Search Results - (( model validation means algorithm ) OR ( rate estimation based algorithm ))*
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Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm
Published 2019“…In conclusion, SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics can be used as models selection algorithms. Additionally, both algorithms are suitable in improving performance of automated models selection procedures. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels
Published 2021“…In the fourth part a deep learning (DL) algorithm of channel estimation for two fad�ing channel models, Tropical and Temperate in the satellite communication system is presented. …”
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Satellite based quantitative rainfall estimation for flash flood forecasting / Wardah Tahir
Published 2008“…In this study, a rainfall estimation algorithm using the information from the geostationary meteorological satellite infrared (IR) images is developed for potential input to a flood forecasting system. …”
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Ant colony optimization and genetic algorithm models for suspended sediment discharge estimation for gorgan-river, Iran
Published 2011“…Therefore, it is still necessary to develop the model for the discharge-sediment relationship. New models based on artificial intelligence models, namely; Ant Colony Optimization (ACO) and Genetic Algorithm (GA) are now being used more frequently to solve optimization problems. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network
Published 2023“…Model validity describes the first sub-objective, which is to solve the complexity of the nonlinear interaction of multiple MEC input variables related to the hydrogen production rate response using artificial neural networks (ANN) before validating the mathematical modeling results by comparing experimental data with the predicted substrate concentration profile and hydrogen production rate profile based on the re-estimated input values of the model parameters using single-objective optimization based on the nonlinear convex method using gradient descent algorithm. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The performance of the algorithm is validated with experimental datasets. …”
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Modeling financial environments using geometric fractional Brownian motion model with long memory stochastic volatility
Published 2018“…All parameters involved in the developed model are estimated by using innovation algorithm. …”
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Subspace Techniques for Brain Signal Enhancement
Published 2009“…This chapter presents a collection of subspace-based techniques derived from other research areas to estimate biomedical signals from human. …”
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Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad
Published 2022“…In addition, the software development based on the suggested method is currently in Technology Readiness Level 4, which means the technology has been validated in the lab. …”
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Modelling and Forecasting the Kuala Lumpur Composite Index Rate of Returns Using Generalised Autoregressive Conditional Heteroscedasticity Models
Published 2004“…The last part of the thesis is concerned with the validation of the model obtained for fitting the GARCH model for the new data set (January 2001-April 2004 or Period IV). …”
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Simulation of COVID-19 outbreaks via graphical user interface (GUI)
Published 2021“…An improved SIRD model was solved via the 4th order Runge-Kutta (RK4) method and 14 unknown parameters were estimated by using Nelder- Mead algorithm and pattern-search technique. …”
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Estimation of microclimate parameters on infestation rate of yellow stem borer (Scirpophaga incertulas) on MR297 rice variety
Published 2023“…In conclusion, the estimation of microclimate parameters on the infestation rate of yellow stem borer on MR297 rice variety in Malaysia to estimate the infestation rate with abiotic factors was the first of its kind for modeling and forecasting the infestation rate of S. …”
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Modeling And Optimization Of Lipase-Catalyzed Synthesis Of Adipate Esters Using Response Surface Methodology And Artificial Neural Network
Published 2010“…A high coefficient of determination (R2) (>0.9) and a low mean absolute error (MAE) and root mean squared error (RMSE) for training, validating and testing data implied the good generalization of the developed models for predicting the reaction yield. …”
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A comparative study on aviation arrival delay prediction using machine learning methods
Published 2023“…Considering the afore-mentioned model building methods for both approaches, ANN model using stepwise regression approach performs the best for flight arrival delay prediction based on F1 score. …”
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A statistical approach for pavement layer moduli backcalculation as a function of traffic speed deflections
Published 2022“…The results revealed an acceptable prediction accuracy for the developed models yielding an average root mean square error (RMSE) of 14.41 for the asphalt layer, 15.12 for the base layer, and 9.50 for the subgrade layer, respectively. …”
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