Zobrazeno 1 - 10
of 3 097
pro vyhledávání: '"K. Srinivasa"'
Publikováno v:
Journal of Hydroinformatics, Vol 26, Iss 5, Pp 972-997 (2024)
The present study aims to evaluate the potentiality of Bidirectional Long Short-Term Memory (Bi-LSTM), Convolutional Neural Networks (CNNs), eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM), and Random Forest (RF) for predi
Externí odkaz:
https://doaj.org/article/cedd6a384bc9468bbbdca5fb5e2d1cc6
Autor:
Rishith Kumar Vogeti, Rahul Jauhari, Bhavesh Rahul Mishra, K. Srinivasa Raju, D. Nagesh Kumar
Publikováno v:
Journal of Water and Climate Change, Vol 15, Iss 2, Pp 832-848 (2024)
The present study analyzes the capability of convolutional neural network (CNN), long short-term memory (LSTM), CNN-LSTM, fuzzy CNN, fuzzy LSTM, and fuzzy CNN-LSTM to mimic streamflow for Lower Godavari Basin, India. Kling–Gupta efficiency (KGE) wa
Externí odkaz:
https://doaj.org/article/44716bc3c3cb450c85b3a65366fff110
Autor:
Bhavesh Rahul Mishra, Rishith Kumar Vogeti, Rahul Jauhari, K. Srinivasa Raju, D. Nagesh Kumar
Publikováno v:
Water Science and Technology, Vol 89, Iss 3, Pp 613-634 (2024)
The present study investigates the ability of five boosting algorithms, namely Adaptive Boosting (AdaBoost), Categorical Boosting (CatBoost), Light Gradient Boosting (LGBoost), Natural Gradient Boosting (NGBoost), and eXtreme Gradient Boosting (XGBoo
Externí odkaz:
https://doaj.org/article/cb0fd0fc262143b1a26ebf26a89cea5c
Autor:
M. Kokila, K. Srinivasa Reddy
Publikováno v:
IEEE Access, Vol 12, Pp 134521-134540 (2024)
Internet of Things (IoT) has more security issues due to the data being shared in an open platform. Integrating blockchain into IoT for security is a new development in computational communication systems. However, attackers are adapting their method
Externí odkaz:
https://doaj.org/article/84753f0dee1141b9ad9af5d8b9d34ff9
Autor:
Rishith Kumar Vogeti, K. Srinivasa Raju, D. Nagesh Kumar, Advani Manish Rajesh, S. V. Somanath Kumar, Yashraj Santosh Kumar Jha
Publikováno v:
Journal of Water and Climate Change, Vol 14, Iss 9, Pp 3150-3165 (2023)
Soil Water Assessment Tool (SWAT), Hydrologic Engineering Center-Hydrologic Modelling System (HEC-HMS), and Hydrologic Simulation Program Fortran (HSPF) are explored for streamflow simulation of Lower Godavari Basin, India. The simulating ability of
Externí odkaz:
https://doaj.org/article/61e5406602494119b83aeb10bc442c03
Publikováno v:
Journal of Water and Climate Change, Vol 14, Iss 7, Pp 2150-2163 (2023)
Urban floods have been highly prominent natural disasters occurring in catchments across the globe, causing financial loss and damage to buildings. This necessitates effective and sustainable mitigation mechanisms. In this context, flood-susceptibili
Externí odkaz:
https://doaj.org/article/6c2b38f3557c43ac86b5a216d5b59dbd
Publikováno v:
H2Open Journal, Vol 5, Iss 4, Pp 670-685 (2022)
The present study applies three Machine Learning Algorithms, namely, Bi-directional Long Short-Term Memory (Bi-LSTM), Wavelet Neural Network (WNN), and eXtreme Gradient Boosting (XGBoost), to assess their suitability for streamflow projections of the
Externí odkaz:
https://doaj.org/article/2a9a3a2e2d0e48fb89a5b5171552c6c0
Publikováno v:
Journal of Water and Climate Change, Vol 13, Iss 11, Pp 3934-3950 (2022)
The present work aims to identify the best hydrological model structure suitable for the Lower Godavari River Basin, India, that forecasts streamflows. An extended version of the Framework for Understanding Structural Errors (FUSE), termed E-FUSE, is
Externí odkaz:
https://doaj.org/article/ac3b53e9da8c4044ba6c322589b80e45
Autor:
G. Pratibha, M. Manjunath, B. M. K. Raju, I. Srinivas, K. V. Rao, Arun K. Shanker, J. V. N. S. Prasad, M. Srinivasa Rao, Sumanta Kundu, A. K. Indoria, Upendra Kumar, K. Srinivasa Rao, Shivakumar Anna, Ch. Srinivasa Rao, V. K. Singh, A. K. Biswas, S. K. Chaudhari
Publikováno v:
Frontiers in Microbiology, Vol 14 (2023)
Soil microbial communities are important drivers of biogeochemical cycling of nutrients, organic matter decomposition, soil organic carbon, and Greenhouse gas emissions (GHGs: CO2, N2O, and CH4) and are influenced by crop and soil management practice
Externí odkaz:
https://doaj.org/article/cb85b0e8bce6482f9b97328b032aa0bf
Publikováno v:
Water Supply, Vol 22, Iss 3, Pp 3178-3194 (2022)
Water Distribution Network(s) (WDN) design is gaining prominence in the urban planning context. Several factors that play a significant role in design are uncertainty in data, non-linear relation of head loss & discharge, combinatorial nature of the
Externí odkaz:
https://doaj.org/article/26f6498e15ca44138ecbf49a437c95c8