses on developing a deep learning-based system for retail item classification. …”
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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... by Dokala Janandra, Krishna Kishore

“…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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Fault classification in smart distribution network using support vector machine by Chuan O.W., Ab Aziz N.F., Yasin Z.M., Salim N.A., Wahab N.A.

“…Gaussian radial basis function (RBF) kernel function has been used for training of SVM to accomplish the most optimized classifier. Initial finding from simulation result indicates that the proposed method is quick in learning and shows good accuracy values on faults type classification in distribution system. …”

CFD modeling on coal properties towards the burnout efficiency by Nabil Asyraf Abd Halim

Nature-Inspired cognitive evolution to play Ms. Pac-Man by Tse, Guan Tan, Jason Teo, Patricia Anthony

“…The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. …”
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Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

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