| Solar irradiance forecasting in remote microgrids using markov switching model A Shakya, S Michael, C Saunders, D Armstrong, P Pandey, S Chalise, ... IEEE Transactions on sustainable Energy 8 (3), 895-905, 2016 | 87 | 2016 |
| Semi-supervised model-based clustering with positive and negative constraints V Melnykov, I Melnykov, S Michael Advances in data analysis and classification 10, 327-349, 2016 | 29 | 2016 |
| An effective strategy for initializing the EM algorithm in finite mixture models S Michael, V Melnykov Advances in Data Analysis and Classification 10, 563-583, 2016 | 24 | 2016 |
| Prioritizing climate‐smart agriculture: An organizational and temporal review M Gardezi, S Michael, R Stock, S Vij, A Ogunyiola, A Ishtiaque Wiley Interdisciplinary Reviews: Climate Change 13 (2), e755, 2022 | 20 | 2022 |
| Clustering large datasets by merging K-means solutions V Melnykov, S Michael Journal of Classification 37 (1), 97-123, 2020 | 20 | 2020 |
| Using Markov Switching Model for solar irradiance forecasting in remote microgrids A Shakya, S Michael, C Saunders, D Armstrong, P Pandey, S Chalise, ... 2016 IEEE Energy Conversion Congress and Exposition (ECCE), 1-7, 2016 | 12 | 2016 |
| Recent developments in model-based clustering with applications V Melnykov, S Michael, I Melnykov Partitional clustering algorithms, 1-39, 2015 | 12 | 2015 |
| Finite mixture modeling of Gaussian regression time series with application to dendrochronology S Michael, V Melnykov Journal of Classification 33, 412-441, 2016 | 11 | 2016 |
| Social media in chemistry: using a learning management system and twitter to improve student perceptions and performance in chemistry MA Fosu, T Gupta, S Michael Technology Integration in Chemistry Education and Research (TICER), 185-208, 2019 | 10 | 2019 |
| Forecasting data center load using hidden markov model A Bajracharya, MRA Khan, S Michael, R Tonkoski 2018 North American Power Symposium (NAPS), 1-5, 2018 | 10 | 2018 |
| Patient engagement as a predictor for health outcomes and costs in multiple chronic conditions S Ngorsuraches, P Da Rosa, X Ge, G Djira, S Michael, H Wey Value in Health 21, S88-S89, 2018 | 6 | 2018 |
| Studying complexity of model-based clustering S Michael, V Melnykov Communications in Statistics-Simulation and Computation 45 (6), 2051-2069, 2016 | 6 | 2016 |
| Spatial Analysis of Breast Cancer Mortality Rates in a Rural State M Schulz, E Spors, K Bates, S Michael Preventing Chronic Disease 19, 2022 | 5 | 2022 |
| Rethinking ‘responsibility’in precision agriculture innovation: lessons from an interdisciplinary research team E Prutzer, M Gardezi, DM Rizzo, M Emery, S Merrill, BEK Ryan, ... Journal of Responsible Innovation 10 (1), 2202093, 2023 | 3 | 2023 |
| Mixture modeling of data with multiple partial right-censoring levels S Michael, T Miljkovic, V Melnykov Advances in Data Analysis and Classification 14, 355-378, 2020 | 3 | 2020 |
| Finite mixture of regression models for a stratified sample A Abdalla, S Michael Journal of Statistical Computation and Simulation 89 (14), 2782-2800, 2019 | 3 | 2019 |
| Learning trends of COVID-19 using semi-supervised clustering S Michael, X Zhu, V Melnykov arXiv preprint arXiv:2109.06955, 2021 | 2 | 2021 |
| Using electronic medical records and health Claim data to develop a patient engagement Score for patients with multiple chronic conditions: an Exploratory study S Ngorsuraches, S Michael, N Poudel, G Djira, E Griese, A Selya, ... Journal of Patient Experience 8, 2374373520981480, 2021 | 1 | 2021 |
| Exploring the Daschle Collection using Text Mining D Bayer, S Michael arXiv preprint arXiv:1904.12623, 2019 | 1 | 2019 |
| Forecasting Participants in the All Women Count! Mammography Program C Holzhauser, PD Rosa, S Michael Preventing chronic Disease 15, https://www.cdc.gov/pcd/issues/2018/, 2018 | 1 | 2018 |
Volodymyr MelnykovProfessor of StatisticsE-mail megerősítve itt: ua.edu
