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Ditemukan 3 dari pencarian Anda melalui kata kunci: author="Sunil Saha"
cover
Integrating the artificial intelligence and hybrid machine learning algorithm…
Komentar Bagikan
Sunil SahaAnik Saha

The aim of the current work is to compare susceptibility maps of landslides produced using machine learning techniques i.e. multilayer perception neural nets (MLP), kernel logistic regression (KLR), random forest (RF), and multivariate adaptive regression splines (MARS); novel ensemble approaches i.e. MLP-Bagging, KLR-Bagging, RF-Bagging and MARS-Bagging in the Kurseong-Himalayan region. For th…

Edisi
Vol.3, December 2022
ISBN/ISSN
2666-5441
Deskripsi Fisik
14 hlm PDF, 5.975 KB
Judul Seri
Artificial Intelligence in Geosciences
No. Panggil
551
cover
Ensemble hybrid machine learning methods for gully erosion susceptibility map…
Komentar Bagikan
Sunil SahaJagabandhu Roy

Gully erosion is one of the important problems creating barrier to agricultural development. The present research used the radial basis function neural network (RBFnn) and its ensemble with random sub-space (RSS) and rotation forest (RTF) ensemble Meta classifiers for the spatial mapping of gully erosion susceptibility (GES) in Hinglo river basin. 120 gullies were marked and grouped into four-f…

Edisi
Vol.3, December 2022
ISBN/ISSN
2666-5441
Deskripsi Fisik
18 hlm PDF, 7.028 KB
Judul Seri
Artificial Intelligence in Geosciences
No. Panggil
551
cover
Site suitability for Aromatic Rice cultivation by integrating Geo-spatial and…
Komentar Bagikan
Debabrata SarkarSunil SahaManab MaitraProlay Mondal

The purpose of this work is to assess the soil fertility for Tulaipanji rice cultivation in Kaliyaganj C.D. Block using the Analytic Hierarchy Process (AHP) and Machine learning algorithms along with the field survey data and GIS. A total of 40 soil samples from Tulaipanji rice fields (from 0 to 40 ​cm depth) have been randomly collected for the analysis of the soil health condition. For the …

Edisi
Vol.2, December 2021
ISBN/ISSN
2666-5441
Deskripsi Fisik
13 hlm PDF, 6.223 KB
Judul Seri
Artificial Intelligence in Geosciences
No. Panggil
551