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Your search keyword '"Reddy, G. Sreenivasa"' showing total 9 results
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9 results on '"Reddy, G. Sreenivasa"'

4. Artificial intelligence revolution in supply chain management.

Author

Basha, Md. Shaik Amzad, Sucharitha, M. Martha, Reddy, G. Sreenivasa, and Uma Devi, A.

Subjects
SUPPLY chain management, ARTIFICIAL intelligence, TECHNOLOGICAL innovations, PRIVATE sector, SUPPLY chains
Abstract

Artificial Intelligence (AI) is a buzzword everywhere in every domain, as it is an emerging technology in all business sectors. It is essential for achieving productivity, business benefits, less human efforts in the required business sectors instead of a large workforce and many more artificial intelligence applications that are scaling up with large scale business sectors. AI capacity to identify the trade patterns, the study's business occurrence, and analyze the information. AI is necessary for today's life and as well as for upcoming generations. Artificial intelligence helps to resolve the most complex problems and difficult situations where humans have not achieved so far, as it is the artificial brainpower of humans. We have seen technological changes happening faster and progressively by AI. The supply chain vastly gained from interest and investments in AI. The digital supply chain initiation, a shift in manufacturing is up and running. Advantageous supply chain management is essential in business sectors, customers, and governments. A combination of Artificial intelligence and supply chain management is put together in making decisions. This article will discuss the overview of AI advancements in supply chain management end-to-end processes. We also reviewed the supply chain operations using AI. [ABSTRACT FROM AUTHOR]

Published
2023
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5. Ground-water potential evaluation of West Godavari District, Andhra Pradesh State, India - a GIS approach

Author

Kamaraju, M.V.V., Bhattacharya, A., Reddy, G. Sreenivasa, Rao, G. Chandrasekhar, Murthy, G.S., and Rao, T. Ch. Malleswara

Subjects
Water, Underground -- Information management -- Methods -- Usage, Geographic information systems -- Usage, Prospecting -- Methods -- Usage, Earth sciences, Company systems management, Geographic information system, Usage, Information management, Methods
Abstract

Introduction With the introduction of remote sensing technology, the ground-water resources of a region can be mapped efficiently utilizing the derived thematic information such as geomorphology, geology, geological structure, and [...]

Published
1996

8. Voltage Profile improvement and power loss reduction for Constant Power type of Loads

Author

kumar, S.Anil, Naidu, B.Amar nath, Reddy, G.V.Subba, Reddy, G. Sreenivasa, kumar, S.Anil, Naidu, B.Amar nath, Reddy, G.V.Subba, and Reddy, G. Sreenivasa

Abstract

The load flow calculation mainly involves for calculating the voltages at each load points and real and reactive power losses across each branch. The classical constant power load model is typically used in power flow studies of transmission or distribution Systems; however, the actual load of a distribution system cannot just be modeled using constant power models, requiring the use of constant current, constant impedance, exponential or a mixture of all these load models to accurately represent the load. This paper presents a study of voltage profile improvement and power loss reduction for constant power type of load model. Keywords: Distribution systems, Load flow, static load models, voltage profile, and power loss.

Published
2014

9. Remote sensing and GIS for locating favourable zones of lead-zinc-copper mineralization in Rajpura-Dariba area, Rajasthan, India.

Author

Srivastav, S. K., Bhattacharya, A., Kamaraju, M. V. V., Reddy, G. Sreenivasa, Shrimal, A. K., Mehta, D. S., List, F. K., and Burger, H.

Subjects
MINES & mineral resources, REMOTE sensing, GEOGRAPHIC information systems
Abstract

This paper reports the results of a pilot study carried out in RajpuraDariba area, Rajasthan, for locating favourable zones of lead-zinc-copper (Pb-Zn-Cu) mineralization using remote sensing, Geographical Information System (GIS) and geostatistical modelling techniques. Remotely sensed data, both aerial and satellite, were used to update the existing geological map. ATLAS GIS software and multivariate geostatistical techniques were used to analyse and integrate different types of geological and geophysical datasets. The Favourability Index (FI) maps prepared during this study show the occurrence of three favourable zones for Pb-Zn-Cu mineralization. They are: (i) around and north of Rawan ka Khera; (ii) isolated spots between Ruppura and Bhupalsagar; and (iii) north of Dhani. Selective geochemical sampling and resistivity profiling carried out in these favourable zones indicated the presence of geochemical anomalies (anomalous concentrations of Zn and Cu) and low/moderate resistivity zones, respectively. Recent drilling carried out by the Department of Mines and Geology (DMG), Rajasthan, at about 2.5 km north of Rawan ka Khera (one of the predicted favourable zones) indicated evidence of Cu mineralization at a depth of about 70 m. [ABSTRACT FROM AUTHOR]

Published
2000
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