Konu "Machine Learning" için Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering listeleme
Toplam kayıt 6, listelenen: 1-6
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Comparative Performance Analysis of Support Vector Regression and Artificial Neural Network for Prediction of Municipal Solid Waste Generation
(Sage Publications Ltd, 2021)The evolution of machine learning (ML) algorithms provides researchers and engineers with state-of-the-art tools to dynamically model complex relationships. The design and operation of municipal solid waste (MSW) management ... -
Early Software Defects Density Prediction: Training the International Software Benchmarking Cross Projects Data Using Supervised Learning
(Institute of Electrical and Electronics Engineers Inc., 2023)Recent reviews of the literature indicate the need for empirical studies on cross-project defect prediction (CPDP) that would allow aggregation of the evidence and improve predictive performance. Most empirical studies ... -
Exploring the Molecular Interaction of PCOS and Endometrial Carcinoma through Novel Hyperparameter-Optimized Ensemble Clustering Approaches
(Multidisciplinary Digital Publishing Institute (MDPI), 2024)Polycystic ovary syndrome (PCOS) and endometrial carcinoma (EC) are gynecological conditions that have attracted significant attention due to the higher prevalence of EC in patients with PCOS. Even with this proven ... -
A machine learning-based framework for predicting game server load
(Springer, 2020)Server load prediction can be utilized for load-balancing and load-sharing in distributed systems. The use of machine learning (ML) algorithms for load estimation in distributed system applications can increase the ... -
The prediction of the ZnNi thickness and Ni % of ZnNi alloy electroplating using a machine learning method
(Taylor and Francis Ltd., 2021)ZnNi alloy coating is commonly used to enhance the corrosion resistance of steel. The percentage of Ni should be maintained between 12% and 14% in the coating for best corrosion performance. The response surface design ... -
RPINBASE: An online toolbox to extract features for predicting RNA-protein interactions
(Academic Press Inc Elsevier Science, 2020)Feature extraction is one of the most important preprocessing steps in predicting the interactions between RNAs and proteins by applying machine learning approaches. Despite many efforts in this area, still, no suitable ...