Deepak Bhatt, D.E.M.E.
Affiliations: | 2014 | Electrical Engineering | The University of Toledo |
Area:
Electronics and Electrical Engineering, Computer Engineering, Computer ScienceGoogle:
"Deepak Bhatt"Parents
Sign in to add mentor| Vijay K. Devabhaktuni | grad student | 2014 | The University of Toledo | |
| (Computer Aided Algorithms Based on Mathematics and Machine Learning for Integrated GPS and INS Land Vehicle Navigation Systems.) | ||||
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Publications
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| Bhatt D, Babu SR, Chudgar HS. (2017) A novel approach towards utilizing Dempster Shafer fusion theory to enhance WiFi positioning system accuracy Pervasive and Mobile Computing. 37: 115-123 |
| Adusumilli S, Bhatt D, Wang H, et al. (2015) A novel hybrid approach utilizing principal component regression and random forest regression to bridge the period of GPS outages Neurocomputing. 166: 185-192 |
| Gummadi J, Bhatt D, Adusumilli S, et al. (2015) Interpolation techniques for modeling and estimating indoor radon concentrations in Ohio: Comparative study Environmental Progress and Sustainable Energy. 34: 169-177 |
| Bhatt D, Aggarwal P, Devabhaktuni V, et al. (2014) A novel hybrid fusion algorithm to bridge the period of GPS outages using low-cost INS Expert Systems With Applications. 41: 2166-2173 |
| Aggarwal P, Bhatt D, Devabhaktuni V, et al. (2013) Dempster Shafer neural network algorithm for land vehicle navigation application Information Sciences. 253: 26-33 |
| Adusumilli S, Bhatt D, Wang H, et al. (2013) A low-cost INS/GPS integration methodology based on random forest regression Expert Systems With Applications. 40: 4653-4659 |
| Yerrabolu P, Mareddy L, Bhatt D, et al. (2013) Correction model based ANN modeling approach for the estimation of radon concentrations in Ohio Environmental Progress. 32: 1223-1233 |
| Bhatt D, Aggarwal P, Bhattacharya P, et al. (2012) An enhanced MEMS error modeling approach based on Nu-Support Vector Regression. Sensors (Basel, Switzerland). 12: 9448-66 |
| Bhatt D, Aggarwal P, Devabhaktuni V, et al. (2012) A new source difference artificial neural network for enhanced positioning accuracy Measurement Science and Technology. 23: 105101 |
| Akkala A, Bhatt D, Devabhaktuni V, et al. (2012) Knowledge-based neural network approaches for modeling and estimating radon concentrations Environmental Progress & Sustainable Energy. 32: 355-364 |