| Performance analysis of waste collection programs in material recovery facilities T Runsewe, O Bafail, N Celik IIE Annual Conference. Proceedings, 1-6, 2020 | 6 | 2020 |
| Effective sampling for drift mitigation in machine learning using scenario selection: A microgrid case study J Darville, A Yavuz, T Runsewe, N Celik Applied Energy 341, 121048, 2023 | 3 | 2023 |
| Machine Learning Based Simulation for Fault Detection in Microgrids J Darville, T Runsewe, A Yavuz, N Celik 2022 Winter Simulation Conference (WSC), 701-712, 2022 | 3 | 2022 |
| Machine learning models for estimating contamination across different curbside collection strategies T Runsewe, H Damgacioglu, L Perez, N Celik Journal of environmental management 340, 117855, 2023 | 2 | 2023 |
| Manufacturing the future via dynamic data driven applications systems (DDDAS) N Celik, YJ Son, T Runsewe Handbook of Dynamic Data Driven Applications Systems: Volume 2, 743-764, 2023 | 1 | 2023 |
| Assessment of the Impact of the Single Stream Recycling on Paper Contamination in Recovery Facilities and Paper Mills T Runsewe, N Celik Univ. of Miami, FL (United States), 2021 | 1 | 2021 |
| Digital Twin Based Learning Framework for Adaptive Fault Diagnosis In Microgrids with Autonomous Reconfiguration Capabilities T Runsewe, A Yavuz, N Celik 2023 Winter Simulation Conference (WSC), 829-840, 2023 | | 2023 |
| Manufacturing the Future via Dynamic Data Driven Applications Systems (DDDAS)-Chapter 28 N Celik, YJ Son, T Runsewe Springer International Publishing, 2023 | | 2023 |
| DDDAS for Optimized Design and Management of 5G and Beyond 5G (6G) Networks N Celik, F Darema, T Runsewe, W Saad, A Yavuz International Conference on Dynamic Data Driven Applications Systems, 123-132, 2022 | | 2022 |
| DDDAS-Based Learning for Edge Computing at 5G and Beyond 5G T Runsewe, A Yavuz, N Celik, W Saad International Conference on Dynamic Data Driven Applications Systems, 135-143, 2022 | | 2022 |
| Stochastic programming models for planning wind based distributed generation in prosumers of energy mode T Runsewe | | 2020 |
| Stochastic model for planning distributed wind generation using climate analytics T Runsewe, C Novoa, T Jin Proceedings of the 2021 Institute of Industrial and Systems Engineers (IISE …, 2019 | | 2019 |
| Data-Driven Computational Energy Management for Multi-Access Edge Computing Enabled Microgrids T Runsewe University of Miami, 0 | | |
Nurcin CelikProfessor at the University of MiamiBestätigte E-Mail-Adresse bei miami.edu
