Zobrazeno 1 - 10 of 12 pro vyhledávání: '"G. V. Srinivasa Reddy"'
1
Hydrological Investigations in Red Soils of a Micro Catchment Area for Dugout Farm Pond at UAS Raichur Campus
Autor: Vinutha K., Premanand B. Dashavant, B. Maheshwara Babu, G. V. Srinivasa Reddy, S. R. Balanagoudar
Publikováno v: International Journal of Environment and Climate Change. 13:377-403
Aims: To measure and characterize storm wise runoff for the catchment area of the farm pond and to correlate rainfall intensity and runoff relationship for the catchment area will help to design the appropriate size of the farm pond and waste weirs o
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d27f08202c51f43e9b7d5f8f5bb4bbae
https://doi.org/10.9734/ijecc/2023/v13i61837
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2
Pan Evaporation Estimation Using Artificial Neural Network (ANN) and Fuzzy Logic Models for Raichur Region, Karnataka: A Case Study
Autor: G. Manoj Kumar, B. Maheshwara Babu, Premanand B. Dashavant, G. V. Srinivasa Reddy, Megha
Publikováno v: International Journal of Environment and Climate Change. :3725-3735
Aims: Accurate estimates of evaporation by employing efficient and proven soft computing techniques that involve least number of influencing variables are important to tackle present water crisis. Place and Duration of Study: In the present study, Ar
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::733d45a66e768b3b9cce3eb9e6e96e17
https://doi.org/10.9734/ijecc/2022/v12i111423
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4
Factors affecting groundwater level fluctuation: A case study at Manvi
Autor: M. Nemichandrappa, Prasad S. Kulkarni, G. V. Srinivasa Reddy, C. T. Ramachandra, Megha Kulakarni
Publikováno v: International Journal of Chemical Studies. 8:803-806
An accurate prediction of groundwater level is quite essential for ecological, sustainable development and management of groundwater resources. The soft computing models like ARIMA, ANN, FL, ANFIS and GA have been reported as the promising tools in p
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::910ee57355f22ad2d035f2075904dd87
https://doi.org/10.22271/chemi.2020.v8.i2l.8864
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8
Comparative Study between Wavelet Artificial Neural Network (WANN) and Artificial Neural Network (ANN) Models for Groundwater Level Forecasting
Autor: B. Maheshwara Babu, Anandakumar, U. Satishkumar, G. V. Srinivasa Reddy
Publikováno v: Indian Journal Of Agricultural Research.
Groundwater level fluctuation modeling is a prime need for effective utilization and planning the conjunctive use in any basin.The application of Artificial Neural Network (ANN) and hybrid Wavelet ANN (WANN) models was investigated in predicting Grou
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::63e39c4b61e7c44725855036132f1635
https://doi.org/10.18805/ijare.a-5079
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9
Analysis of regional droughts, magnitudes and comparison over Ballari district
Autor: G. V. Srinivasa Reddy, B. Maheshwara Babu, D. Krishnamurthy, M. Nemichandrappa, Hanumanthappa Ramdurg
Publikováno v: ASIAN JOURNAL OF ENVIRONMENTAL SCIENCE. 10:156-160
Drought generally initiates with the deficit of monsoon rains leading to meteorological drought and if prolonged, affects other sectors dependent on the water for its sustenance resulting in agricultural and hydrological droughts. The present study w
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4f7b0c713991c404fa7c954c88b3a8b5
https://doi.org/10.15740/has/ajes/10.2/156-160
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10
Weekly rainfall variability and probability analysis for resource planning at Hadagali, Karnataka
Autor: M. Nemichandrappa, D. Krishnamurthy, B. Maheshwara Babu, G. V. Srinivasa Reddy, Hanumanthappa Ramdurg
Publikováno v: INTERNATIONAL JOURNAL OF AGRICULTURAL ENGINEERING. 8:255-260
Daily rainfall data of 35 years (1978-2012) of Hadagali were used for weekly analysis to study the variability and the probability level of occurrence. The highest mean weekly rainfall (42.5 mm) was received during 39th SMW. The CV was less than 150
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5e5571b1cf0f9a7568f4d9540e539119
https://doi.org/10.15740/has/ijae/8.2/255-260
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