Search Results - (( based optimization based algorithm ) OR ( data virtualization learning algorithm ))

Virtual power plant and microgrids controller for energy management based on optimization techniques by Abdolrasol M.G.M., Mohamed A., Hannan M.A.

ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation by Hannan M.A., Abdolrasol M.G., Mohamed R., Al-Shetwi A., Ker P., Begum R., Muttaqi K.

An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm by Abdolrasol M.G.M., Hannan M.A., Mohamed A., Amiruldin U.A.U., Abidin I.B.Z., Uddin M.N.

Enhancing hyperparameters of LSTM network models through genetic algorithm for virtual learning environment prediction by Ismanto, Edi, Ab Ghani, Hadhrami, Md Saleh, Nurul Izrin

“…Genetic algorithms for hyperparameter optimization significantly contributed, with the GA + LSTM + ADAGRAD model achieving 88% and 87% accuracy in the 7th and 9th models for BBB course data. …”
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Artificial Neural Network Based Particle Swarm Optimization for Microgrid Optimal Energy Scheduling by Abdolrasol M., Mohamed R., Hannan M., Al-Shetwi A., Mansor M., Blaabjerg F.

Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

“…After that, it has been suggested to improve the efficiencies in the Deep Neural Network (DNN) model by combining the DNN with an unsupervised machine learning algorithm, the K-Means clustering algorithm. This study constructs the flow of DNN based method with the K-Means algorithm. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

“…The growing global populations, particularly in major cities, have created new problems, notably in terms of public safety regulation and optimization. As a result, in this paper, a strategy is provided for predicting crime occurrences in a city based on historical events and demographic observation. …”
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Reactive power tracing in pool-based power system utilising the hybrid genetic algorithm and least squares support vector machine by Mohd Wazir, Mustafa, Prof. Dr., Mohd Herwan, Sulaiman, Hussain, Shareef, Dr., Siti Nur Hidayah, Abd Khalid

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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. Gathering and evaluating a large amount of data is time and effortintensive. …”
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Facilitating English Language teaching through AI- based drama in Palestine by Bsharat, Tahani, Sheikh Ahmad, Ismail

“…Artificial Intelligence (AI) has the potential to significantly reshape the landscape of education through the integration of AI- powered tools, personalized learning algorithms, and virtual and augmented reality. …”
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Improving Patient Rehabilitation Performance In Exercise Games Using Collaborative Filtering Approach by Waidah Ismail, Ismail Ahmed Al-Qasem Al-Hadi, Crina Grosan, Rimuljo Hendradi

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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Reinforcement learning-driven hybrid precopy/postcopy VM migration for energy-efficient data centers by Hidayat, Taufik, Ramli, Kalamullah, Harwahyu, Ruki, Salman, Muhammad, Gunawan, Teddy Surya

“…The data center state and the resource load, including the CPU, memory, and network, are represented in the agent’s state space using a two-layer graph neural network (GNN), and the asynchronous advantage actor–critic (A3C) algorithm is employed to dynamically determine whether to continue the precopy phase or switch to postcopy and optimize the trade-off among the total migration time, downtime, and energy consumption while adhering to the service-level agreement (SLA) constraints. …”
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Malware Detection using Deep Learning (DL) by Chowdhury Sajadul Islam, Madihah Mohd Saudi, Nur Hafiza Zakaria, Muji Setiyo

Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

“…The reliability of VR supports various variations in learning, including learning programming algorithms. …”
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Opposition-based Whale Optimization Algorithm by Alamri, Hammoudeh S., Alsariera, Yazan A., Kamal Z., Zamli

“…In order to improve solution accuracy and reliability, this paper proposes a new algorithm based on WOA. The new algorithm called Opposition-based Whale Optimization (OWOA). …”
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Performance comparison of non-invasive blood glucose level using artificial neural network and ultra-wide band antenna by Islam, Minarul Rafiqul, Sabira, Khatun, Kamarul Hawari, Ghazali, Mohd Mawardi, Saari, Shakib, Mohammed Nazmus, Mohamad Shaiful, Abdul Karim

“…Several experiments were carried out to investigate the optimal ANN learning algorithm (levenberg-marquardt (LM), resilient backpropagation (RP) and scaled conjugate gradient (SCG)) for performance comparison. …”
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The impact of virtual reality on programming algorithm courses on student learning outcomes by Dewi, Ika Parma, Ambiyar, Effendi, Hansi, Giatman, Muhammad, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem by Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

“…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
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