Search Results - (( data integration learning algorithm ) OR ( parameter optimization based algorithm ))

Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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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.

Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction by Jinmei Shi, Yu-Beng Leau, Kun Li, Huandong Chen

“…Given this context, this paper proposes a network traffic prediction mechanism based on optimized Variational Mode Decomposition (VMD) and Integrated Extreme Learning Machine (ELM). …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Therefore, we propose a prominent approach that integrates each of the NN, a meta-heuristic based on an evolutionary genetic algorithm (GA), and a core online-offline clustering (Core). …”
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Hyper-heuristic framework for sequential semi-supervised classification based on core clustering by Adnan, Ahmed, Muhammed, Abdullah, Abd Ghani, Abdul Azim, Abdullah, Azizol, Huyop @ Ayop, Fahrul Hakim

“…Existing stream data learning models with limited labeling have many limitations, most importantly, algorithms that suffer from a limited capability to adapt to the evolving nature of data, which is called concept drift. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

“…The ADAM optimizer effectively tackles challenges in continuous parameter optimization by dynamically updating the model's weights and biases, adapting the learning rate for each parameter based on accumulated historical gradient information to achieve more efficient minimization of the loss function during training. …”
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat by Chia , Yu Huat

“…In addition, Coati Optimization algorithm, Particle Swarm Opimisation (PSO) and Bayesian Optimsiation (BO) are integrated to identify optimal parameters and minimize settlement during twin tunnel excavation and GBT with the optimisation algorithm has shown consistent capability identifying the least SS induced by twin tunnels Keyword: …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

“…In this study, the performance of these three algorithms in obtaining the optimal blade design based on the �436�45D are investigated and compared. …”
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Hierarchical multi-agent system in traffic network signalization with improved genetic algorithm by Tan, Min Keng, Chuo, Helen Sin Ee, Chin, Renee Ka Yin, Yeo, Kiam Beng, Teo, Kenneth Tze Kin

“…A dynamic modeling technique is proposed using Q-learning (QL) algorithm to online observe and learn the inflow-outflow traffic behaviors and extract the model parameters to update the evaluation model used in the fitness function of genetic algorithm (GA). …”
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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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Deep continual learning for predicting blast-induced overbreak in tunnel construction / He Biao by He , Biao

“…Third, the integration of metaheuristic algorithms further ascertains the optimal blasting parameters for overbreak minimization under specific rock sections. …”
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Precision agriculture for corn using reinforcement learning by Tan, Carlton

“…Beyond data access, RACKY incorporates a sophisticated reinforcement learning agent based on the Proximal Policy Optimization (PPO) algorithm within the SWATGym. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review by Yafouz A., Ahmed A.N., Zaini N., El-Shafie A.

Enhancement of Groundwater-Level Prediction Using an Integrated Machine Learning Model Optimized by Whale Algorithm by Banadkooki F.B., Ehteram M., Ahmed A.N., Teo F.Y., Fai C.M., Afan H.A., Sapitang M., El-Shafie A.

“…The objectives were: (1) to prepare robust hybrid ANN models; (2) to study the combination of ANN models and optimization algorithms; and (3) to study uncertainty related to the input parameters of the models, whereby three scenarios with different inputs were considered. …”

Precision agriculture for corn using reinforcement learning by Tan, Carlton

“…Beyond data access, RACKY incorporates a sophisticated reinforcement learning agent based on the Proximal Policy Optimization (PPO) algorithm within the SWATGym. …”
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