Browsing by Subject "Machine learning"
Now showing items 1-6 of 6
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Anticipating the Friction Coefficient of Friction Materials used in Automobiles By Means of Machine Learning Without Using a Test lnstrument
(2013)The most important factor for designs in which friction materials are used is the coefficient of friction. The coefficient of friction has been determined taking such variants as velocity, temperature, and pressure into ... -
Developing of a Learning-based System to Assist Treatment Process of Arrhythmia Patients
(2011)The transformation process of the data kept in data warehouse into usable information for decision support system is very important. In this process, it is necessary to reveal the useful data that can meet the needs of the ... -
Developing of a learning-based system to assist treatment process of arrhythmia patients
(2011)The transformation process of the data kept in data warehouse into usable information for decision support system is very important. In this process, it is necessary to reveal the useful data that can meet the needs of the ... -
Gradient boosting for Parkinson's disease diagnosis from voice recordings
(Bmc, 2020)Background Parkinson's Disease (PD) is a clinically diagnosed neurodegenerative disorder that affects both motor and non-motor neural circuits. Speech deterioration (hypokinetic dysarthria) is a common symptom, which often ... -
Modeling and Estimating of Load Demand of Electricity Generated from Hydroelectric Power Plants in Turkey using Machine Learning Methods
(2014)In this study, the electricity load demand, between 2012 and 2021, has been estimated using the load demand of the electricity generated from hydroelectric power plants in Turkey between 1970 and 2011. Among machine learning ... -
Wind speed forecasting using reptree and bagging methods in Kirklareli-Turkey
(Asian Research Publishing Network (ARPN), 2013)In this study, an analysis was performed by examining the wind power potential of Ki{dotless}rklareli province which is in the west of Turkey. Statistical data between 2001 and 2007 was used in this study. The data was ...
