Comparative analysis of machine learning techniques in optimal site selection

Comparative analysis of machine learning techniques in optimal site selection

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

Podrobná bibliografie
Hlavní autoři: Aurnab, Aukik, Choudhury, Shaktiman, Ruhan, Shoubhick Roy, Rifaiya Abrar, Shikh Muhammad, Hossain Rabbi, S.M. Riyadh
Další autoři: Khan, Rubayat Ahmed
Médium: Diplomová práce
Jazyk:English
Vydáno: Brac University 2023
Témata:
Optimal Site Selection (OSS)
Comparative analysis
Boosting and stacking
SVR
Random forest
XGBoost
Ridge regression
Lasso regression
Elasticnet
Convolutional Neural Network (CNN)
Ensemble learning
VGG16
VGG19
ResNet
DenseNet
InceptionV3
Root Mean Squared Error (RMSE)
Mean Squared Error (MSE)
Mean Absolute Error (MAE)
Median Absolute Error (MedAE)
Max error (ME)
Median Absolute Deviation(MAD)
Machine learning.
Artificial intelligence.
On-line přístup:http://hdl.handle.net/10361/19150

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