| Application of least square support vector machine and multivariate adaptive regression spline models in long term prediction of river water pollution O Kisi, KS Parmar Journal of Hydrology 534, 104-112, 2016 | 359 | 2016 |
| Significant Applications of Machine Learning for COVID-19 Pandemic RPS Shashi Kushwaha, Shashi Bahl, Ashok Kumar Bagha, Kulwinder Parmar, Mohd ... Journal of Industrial Integration and Management, 2020 | 199 | 2020 |
| 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, K Parmar, J Kumar, SJS Makkhan Chaos Solitons & Fractals, 2020 | 181 | 2020 |
| Long-term aerosol climatology over Indo-Gangetic Plain: Trend, prediction and potential source fields M Kumar, KS Parmar, DB Kumar, A Mhawish, DM Broday, RK Mall, ... Atmospheric environment 180, 37-50, 2018 | 163 | 2018 |
| 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 JK Sarbjit Singh, Kulwinder Singh Parmar, Sidhu Jitendra Singh Makkhan ... Chaos Solitons & Fractals, 2020 | 125 | 2020 |
| The viability of extended marine predators algorithm-based artificial neural networks for streamflow prediction RMA Ikram, AA Ewees, KS Parmar, ZM Yaseen, S Shahid, O Kisi Applied Soft Computing 131, 109739, 2022 | 113 | 2022 |
| Autoregressive models in environmental forecasting time series: a theoretical and application review J Kaur, KS Parmar, S Singh Environmental Science and Pollution Research 30 (8), 19617-19641, 2023 | 108 | 2023 |
| Water quality management using statistical analysis and time-series prediction model KS Parmar, R Bhardwaj Applied Water Science, 2014 | 106 | 2014 |
| River Water Prediction Modeling Using Neural Networks, Fuzzy and Wavelet Coupled Model KS Parmar, R Bhardwaj Water Resources Management, 2014 | 86 | 2014 |
| Pan evaporation modeling by three different neuro-fuzzy intelligent systems using climatic inputs RM Adnan, A Malik, A Kumar, K Parmar, O Kisi Arabian Journal of Geosciences, 2019 | 85 | 2019 |
| Water quality index and fractal dimension analysis of water parameters KS Parmar, R Bhardwaj International journal of environmental science and technology 10, 151-164, 2013 | 80 | 2013 |
| Modeling of air pollutants using least square support vector regression, multivariate adaptive regression spline, and M5 model tree models VD Ozgur Kisi, Kulwinder Singh Parmar, Kirti Soni Air Quality, Atmosphere & Health, 2017 | 78 | 2017 |
| Modeling monthly streamflow in mountainous basin by MARS, GMDH-NN and DENFIS using hydroclimatic data RM Adnan, Z Liang, KS Parmar, K Soni, O Kisi Neural Computing and Applications 33, 2853-2871, 2021 | 74 | 2021 |
| Water temperature prediction using improved deep learning methods through reptile search algorithm and weighted mean of vectors optimizer RMA Ikram, RR Mostafa, Z Chen, KS Parmar, O Kisi, ... Journal of Marine Science and Engineering 11 (2), 259, 2023 | 68 | 2023 |
| Wavelet and statistical analysis of river water quality parameters KS Parmar, R Bhardwaj Applied Mathematics and Computation 219, 10172-10182, 2013 | 68 | 2013 |
| Statistical analysis of aerosols over the Gangetic–Himalayan region using ARIMA model based on long-term MODIS observations K Soni, S Kapoor, KS Parmar, DG Kaskaoutis Atmospheric Research 149, 174-192, 2014 | 56 | 2014 |
| Soft computing model coupled with statistical models to estimate future of stock market S Singh, K Parmar, J Kumar Neural Computing and Applications, 2021 | 45 | 2021 |
| Time series model prediction and trend variability of aerosol optical depth over coal mines in India KSKSPS Kapoor Environmental Science and Pollution Research, 2014 | 44* | 2014 |
| Modeling multistep ahead dissolved oxygen concentration using improved support vector machines by a hybrid metaheuristic algorithm RM Adnan, HL Dai, RR Mostafa, KS Parmar, S Heddam, O Kisi Sustainability 14 (6), 3470, 2022 | 42 | 2022 |
| Comparison of ARIMA and ANN approaches in time-series predictions of traffic noise N Garg, MK Sharma, KS Parmar, K Soni, RK Singh, S Maji Noise Control Engineering Journal 64 (4), 522-531, 2016 | 33 | 2016 |
Ozgur KisiDepartment of Civil Engineering, University of Applied Sciences, Lübeck, GermanyE-mailová adresa ověřena na: th-luebeck.de