Deep learning framework to forecast electricity demand J Bedi, D Toshniwal Applied energy 238, 1312-1326, 2019 | 440 | 2019 |
Hybrid prediction model for type-2 diabetic patients BM Patil, RC Joshi, D Toshniwal Expert systems with applications 37 (12), 8102-8108, 2010 | 277 | 2010 |
Impact of lockdown measures during COVID-19 on air quality–A case study of India P Kumari, D Toshniwal International Journal of Environmental Health Research 32 (3), 503-510, 2022 | 232 | 2022 |
A data mining approach to characterize road accident locations S Kumar, D Toshniwal Journal of Modern Transportation 24, 62-72, 2016 | 226 | 2016 |
Deep learning models for solar irradiance forecasting: A comprehensive review P Kumari, D Toshniwal Journal of Cleaner Production 318, 128566, 2021 | 221 | 2021 |
A data mining framework to analyze road accident data S Kumar, D Toshniwal Journal of Big Data 2, 1-18, 2015 | 199 | 2015 |
Impact of lockdown on air quality over major cities across the globe during COVID-19 pandemic P Kumari, D Toshniwal Urban climate 34, 100719, 2020 | 197 | 2020 |
Empirical mode decomposition based deep learning for electricity demand forecasting J Bedi, D Toshniwal IEEE access 6, 49144-49156, 2018 | 196 | 2018 |
Extreme gradient boosting and deep neural network based ensemble learning approach to forecast hourly solar irradiance P Kumari, D Toshniwal Journal of Cleaner Production 279, 123285, 2021 | 185 | 2021 |
Long short term memory–convolutional neural network based deep hybrid approach for solar irradiance forecasting P Kumari, D Toshniwal Applied Energy 295, 117061, 2021 | 150 | 2021 |
Association rule for classification of type-2 diabetic patients BM Patil, RC Joshi, D Toshniwal 2010 second international conference on machine learning and computing, 330-334, 2010 | 142 | 2010 |
Feature based summarization of customers’ reviews of online products K Bafna, D Toshniwal Procedia Computer Science 22, 142-151, 2013 | 130 | 2013 |
Deep learning-based road damage detection and classification for multiple countries D Arya, H Maeda, SK Ghosh, D Toshniwal, A Mraz, T Kashiyama, ... Automation in Construction 132, 103935, 2021 | 126 | 2021 |
Global road damage detection: State-of-the-art solutions D Arya, H Maeda, SK Ghosh, D Toshniwal, H Omata, T Kashiyama, ... 2020 IEEE International Conference on Big Data (Big Data), 5533-5539, 2020 | 120 | 2020 |
RDD2020: An annotated image dataset for automatic road damage detection using deep learning D Arya, H Maeda, SK Ghosh, D Toshniwal, Y Sekimoto Data in brief 36, 107133, 2021 | 107 | 2021 |
Transfer learning-based road damage detection for multiple countries D Arya, H Maeda, SK Ghosh, D Toshniwal, A Mraz, T Kashiyama, ... arXiv preprint arXiv:2008.13101, 2020 | 98 | 2020 |
Analysing road accident data using association rule mining S Kumar, D Toshniwal 2015 International Conference on Computing, Communication and Security …, 2015 | 89 | 2015 |
Analysis of hourly road accident counts using hierarchical clustering and cophenetic correlation coefficient (CPCC) S Kumar, D Toshniwal Journal of Big Data 3, 1-11, 2016 | 82 | 2016 |
Energy load time-series forecast using decomposition and autoencoder integrated memory network J Bedi, D Toshniwal Applied Soft Computing 93, 106390, 2020 | 74 | 2020 |
A comparative analysis of heterogeneity in road accident data using data mining techniques S Kumar, D Toshniwal, M Parida Evolving systems 8, 147-155, 2017 | 74 | 2017 |