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Now showing items 1-10 of 11
Predicting the success of ensemble algorithms in the banking sector
(Igi Global, 2019)
The banking sector, like other service sector, improves in accordance with the customer's needs. Therefore, to know the needs of customers and to predict customer behaviors are very important for competition in the banking ...
Optimal dimensioning of retaining walls using explainable ensemble learning algorithms
(MDPI-Multidisciplinary Digital Publishing Institute, 2022)
This paper develops predictive models for optimal dimensions that minimize the construction cost associated with reinforced concrete retaining walls. Random Forest, Extreme Gradient Boosting (XGBoost), Categorical Gradient ...
Monitoring the rehabilitation progress using a DCNN and kinematic data for digital healthcare
(Institute of Electrical and Electronics Engineers, 2021)
Monitoring the progress of patients during the rehabilitation process after an operation is beneficial for adjusting care and medical treatment in order to improve the patient's quality of life. The supervised methods used ...
Classification of brain electrophysiological changes in response to colour stimuli
(Springer, 2021)
In this study, the classification of ongoing brain activity occurring as a response to colour stimuli was managed and reported. Until now, the classification of the seen colour from brain electrical signals has not been ...
Artificial intelligence and machine learning applications in agricultural supply chain: a critical commentary
(Fresenius Environmental Bulletin, 2021)
Integration of AI and ML technologies in the agricultural supply chain (ASC) is revolutionalizing, the domain by bringing in robust monitoring and prediction as well as quick decision-making abilities. A comprehensive ...
Optimum design of cylindrical walls using ensemble learning methods
(MDPI-Multidisciplinary Digital Publishing Institute, 2022)
The optimum cost of the structure design is one of the major goals of structural engineers. The availability of large datasets with preoptimized structural configurations can facilitate the process of optimum design ...
Efficiency of deep neural networks for joint angle modeling in digital gait assessment
(Springer Open, 2021)
Reliability and user compliance of the applied sensor system are two key issues of digital healthcare and biomedical informatics. For gait assessment applications, accurate joint angle measurements are important. Inertial ...
Application of machine learning methods for pallet loading problem
(MDPI-Multidisciplinary Digital Publishing Institute, 2021)
Because of continuous competition in the corporate industrial sector, numerous companies are always looking for strategies to ensure timely product delivery to survive against their competitors. For this reason, logistics ...
Sonlu elemanlar analizi ile cerrahi destekli hızlı maksiller genişletmede tedavi protokollerinin değerlendirilmesi
(2023)
Joint moments during gait provide valuable information for clinical decision-making in patients with cerebral
palsy (CP). Joint moments are calculated based on ground reaction forces (GRF) using inverse dynamics ...
Machine learning-based prediction of joint moments based on kinematics in patients with cerebral palsy
(Journal of Biomechanics, 2023)
Joint moments during gait provide valuable information for clinical decision-making in patients with cerebral
palsy (CP). Joint moments are calculated based on ground reaction forces (GRF) using inverse dynamics ...