مشروع البحث: APPLICATION OF MACHINE LEARNING AND DEEP LEARNING TECHNIQUES TO PREDICT MISSING PETROPHYSICAL DATA
تحميل...
المساهمين
الممولين
رقم التعريف
776
الباحث
سكينة علي عبد السلام عاشور
الوصف
The effectiveness of all machine learning models used in this research to predict missing logs has been proved. However, there is a slight difference in the prediction accuracy between these models. The prediction ability of the random forest algorithm leads in this research with a prediction accuracy of up to 99%. Then it is followed by the decision tree and the k-nearest neighbor algorithms. In respect of deep learning models, the ability of the model using the RELU activation function is superior to its counterparts by prediction accuracy of 99%, followed by the model using the GELU activation function, and the model using the SWISH.
الكلمات الدالة
APPLICATION OF MACHINE LEARNING AND DEEP