Search Results - hyper-((parameters estimation) OR (parameter estimation))

Bayesian estimation of time to failure distributions based on skew normal degradation model : an application to GaAs laser degradation data by Laila Naji Ba Dakhn, Mohd Aftar Abu Bakar, Kamarulzaman Ibrahim

“…In this paper, the Bayesian method which involves informative and weakly informative priors are considered to estimate the parameters and percentiles of the time to failure distribution. …”
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Estimation of the Regularisation Parameter in Huber-MRF for Image Resolution Enhancement by Sakinah Ali Pitchay, Kaban, A

Hierarchical Bayesian Spatial Models for Disease Mortality Rates by Mohamed Elobaid, Rafida

“…Using the MCMC method, particular sets of prior densities over the space of possible relative risks parameters and hyper-parameters were adopted for each model. …”
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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm by Lipu M.S.H., Hannan M.A., Hussain A., Saad M.H.M., Ayob A., Muttaqi K.M.

Numerical Modelling for Prediction of Suspended Sediment Concentration in Bidor River by Abdul Kadir, Munira Malim

“…Nowadays, improvement of artificial intelligence, as an estimator for hydrological phenomenon has generated an abundant change in estimations. …”
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Estimation of the regularisation parameter in Huber-MRF for image resolution enhancement by Sakinah Ali Pitchay, Kab�n A.

State-of-Charge Estimation of Li-ion Battery at Variable Ambient Temperature with Gated Recurrent Unit Network by Hannan M.A., How D.N.T., Mansor M., Lipu M.S.H., Ker P.J., Muttaqi K.M.

“…Charging (batteries); Deep learning; Learning systems; Lithium compounds; Lithium-ion batteries; Long short-term memory; Multilayer neural networks; Temperature; Empirical evaluations; Experiment set-up; Hyper-parameter; Learning methods; Multi layer perceptron; Simple recurrent networks; State of charge; State-of-charge estimation; Battery management systems…”

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.

“…However, proper selection of RFR architecture and hyper-parameters combination remains a key issue to be explored. …”

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.

“…Battery management systems; Charging (batteries); Computer architecture; Digital storage; Heuristic methods; Lithium-ion batteries; Long short-term memory; Temperature measurement; Trees (mathematics); Bidirectional gated recurrent unit; Computational modelling; Deep learning; GRU; Hyper-parameter; Learning models; Optimisations; Parzen estimators; State-of-charge estimation; States of charges; Optimization…”

Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Ayob A., Saad M.H.M., Muttaqi K.M.

A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources by Ahmadipour M., Ali Z., Ramachandaramurthy V.K., Ridha H.M.

“…To ensure fair comparisons, parameter configurations for all algorithms are automated using the parameter tuning tool iterated racing (irace). …”

Comparative Parametric Numerical Simulations Of Materials Used As Liners In The Explosively Formed Projectiles (EFPs) by G., Hussain, K., Sanaullah

“…Numerical simulations are carried out using AUTODYN 2D hydrocode to study effects of liner’s materials on the shape, velocity, traveled distance, time, pressure, internal energy, temperature, yield stress, divergence or stability, density, compression, and length to diameter (L/D) ratio of EFPs. These parameters are estimated at the instants of maximum as well as at stable velocities. …”
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River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network by Zanial W.N.C.W., Malek M.B.A., Reba M.N.M., Zaini N., Ahmed A.N., Sherif M., Elshafie A.

“…Finding the best value for the hyper-parameters is one of the problems with machine learning algorithms, which have lately been adopted by many academics. …”

Development of novel high damping rubber damper for dynamic energy dissipation under direct axial cyclic load / Teh Tzyy Wooi by Teh , Tzyy Wooi

“…An empirical formula is derived to enable structural designers to estimate the mechanical properties of the tested damper. …”
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Knowledge Transfer Of Aedes Larvae Control System For Dengue Outbreak To A Local Authority Company by Ghazali, Rozaimi, Sulaima, Mohamad Fani, Ab. Ghani, Mohd Ruddin, Othman, Md Nazri, Jali, Mohd Hafiz

“…Besides, the pre-trained model of the Common Object in the Context dataset has been applied in this training, where the hyper-parameter fine-tune configuration has been implemented in this study. …”
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Aedes Aegypti Larvae Detection System Based On Convolution Neural Network Via Transfer Learning by Mohd Fuad, Mohamad Aqil

“…Besides, the pre-trained model of the Common Object in the Context dataset has been applied in this training, where the hyper-parameter fine-tune configuration has been implemented in this study. …”
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