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.

Bibliographische Detailangaben
Hauptverfasser: Aurnab, Aukik, Choudhury, Shaktiman, Ruhan, Shoubhick Roy, Rifaiya Abrar, Shikh Muhammad, Hossain Rabbi, S.M. Riyadh
Weitere Verfasser: Khan, Rubayat Ahmed
Format: Abschlussarbeit
Sprache:English
Veröffentlicht: Brac University 2023
Schlagworte:
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.
Online Zugang:http://hdl.handle.net/10361/19150

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