Search Results - (( model validation _ algorithm ) OR ( whale classification model algorithm ))
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Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem
Published 2023“…The new Binary Whale Optimization Algorithm is integrated with wrapper feature selection and validated on descriptor selection problem to improve Amphetamine-type stimulants drug classification result. …”
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Conference or Workshop Item -
2
Hyperparameter tuned deep learning enabled intrusion detection on internet of everything environment
Published 2022“…Finally, MVO algorithm is exploited with Bidirectional Gated Recurrent Unit (BiGRU) model for classification. …”
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Information fusion and data augmentation with deep features for a deep learning-based baby cry recognition / Zhang Ke
Published 2024“…The Whale optimization algorithm-Variational mode decomposition is used to optimally decompose the baby cry signals. …”
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Thesis -
4
Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm
Published 2024“…This study presents a new approach for ozone level detection through feature selection by the modified Whale Optimization Algorithm (mWOA). This study aims to enhance the accuracy and efficiency of ozone level prediction models by selecting the most informative features from the dataset. …”
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Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm
Published 2024“…This study presents a new approach for ozone level detection through feature selection by the modified Whale Optimization Algorithm (mWOA). This study aims to enhance the accuracy and efficiency of ozone level prediction models by selecting the most informative features from the dataset. …”
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Unleashing the power of Manta Rays Foraging Optimizer: A novel approach for hyper-parameter optimization in skin cancer classification
Published 2025“…The model achieves impressive accuracy and loss metrics (ISIC: 99.43 , 0.0250; PH2: 99.96 , 0.0033; HAM10000: 97.70 , 0.0626), outperforming alternative optimization algorithms such as the Grey Wolf Optimizer (98.33 accuracy, 0.17 loss), Whale Optimization Algorithm (96 accuracy), Grasshopper Optimization Algorithm (97.2 accuracy), Densnet121-MRFO (99.26 accuracy), InceptionV3 with GA (99.9 accuracy), and African Vulture Optimization Algorithm (92.7 accuracy). …”
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Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm
Published 2023“…Lastly, a study of the industrial case was performed as a validation of the developed model and algorithm. An automotive company is selected, and the collected actual data is used for validation purposes. …”
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Thesis -
9
Implementation of New Improved Round Robin (NIRR) CPU scheduling algorithm using discrete event simulation
Published 2015“…The main objective of this research is to validate the NIRR algorithm by developing a comprehensive simulation model using Discrete Event Simulation (DES). …”
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Thesis -
10
Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…The validation test-through correlation analysis was used to validate the model. …”
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Implementation of New Improved Round Robin (NIRR) CPU scheduling algorithm using discrete event simulation
Published 2016“…The main objective of this research is to validate the NIRR algorithm by developing a comprehensive simulation model using Discrete Event Simulation (DES). …”
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Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score
Published 2021“…However, the conversion of a complex form of ML algorithms into a simple statistical model is the prime concern. …”
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Thesis -
13
Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…The validation test-through correlation analysis was used to validate the model. …”
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Performance of Semi Active Lateral Control (SALC) algorithm for semi active suspension system in multibody co-simulation method / M. M. Abdul Majid ...[et al.]
Published 2018“…The experimental data used for simulation model correlation and validation. New controller algorithm (SALC) was than developed in Matlab/Simulink and integrate with correlated vehicle plant model for handling performance validation against passive suspension and Skyhook. …”
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Simplified approach to validate constitutive model formulation of orthotropic materials undergoing finite strain deformation
Published 2016“…The results then established the capability of the proposed formulation and its algorithm implementation before validation against the selected experimental tests can be conducted.…”
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Prediction of Machine Failure by Using Machine Learning Algorithm
Published 2019“…Validation for the model is analyzed by using validation testing data and cross validation. …”
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Final Year Project -
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Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control
Published 2019“…The performance of modified SFS algorithm to train a nonlinear auto-regressive exogenous model (NARX) structure FNNs-based model of the system was then compared with its predecessor and with several well-known metaheuristic algorithms. …”
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System identification using Extended Kalman Filter
Published 2017“…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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Student Project -
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Landslide susceptibility mapping at VAZ watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF)...
Published 2013“…In this study, both MLP and RBF algorithms were used in artificial neural network model. …”
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network
Published 2009“…The model was then fed with new sets of machining parameters to experimentally validate the model’s ability in predicting the cut quality. …”
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