Bibhuti Bhusan Sahoo

Closure to “Comparative Evaluation of Machine-Learning Models for Predicting Daily Evapotranspiration in a Naturally Ventilated Greenhouse”

Bibhuti Bhusan Sahoo, Mohammad Najafzadeh, Santosh DT, Thandra Jithendra et autres

in, ir, ca, us (code pays fourni par la source)

Bottom water characteristics and paleoceanographic evolution of Central Southern Pacific Ocean across the Mid-Brunhes Transition

N. Mahanta, Bibhuti Bhusan Sahoo, Sunil K. Das, Sudipto Datta et autres

in (code pays fourni par la source)

Comparative Evaluation of Machine-Learning Models for Predicting Daily Evapotranspiration in a Naturally Ventilated Greenhouse

Bibhuti Bhusan Sahoo, Mohammad Najafzadeh, Santosh DT, Thandra Jithendra et autres

Accurate determination of reference evapotranspiration (ET0) is crucial for optimizing irrigation scheduling in greenhouse environments, ensuring optimal plant growth and resource management. This study aims to identify the most accurate method for predicting ET0 in naturally ventilated greenhouse conditions. Four machine learning …

in, ir, us (code pays fourni par la source)

Evaluation of Lignocellulosic Substrates on Productivity of Pearl Oyster Mushroom (Pleurotus ostreatus)

Niranjan Chinara, Saudamini Swain, Bibhuti Bhusan Sahoo

Among the oyster mushrooms, Pearl oyster mushroom (Pleurotus ostreatus) is one of the important edible mushrooms cultivated in India. It can be grown on different lignocellulosic substrates. However, its productivity depends upon the nature and the composition of the substrates. Therefore, locally …

Water budget assessment at data sparse Eastern Indian catchment: a seasonal perspective

Bibhuti Bhusan Sahoo, Ram Ashish Giri, Mani Bhushan

in (code pays fourni par la source)

A Deep Learning Approach to Predict Surface Soil Wetness and Its Uncertainty Analysis Over the Tel River Basin, India

Sovan Sankalp, Bibhuti Bhusan Sahoo, Sushindra Kumar Gupta, Mani Bhushan et autres

ABSTRACT Surface soil moisture (SSM) refers to the capacity of the top layer of soil to hold moisture. It is an essential part of the budget for surface water. Soil moisture monitoring is crucial to reduce the effects of precipitation deficits and …

in (code pays fourni par la source)

Perspective Chapter: Biopesticides to Produce Zero-Residue Vegetables

Bibhuti Bhusan Sahoo, Amitabh Panda, Swaraj Meher

Vegetables are a vital source of phytonutrients that are essential for human health. However, inadequate availability and phytotoxicity lead to various diseases in our daily lives. Therefore, it is crucial to produce and consume vegetables with minimal or no residues to ensure …

Application of machine learning models in Mahanadi River basin, Odisha for prediction of flood

Shradhanjalee Pradhan, Janhabi Meher, Bibhuti Bhusan Sahoo

Machine learning (ML) models can aid in flood alerts and reduction of its disastrous effect. ML approaches have gained popularity because of their minimal computing demands and rely on observational data. The goal of this study was to develop an ML model …

Late Miocene to Early Pliocene paleoceanographic evolution of the Central South Pacific: A deep-sea benthic foraminiferal perspective

Sunil K. Das, N. Mahanta, Bibhuti Bhusan Sahoo, Raj K. Singh et autres

in, us, de, jp, fr (code pays fourni par la source)

Prediction of groundwater level changes based on machine learning technique in highly groundwater irrigated alluvial aquifers of south-central Punjab, India

Sushindra Kumar Gupta, Sashikanta Sahoo, Bibhuti Bhusan Sahoo, Prashant K. Srivastava et autres

in (code pays fourni par la source)

Review of: "Flood Prediction Using Artificial Neural Networks: A Case Study in Temerloh, Pahang"

Bibhuti Bhusan Sahoo

Potential competing interests: No potential competing interests to declare.

in (code pays fourni par la source)

Improving the forecasting accuracy of monthly runoff time series of the Brahmani River in India using a hybrid deep learning model

Sonali Swagatika, Jagadish Chandra Paul, Bibhuti Bhusan Sahoo, Sushindra Kumar Gupta et autres

Abstract Accurate prediction of monthly runoff is critical for effective water resource management and flood forecasting in river basins. In this study, we developed a hybrid deep learning (DL) model, Fourier transform long short-term memory (FT-LSTM), to improve the prediction accuracy of …

in (code pays fourni par la source)