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Pritam Anand
Pritam Anand
Assistant Professor, Dhirubhai Ambani Institute of Information and Communication Technology
Dirección de correo verificada de ieee.org - Página principal
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Wavelet transform and variants of SVR with application in wind forecasting
HS Dhiman, P Anand, D Deb
Innovations in Infrastructure: Proceedings of ICIIF 2018, 501-511, 2018
352018
A heuristic technique to detect phishing websites using TWSVM classifier
RS Rao, AR Pais, P Anand
Neural Computing and Applications 33 (11), 5733-5752, 2021
332021
A ν-twin support vector machine based regression with automatic accuracy control
R Rastogi, P Anand, S Chandra
Applied Intelligence 46, 670-683, 2017
332017
A class of new support vector regression models
P Anand, R Rastogi, S Chandra
Applied Soft Computing 94, 106446, 2020
282020
A new asymmetric ϵ-insensitive pinball loss function based support vector quantile regression model
P Anand, R Rastogi, S Chandra
Applied Soft Computing 94, 106473, 2020
252020
Large-margin distribution machine-based regression
R Rastogi, P Anand, S Chandra
Neural Computing and Applications 32 (8), 3633-3648, 2020
242020
Sparse support vector machine with pinball loss
M Tanveer, S Sharma, R Rastogi, P Anand
Transactions on Emerging Telecommunications Technologies 32 (2), e3820, 2021
162021
-norm Twin Support Vector Machine-based Regression
R Rastogi, P Anand, S Chandra
Optimization 66 (11), 1895-1911, 2017
72017
Improvement over pinball loss support vector machine
P Anand, R Rastogi, S Chandra
arXiv preprint arXiv:2106.01109, 2021
52021
A new asymmetric -insensitive pinball loss function based support vector quantile regression model
P Anand, R Rastogi, S Chandra
arXiv preprint arXiv:1908.06923, 2019
52019
Time efficient variants of twin extreme learning machine
P Anand, A Bharti, R Rastogi
Intelligent Systems with Applications 17, 200169, 2023
42023
A - support vector quantile regression model with automatic accuracy control
P Anand, R Rastogi, S Chandra
arXiv preprint arXiv:1910.09168, 2019
42019
Generalized—Loss Function-Based Regression
P Anand, R Rastogi, S Chandra
Machine intelligence and signal analysis, 395-409, 2018
42018
A combined reward-penalty loss function based extreme learning machine for binary classification
P Anand, A Bharti
2019 Second International Conference on Advanced Computational and …, 2019
32019
A privacy-preserving twin support vector machine classifier for vertical partitioned data
P Anand, JP Pandey, R Rastogi, S Chandra
Computational Intelligence: Theories, Applications and Future Directions …, 2019
32019
Support vector regression via a combined reward cum penalty loss function
P Anand, R Rastogi, S Chandra
arXiv preprint arXiv:1904.12331, 2019
22019
A combined reward-penalty loss function based support vector machine
P Anand
2018 International CET Conference on Control, Communication, and Computing …, 2018
22018
Huber SVR-Based Hybrid Models for Significant Wave Height Forecasting Using Buoy Sensors
P Anand, S Jain, R Mishra
IEEE Sensors Letters 7 (12), 1-4, 2023
2023
Tube Loss: A Novel Approach for High Quality Prediction Interval Estimation
P Anand, T Bandyopadhyay, HM Savaliya, S Chandra
2023
New improved wave hybrid models for hourly significant wave height forecasting
P Anand, S Jain, H Savaliya
IEEE Access, 2023
2023
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