Search Results - (( java application stemming algorithm ) OR ( model validation process algorithm ))

Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models by Quadros, Jaimon Dennis, Khan, Sher Afghan, Aabid, Abdul, Baig, Muneer

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Simplified approach to validate constitutive model formulation of orthotropic materials undergoing finite strain deformation by Mohd Nor, Mohd Khir, Ma`at, Norzarina

“…The validation process must be systematically conducted by stages from simple to complex behaviours. …”
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System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Prediction of Machine Failure by Using Machine Learning Algorithm by Fakhrurazi, Nur Amalina

“…Validation for the model is analyzed by using validation testing data and cross validation. …”
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Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

“…The validation test-through correlation analysis was used to validate the model. …”

An experimental validation and optimisation tool path strategy for thin walled structure by Alsultaney, Hazem K., Mohd Ariffin, Mohd Khairol Anuar, Baharudin, B. T. Hang Tuah, Ali, Aidy, Mustapha, Faizal

“…The target was to develop models which mimic the actual cutting process using the finite element method (FEM), to validate the developed tool path strategy algorithm with the actual machining process and to programme the developed algorithm into the software. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

“…The validation test-through correlation analysis was used to validate the model. …”
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Optimization of multi-holes drilling toolpath using tiki-taka algorithm by Norazlina, Abdul Rahman

“…The study aims to model the MDMT toolpath using the Traveling Salesman Problem (TSP) concept, apply TTA to optimize this model, and validate the model and algorithm through machining experiments on this problem. …”
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Predicting bankruptcy using ant colony optimization / Nur Syafiqah Abdul Ghani by Abdul Ghani, Nur Syafiqah

“…To achieve the set objectives, this research is conducted through three-phase of research activities which are Data pre-processing, Model Development, and Model Validation. …”
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A self-adaptive agent-based simulation modelling framework for dynamic processes by Ling, Loo Yim, Dr.

“…Key parameters for dynamic processes of different domains were formulated for the construction of self-adaptive simulation algorithms and modelling. …”

SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

“…The SURE-Autometrics is also validated using two sets of real data by comparing the forecast error measures with five model selection algorithms and three non-algorithm procedures. …”
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Optimization of multi-holes drilling path using particle swarm optimization by Najwa Wahida, Zainal Abidin

“…One way to improve the multi-hole drilling is by optimising the tool path in the process. This research aims to model and optimise multi-hole drilling problems using Particle Swarm Optimisation (PSO) algorithm. …”
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Adaptive-model based self-tuning generalized predictive control of a biodiesel reactor / Ho Yong Kuen by Ho, Yong Kuen

“…Several RLS algorithms were screened and the Variable Forgetting Factor Recursive Least Squares (VFF-RLS) algorithm was selected to capture the dynamics of the process online for the purpose of model adaptation in the controller. …”
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Improvement real-time detection of moving vehicle in a dynamic scene using shadow removal method / Khairul Azman Ahmad, Mohd Halim Mohd Noor,Mohamad Adha Mohamad Idin by Ahmad, Khairul Azman, Mohd Noor, Mohd Halim, Mohamad Idin, Mohamad Adha

“…There are four major steps in a background subtraction algorithm, which are pre-processing, background modeling, foreground detection, and data validation. …”
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A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model by Ouwabunmi, Babalola AbdulHafeez

“…While the focus was on comparing standalone and hybrid models, the study identifies opportunities for future benchmarking against external tools to further validate its contributions. …”
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A graphical user interface application for continuous-time identification of dynamical system by Rahmat, Mohd. Fua'ad, Omar, Rosli, Jamaluddin, Hishamuddin

“…A stepby-step instruction on how to use the GUI employed in the study is also presented. A validation process had been implemented using cross validation process. …”
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Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan by Hamdan, Ezaryf

“…The success of this project is evaluated using various metrics, including prediction accuracy, precision, recall, and F1 score. Cross-validation techniques are employed to validate the model's performance and ensure robustness. …”
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Mathematical modelling of mass transfer in multi-stage rotating disc contactor column by Arshad, Khairil Anuar, Talib, Jamalludin, Maan, Normah

“…The existing mass transfer model with constant boundary condition does not accurately represent the mass transfer process. …”
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Modeling And Optimization Of Physical Vapour Deposition Coating Process Parameters For Tin Grain Size Using Combined Genetic Algorithms With Response Surface Methodology by Mohamad Jaya, Abdul Syukor, Muhamad, Mohd Razali, Abd Rahman, Md Nizam, Mohammad Jarrah, Mu'ath Ibrahim, Hasan Basari, Abd Samad

“…Additionally,analysis of variance(ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters, genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively.…”
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Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm by Rashid, Roslina, Jamaluddin, Hishamuddin, Saidina Amin, Nor Aishah

“…To estimate and validate the model parameters, experimental works involving hydrolysing tapioca starch were conducted. …”
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