Search Results - (( time estimation using algorithm ) OR ( parameter estimation learning algorithm ))

Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

“…This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random forest regression (RFR) algorithm. …”

Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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State of Charge Estimation for Lithium-Ion Battery Using Recurrent NARX Neural Network Model Based Lighting Search Algorithm by Lipu M.S.H., Hannan M.A., Hussain A., Saad M.H.M., Ayob A., Blaabjerg F.

Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization by Muhammad Akmal, Remli, Nor Syahidatul Nadiah, Ismail, Noor Azida, Sahabudin, Nor Bakiah, Abd Warif

“…Estimating parameters values is difficult and time-consuming process due to their highly nonlinear and huge number of kinetic parameters involved. …”
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RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION by CATUR ANDRYANI, NUR AFNY

“…The thesis also try to investigate the influence of initialization of RBF weights parameters on the overall learning performance using random method and advanced unsupervised learning, such as clustering techniques, as a comparison. …”
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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 study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. …”

Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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An intelligent method to estimate the inertia matrix of a robot arm for active force control using on-line neural network training scheme by Hussein, Shamsul Bahri, Jamaluddin, Hishamuddin, Mailah, Musa

“…During the training stage, the proposed ANN scheme trains the ANN parameters (weights and biases) for a period of time by utilising the back-propagation (BP) learning method. …”
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SOC Estimation Using Deep Bidirectional Gated Recurrent Units with Tree Parzen Estimator Hyperparameter Optimization by How D.N.T., Hannan M.A., Lipu M.S.H., Ker P.J., Mansor M., Sahari K.S.M., Muttaqi K.M.

A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…While the firefly algorithm solution is superior, it has a higher time complexity compared to other algorithms used when there are more hidden layers and neurons. …”
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Large-scale kinetic parameters estimation of metabolic model of escherichia coli by Azrag, M. A. K., Tuty Asmawaty, Abdul Kadir, Kabir, M. Nomani, Jaber, Aqeel S.

“…Metabolic models are constructed using mass-balance equations with kinetic-rate computation to simulate the behavior of the metabolic system over time. …”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

“…These parameters are used to develop a standalone intelligently machine learning adaptive distance relay (ML-ADR) modification. …”
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Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

“…Carbon nanotubes; Electrocatalysts; Electrooxidation; Forestry; Formic acid; Gaussian distribution; Learning algorithms; Palladium; Parameter estimation; Regression analysis; Support vector machines; Formic acid electrooxidation; Fuel cell application; Gaussian kernel functions; Gaussian process regression; Interaction effect; Machine learning algorithms; Performance; Process parameters; Regression trees; Support vector machine regressions; Sensitivity analysis…”

Optimal Tuning of Fractional Order Sliding Mode Controller for PMSM Speed Using Neural Network with Reinforcement Learning by Zahraoui Y., Zaihidee F.M., Kermadi M., Mekhilef S., Alhamrouni I., Seyedmahmoudian M., Stojcevski A.

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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

“…This dataset, alongside key parameters like cover-to-depth ratio, pillar width, soil stiffness, cohesion, friction angle, and overburden-to-face pressure ratio, integrates into a machine learning framework using a theory-guided approach. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

“…Multi-Verse Optimizer (MVO) is one of the most recent robust nature-inspired metaheuristic algorithm. It has been successfully implemented and used in various areas such as machine learning applications, engineering applications, network applications, parameter control, and other similar applications to solve optimization problems. …”
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Using Machine Learning Algorithms to Estimate the Compressive Property of High Strength Fiber Reinforced Concrete by Dai, L., Wu, X., Zhou, M., Ahmad, W., Ali, M., Sabri, M.M.S., Salmi, A., Ewais, D.Y.Z.

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An extended adaptive mechanism of evolutionary based channel assignment via reinforcement by Teo, Kenneth Tze Kin, Yew, Hoe Tung, Lye, Scott Carr Ken, Lim, Kit Guan, Ang, Soo Siang, Khairul Anuar Mohamad, Ali Chekima, Liau, Chung Fan, Aroland Jilui Kiring

“…Initial channel assignment parameters are obtained using self-learning scheme and evolutionary algorithms is used to fine-tune the estimated parameters from reinforcement learning algorithm to optimise the channel assignment problem in wireless mobile networks. …”
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Q-learning based vertical handover decision algorithm in LTE-A two-tier macrocell-femtocell systems / Ammar Bathich by Bathich, Ammar

“…The proposed handover algorithms are validated using the LTE-Sim simulator under an urban environment. …”
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