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プロフィール詳細
Dr. Bibhuti Bhusan S.に依頼
India
Data analyst, ETL expert, Predictive modeling, Remote sensing and gis expert, expert on Python and R, Scientific writing
プロフィール概要
専門分野
サービス
Writing
Technical Writing,
Copywriting,
Newswriting
Research
Market Research,
User Research,
Meta-Research,
Gap Analysis,
Gray Literature Search,
Systematic Literature Review
Consulting
Scientific and Technical Consulting
Data & AI
Predictive Modeling,
Statistical Analysis,
Data Visualization,
Big Data Analytics,
Data Processing,
Data Insights
職務経験
Associate Professor
MVR College of Engineering and Technology
12月 2018 - 現在 
学歴
PhD Research Scholar (Civil Engineering)
National Institute of Technology Patna
6月 2015 - 現在
認定資格
- 認定資格の詳細は未入力です。
出版物
JOURNAL ARTICLE
Bibhuti Bhusan Sahoo, Sovan Sankalp, Sanat Nalini Sahoo (2021). Deep learning models' comparable assessment and uncertainty analysis for diurnal temperature range (DTR) predictions over indian urban cities . Results in Engineering.
Bibhuti Bhusan Sahoo, Ramakar Jha(2020). Assessment of low flow trends and change point detection in Mahanadi River basin, India . Sustainable Water Resources Management. 6. (5). Springer Science and Business Media {LLC}
Bibhuti Bhusan Sahoo, Ramakar Jha, Anshuman Singh, Deepak Kumar(2020). Bivariate low flow return period analysis in the Mahanadi River basin, India using copula . International Journal of River Basin Management. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 1--10. Informa {UK} Limited
Bibhuti Bhusan Sahoo, Ramakar Jha, Anshuman Singh, Deepak Kumar(2019). Long short-term memory (LSTM) recurrent neural network for low-flow hydrological time series forecasting . Acta Geophysica. 67. (5). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 1471--1481. Springer Science and Business Media {LLC}
BIBHUTI BHUSAN SAHOO, Abinash Mohanta, KANHU PATRA (2018). Anticipate Manning’s Coefficient in Meandering Compound Channels . Hydrology.
Bibhuti Bhusan Sahoo, Ramakar Jha, Anshuman Singh, Deepak Kumar(2018). Application of Support Vector Regression for Modeling Low Flow Time Series . KSCE Journal of Civil Engineering. Springer Nature
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