Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Jagabandhu Roy"'
Autor:
Jagabandhu Roy, Sunil Saha
Publikováno v:
Artificial Intelligence in Geosciences, Vol 3, Iss , Pp 28-45 (2022)
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 Me
Externí odkaz:
https://doaj.org/article/5c3521c7802146248876f709c7dac308
Autor:
Sunil Saha, Raju Sarkar, Jagabandhu Roy, Tusar Kanti Hembram, Saroj Acharya, Gautam Thapa, Dowchu Drukpa
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-23 (2021)
Abstract Landslides are major natural hazards that have a wide impact on human life, property, and natural environment. This study is intended to provide an improved framework for the assessment of landslide vulnerability mapping (LVM) in Chukha Dzon
Externí odkaz:
https://doaj.org/article/88429031e1d44212a13b75c1621965c5
Autor:
Alireza Arabameri, M. Santosh, Sunil Saha, Omid Ghorbanzadeh, Jagabandhu Roy, John P. Tiefenbacher, Hossein Moayedi, Romulus Costache
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 12, Iss 1, Pp 1343-1370 (2021)
Landslides are a form of soil erosion threatening the sustainability of some areas of the world. There is, therefore, a need to investigate landslide rates and behaviour. In this research, we introduced a novel hybrid artificial intelligence approach
Externí odkaz:
https://doaj.org/article/4fceed1ebf704a76ad1009c7d0f9cfcd
Autor:
Jagabandhu Roy, Sunil Saha
Publikováno v:
Geoenvironmental Disasters, Vol 6, Iss 1, Pp 1-18 (2019)
Abstract Landslide is an important geological hazard in the large extent of geo-environment, damaging the human lives and properties. The present work, intends to identify the landslide susceptibility zones for Darjeeling, India, using the ensembles
Externí odkaz:
https://doaj.org/article/8d931adbd370456f989bfb36fbe0aca8
Autor:
Sunil Saha, Jagabandhu Roy, Tusar Kanti Hembram, Biswajeet Pradhan, Abhirup Dikshit, Khairul Nizam Abdul Maulud, Abdullah M. Alamri
Publikováno v:
Water, Vol 13, Iss 19, p 2664 (2021)
The efficiency of deep learning and tree-based machine learning approaches has gained immense popularity in various fields. One deep learning model viz. convolution neural network (CNN), artificial neural network (ANN) and four tree-based machine lea
Externí odkaz:
https://doaj.org/article/b75c64b3494c4d24a649502c244f37d7
Autor:
Alireza Arabameri, Omid Asadi Nalivan, Sunil Saha, Jagabandhu Roy, Biswajeet Pradhan, John P. Tiefenbacher, Phuong Thao Thi Ngo
Publikováno v:
Remote Sensing, Vol 12, Iss 11, p 1890 (2020)
Gully erosion has become one of the major environmental issues, due to the severity of its impact in many parts of the world. Gully erosion directly and indirectly affects agriculture and infrastructural development. The Golestan Dam basin, where soi
Externí odkaz:
https://doaj.org/article/02adf671725a4318a13dddd92298ca99
Publikováno v:
Remote Sensing, Vol 12, Iss 3, p 475 (2020)
This analysis aims to generate landslide susceptibility maps (LSMs) using various machine learning methods, namely random forest (RF), alternative decision tree (ADTree) and Fisher’s Linear Discriminant Function (FLDA). The results of the FLDA, RF
Externí odkaz:
https://doaj.org/article/42fcf43cb24a4cdd9ed2e21f9e748bee
Publikováno v:
Sensors, Vol 20, Iss 5, p 1313 (2020)
Gully erosion is a form of natural disaster and one of the land loss mechanisms causing severe problems worldwide. This study aims to delineate the areas with the most severe gully erosion susceptibility (GES) using the machine learning techniques Ra
Externí odkaz:
https://doaj.org/article/346a4d90b5854624b60c9d30f3452e01
Autor:
David Durjoy Lal Soren, Jagabandhu Roy, Brototi Biswas, Ratnaprabha Jadhav, Ashutosh Singh, Deepak Prasad
Publikováno v:
Forum geografic. :34-43
Publikováno v:
Advances in Space Research. 68:2819-2840
Landslide is a big problem in the mountainous region all over the world. Sikkim Himalayan region is also suffering from landslide problem. This study's main objective was to generate landslide susceptibility map (LSM) considering the hybrid ensemble