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Semhar Michael
Semhar Michael
Associate Professor of Statistics, South Dakota State University
Verified email at sdstate.edu
Title
Cited by
Cited by
Year
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
872016
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
282016
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
242016
Clustering large datasets by merging K-means solutions
V Melnykov, S Michael
Journal of Classification 37 (1), 97-123, 2020
192020
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
182022
Recent developments in model-based clustering with applications
V Melnykov, S Michael, I Melnykov
Partitional clustering algorithms, 1-39, 2015
122015
Finite mixture modeling of Gaussian regression time series with application to dendrochronology
S Michael, V Melnykov
Journal of Classification 33, 412-441, 2016
112016
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
112016
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
102019
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
102018
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
62018
Studying complexity of model-based clustering
S Michael, V Melnykov
Communications in Statistics-Simulation and Computation 45 (6), 2051-2069, 2016
62016
Spatial Analysis of Breast Cancer Mortality Rates in a Rural State
M Schulz, E Spors, K Bates, S Michael
Preventing Chronic Disease 19, 2022
52022
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
32023
Finite mixture of regression models for a stratified sample
A Abdalla, S Michael
Journal of Statistical Computation and Simulation 89 (14), 2782-2800, 2019
32019
Learning trends of COVID-19 using semi-supervised clustering
S Michael, X Zhu, V Melnykov
arXiv preprint arXiv:2109.06955, 2021
22021
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
22020
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
12021
Exploring the Daschle Collection using Text Mining
D Bayer, S Michael
arXiv preprint arXiv:1904.12623, 2019
12019
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
12018
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