Search Results - (( model evaluation metric algorithm ) OR ( panel identification system algorithm ))

Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms by Bakar, Abubakar Diwani

“…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). …”
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Improving Accuracy Metric with Precision and Recall Metrics for Optimizing Stochastic Classifier by Hossin, M., Sulaiman, M.N, Mustapha, N., Rahmat, R.W

“…In this study, we propose a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects. …”
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Improving accuracy metric with precision and recall metrics for optimizing stochastic classifier by Hossin, Mohammad, Sulaiman, Md. Nasir, Mustapha, Norwati, O. K. Rahmat, Rahmita Wirza

“…In this study, we propose a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects. …”
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Improving accuracy metric with precision and recall metrics for optimizing stochastic classifier by M., Hossin, M.N., Sulaiman, N., Mustpaha, R.W., Rahmat

“…In this study, we propose a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects.We refer the new evaluation metric as optimized accuracy with recall-precision (OARP). …”
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A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting by Md Salleh N.S., Suliman A., Jorgensen B.N.

Role Minimization As An Optimization Metric In Role Mining Algorithms : A Literature Review by Ahmad, Rabiah, Abd Hamid, Nazirah, Selamat, Siti Rahayu

“…A recent access control model that could accommodate a dynamic structure such as cloud computing can be recognized as role based access control and the role management process of this access control can be identified as role mining.The current trend in role based access control is the role mining problem that can be described as the difficulty to uncover an optimum set of roles from the userpermission assignment.To solve this problem,the researchers have proposed role mining algorithms to produce role set and among the existing algorithms there is an intrinsic topic of the common perception to evaluate the goodness of the generated role set.Eventually,the value of the identified roles could be measured by the preferred metric of optimality namely the number of roles,sizes of userassignment and permission-assignment and Weighted Structural Complexity.Until now, there is some disagreement on the optimization metric but notably many researchers have agreed on the minimization of the number of roles as a solid metric.This paper discusses an overview of the current state-of-the-art on the recent role mining algorithms that focus on role minimization as an optimization metric to evaluate the goodness of the identified roles. …”
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Model predictive control for MPPT of distributed photovoltaic module by Jowalin, Wellfred

“…A conventional P&O technique was design by develop the algorithm to compare the result. A plant using system identification developed as the MPC needs a plant for prediction. …”
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Efficient region of interest based metric learning for effective open world deep face by Faizabadi, Ahmed Rimaz, Mohd Zaki, Hasan Firdaus, Zainal Abidin, Zulkifli, Nik Hashim, Nik Nur Wahidah, Husman, Muhammad Afif

“…To establish the effectiveness, we investigated various threshold finding strategies for five state-of-the-art face recognition algorithms for open world adaptation on different datasets.We also proposed a novel performance evaluation metric for FR algorithms on imbalanced datasets. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

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Scheduling tight deadlines for scientific workflows in the cloud by Bajaher, Awadh Salem Saleh

“…The results show that the PDC performs better in term of success rate metric while the DCCP algorithm has better performance in term of normalized cost metric. …”
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A review of deep learning-based defect detection and panel localization for photovoltaic panel surveillance system by Mohamed Ameerdin, Muhammad Irshat, Jamaluddin, Muhammad Herman, Shukor, Ahmad Zaki, Mohamad, Syazwani

“…YOLO algorithms are utilized for their real-time detection capabilities, allowing for immediate identification and categorization of defects during routine inspections. …”
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Cross-project software defect prediction by Bala, Yahaya Zakariyau, Abdul Samat, Pathiah, Sharif, Khaironi Yatim, Manshor, Noridayu

“…In this work, five research questions covering the classification algorithms, dataset, independent variables, performance evaluation metrics used in CPDP studies, and as well as the performance of individual machine learning classification algorithms in predicting software defects across different software projects were addressed accordingly. …”
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Classification models for higher learning scholarship award decisions by Wirawati Dewi Ahmad, Azuraliza Abu Bakar

“…Each model was evaluated using technical evaluation metric, such contingency table metrics, and accuracy, precision, and recall measures. …”
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OAERP : A Better Measure than Accuracy in Discriminating a Better Solution for Stochastic Classification Training by Hossin, M., Sulaiman, M.N, Mustapha, A., Rahmat , R.W

“…In this study, a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects was proposed. …”
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OAERP: a better measure than accuracy in discriminating a better solution for stochastic classification training by Hossin, Mohammad, Sulaiman, Md. Nasir, Mustapha, Aida, Mustapha, Norwati, O. K. Rahmat, Rahmita Wirza

“…In this study, a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects was proposed. …”
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Heart Attack Prediction with Deep Learning by Syasya Putri binti Mohamad Razauddin

Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…The first experiment revealed that the Algorithm Adaptation framework outperformed Problem Transformation methods across most metrics. …”
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Development Of Performance Evaluation And Prediction Models In Logistics Service And Supply Networks Towards A Sustainable And Robust Supply Chain by Jomthanachai, Suriyan

“…And to utilize the models as tools and metrics for evaluating and predicting supply chain performance.…”
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Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling by Shimailawi, Shatha Abdulhadi Muthana

“…Friedman test using GRG metric shows significant better performance (p-values<0.05) for PACS algorithm compared to benchmark algorithms. …”
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An intermediate significant bit (ISB) watermarking technique using neural networks by Zeki, A., Abubakar, A., Chiroma, H.

“…Many researchers have used these approaches to evaluate their algorithms. These strategies have been used for a long time, however, which unfortunately limits the value of PSNR and NCC in reflecting the strength and weakness of the watermarking algorithms. …”
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