| Development of New Hybrid Model of Discrete Wavelet Decomposition and Autoregressive Integrated Moving Average (ARIMA) Models in Application to One Month Forecast the … S Singh, KS Parmar, J Kumar, JS Makkhan Sidhu Chaos, Solitons and Fractals 135 (June 2020), 109866, 2020 | 171 | 2020 |
| Study of ARIMA and least square support vector machine (LS-SVM) models for the prediction of SARS-CoV-2 confirmed cases in the most affected countries. S Singh, KS Parmar, JS Makkhan Sidhu, J Kaur, S Peshoria, J Kumar Chaos, Solitons & Fractals Volume 139, October 2020, 110086 139 (October …, 2020 | 113 | 2020 |
| Autoregressive models in environmental forecasting time series: a theoretical and application review J Kaur, K Parmar, S Singh Environmental Science and Pollution Research, 2023 | 60 | 2023 |
| Soft computing model coupled with statistical models to estimate future of stock market S Singh, KS Parmar, J Kumar Neural Computing & Applications, 2021 | 36 | 2021 |
| Prediction of river water quality parameters using soft computing techniques KS Parmar, K Soni, S Singh Intelligent Data Analytics for Decision-Support Systems in Hazard Mitigation …, 2020 | 7 | 2020 |
| Comparison of hybrid machine learning model for the analysis of black carbon in air around the major coal mines of India SJS Makkhan, S Singh, KS Parmar, S Kaushal, K Soni Neural Computing and Applications, 2022 | 5 | 2022 |
| Prediction of COVID‑19 pervasiveness in six major affected states of India and two‑stage variation with temperature S Singh, KS Parmar, J Kaur, J Kumar, SJS Makkhan. Air Quality, Atmosphere & Health, 2021 | 5 | 2021 |
| Development of a mathematical model to forecast black carbon concentration using ARIMA and soft computing J Kaur, S Singh, KS Parmar, K Soni Arabian Journal of Geosciences 16, 2023 | 3 | 2023 |
| Forecasting volatility in the stock market data using GARCH, EGARCH, and GJR models S Singh, K Parmar, J Kaur Handbook of Hydroinformatics 1, 207-220, 2023 | 3 | 2023 |
| Forecasting of AQI (PM2.5) for the three most polluted cities in India during COVID‑19 by hybrid Daubechies discrete wavelet decomposition and autoregressive (Db‑DWD‑ARIMA) model J Kaur, S Singh, KS Parmar Environmental Science and Pollution Research, 2023 | 2 | 2023 |
| Prediction of Confirmed, Recovered and Casualties’ Cases of COVID-19 in India by Autoregressive Integrated Moving Average (ARIMA) Models S Singh, KS Parmar, J Kumar, J Kaur Modeling, Control and Drug Development for COVID-19 Outbreak Prevention 366 …, 2021 | 2 | 2021 |
| Forecasting Time Series Data Using Artificial Neural Network: A Review S Singh, KS Parmar, H Kaur, J Kaur Artificial Intelligence, Machine Learning, and Data Science Technologies, 310, 2021 | 1 | 2021 |
| A Study of the Effect of Increasing Number of Servers on the Performance Measures of a Queuing System S Singh, J Kaur International Journal of Scientific Research and Review 8 (5), 1451-1456, 2019 | | 2019 |
| ARIMA-Wavelet Coupled Approach for Time Series Analysis S Singh, KS Parmar, J Kumar, J Kaur International Journal of Scientific Research and Review 7 (03), 3743-3756, 2019 | | 2019 |
| Analysis of Waiting lines and queuing system in Banks in India during demonetization: A Case Study S Singh Research Cell: An International Journal of Engineering Sciences 24 (16), 137-144, 2017 | | 2017 |
Dr. Kulwinder Singh ParmarI K Gujral Punjab Technical University在 ptu.ac.in 的电子邮件经过验证
