Raja Das
VIT University
20 Papers
59 Citations
Raja Das is an academic researcher from VIT University. The author has contributed to research in topics: Artificial neural network & Electrical discharge machining. The author has an hindex of 10, co-authored 20 publications. Previous affiliations of Raja Das include Purushottam Institute of Engineering & Technology.
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Papers
Validation of artificial neural network models for predicting biochemical markers associated with male infertility.
A.S. Vickram,A. Rao Kamini,Raja Das,M. Ramesh Pathy,R. Parameswari,K. Archana,T.B. Sridharan +6 more
TL;DR: Back propagation neural network model BPNN can be used to predict biochemical parameters for the proper diagnosis of male infertility in assisted reproductive technology (ART) centres using semen samples collected for this research.
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Fuzzy logic controller based maximum power point tracking for PV system
S. Narendiran,Sarat Kumar Sahoo,Raja Das,Ashwin Kumar Sahoo +3 more
- 17 Mar 2016
TL;DR: In this article, a fuzzy logic controller (FLC) based maximum power point tracking (MPPT) method for the PV system under constant and varying climatic conditions is proposed. But the performance of fuzzy logic with various membership function (MF) is analyzed to optimize the MPPT.
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Estimation of MHD boundary layer slip flow over a permeable stretching cylinder in the presence of chemical reaction through numerical and artificial neural network modeling
P. Bala Anki Reddy,Raja Das +1 more
TL;DR: In this paper, a numerical method is implemented to approximate the flow of heat and mass transfer characteristics as a function of some input parameters, explicitly the curvature parameter, magnetic parameter, permeability parameter, velocity slip, Grashof number, solutal Grashoff number, Prandtl number, temperature exponent, Schmidt number, concentration exponent and chemical reaction parameter.
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Recurrent neural network estimation of material removal rate in electrical discharge machining of AISI D2 tool steel
Mohan Kumar Pradhan,Raja Das +1 more
- 01 Mar 2011
TL;DR: In this article, an Elman network is used for the prediction of material removal rate (MRR) in electrical discharge machining (EDM), which can be used to model non-linear dynamic systems.
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Bioleaching of heavy metals from spent batteries using Aspergillus nomius JAMK1
TL;DR: In this article, Aspergillus nomius was identified as a potential strain for heavy metals uptake from aqueous solution as well as electronic waste and the activity of A. nomius JAMK1 in bioleaching of metals from spent batteries was studied and analyzed using AAS, X-ray diffraction, SEM and EDAX.
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