Search Results - (( model validation system algorithm ) OR ( parameter automation a algorithm ))

Customer analysis with machine vision by Tiong, Wei Jie

“…The study found that the best model is the retrained YOLOv8n, which achieved a false detection rate of 8.16 %, outperforming all the pretrained models. …”
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Adaptive linux-based TCP congestion control algorithm for high-speed networks by Alrshah, Mohamed A.

“…The main contributions of this model are: First, to validate the simulation results of AF-based CCA by comparing them to the numerical results of this model and to the results of NewReno as a benchmark. …”
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Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application by Aminordin, Azmi

“…This study suggests the work to combine the optimization of feature selection and algorithm parameters to achieve higher accuracy and acquire more reliable comparison.…”
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Stereo Camera-Based Aerial Target Geolocation in a Ground-Based Platform Environment by Amir Hilmi Bin Ahmad Azizi

System identification and control of linear electromechanical actuator using PI controller based metaheuristic approach by Abdullah Hashim, Azrul Azim, Abdul Ghani, Nor Maniha, Ahmad, Salmiah, Nasir, Ahmad Nor Kasruddin

“…As for validation, PI-ABC showed similar results in HIL environment with a steady-state error of -0.0314, an overshoot of 5.0007%, a rise time of 1.3805 s, and a settling time of 9.1002 s. …”
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System identification and control of linear electromechanical actuator using PI controller based metaheuristic approach by Azrul Azim, Abdullah Hashim, Nor Maniha, Abdul Ghani, Salmiah, Ahmad, Ahmad Nor Kasruddin, Nasir

“…As for validation, PI-ABC showed similar results in HIL environment with a steady-state error of -0.0314, an overshoot of 5.0007%, a rise time of 1.3805 s, and a settling time of 9.1002 s. …”
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Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system by Ayop Azmi, Nurnajmin Qasrina Ann, Pebrianti, Dwi, Abas, Mohammad Fadhil, Bayuaji, Luhur

“…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper�parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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Real-time oil palm fruit bunch ripeness grading system using image processing techniques by Alfatni, Meftah Salem M.

“…These results are optimal based on the thorns model. A new approach was developed using expert rules-based system. …”
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Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohammad Fadhil, Abas, Bayuaji, Luhur

“…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper-parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm by Abdul Haris, Faranadia

“…The statistical analysis showed a good agreement between manual and automated data on each parameter, with a percentage difference observed between 0.08% and 6.88%. …”
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Development of a Neural-Fuzzy Model for Machinability Data Selection in Turning Process by Kong, Hong Shim

“…A neural-fuzzy model has been developed to represent machinability data selection in turning process. …”
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Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

“…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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Automated real-time electrocardiogram diagnosis based on the modified Pan-Tompkins algorithm for long-term monitoring systems by Gerasimova, Yuliya, Sidi, Fatimah, Ivel, Victor, Avdeyev, Vladimir, Abdullah, Lili Nurliyana, Moldakhmetov, Sayat

“…A modified Pan-Tompkins algorithm for determining the boundaries of the QRS system has been developed. …”
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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. …”

Performance optimization of simultaneous machine and automated guided vehicle scheduling using fuzzy logic controller based genetic algorithm. by Sulaiman, Shamsuddin, Mohd Ariffin, Mohd Khairol Anuar, Badakshian, Mostafa

“…Previously, genetic algorithm (GA) is considered as a heuristic method to solve AGVscheduling problem. …”
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Automated Model Generation Approach Using MATLAB by Xia, Likun

“…An estimation algorithm is then required in order to obtain parameters for these models. …”
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Using simulated annealing algorithm for optimization of quay cranes and automated guided vehicles scheduling by Homayouni, Seyed Mahdi, Tang, Sai Hong, Ismail, Napsiah, Mohd Ariffin, Mohd Khairol Anuar

“…This model minimizes the makespan of all the loading and unloading tasks for a set of cranes in a scheduling problem. Based on the simulated annealing (SA) algorithm, a scheduling method is proposed to solve the problem in a relatively short period of time. …”
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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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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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