Outputs (29)

Bayesian analysis of multifidelity computer models with local features and non-nested experimental designs: Application to the WRF model (2020)
Journal Article
Konomi, B., & Karagiannis, G. (2021). Bayesian analysis of multifidelity computer models with local features and non-nested experimental designs: Application to the WRF model. Technometrics, 63(4), 510-522. https://doi.org/10.1080/00401706.2020.1855253

Motivated by a multi-fidelity Weather Research and Forecasting (WRF) climate model application where the available simulations are not generated based on hierarchically nested experimental design, we develop a new co-kriging procedure called Augmente... Read More about Bayesian analysis of multifidelity computer models with local features and non-nested experimental designs: Application to the WRF model.

Calibrations and validations of biological models with an application on the renal fibrosis (2020)
Journal Article
Karagiannis, G., Hao, W., & Lin, G. (2020). Calibrations and validations of biological models with an application on the renal fibrosis. International Journal for Numerical Methods in Biomedical Engineering, 36(5), Article e3329. https://doi.org/10.1002/cnm.3329

We calibrate a mathematical model of renal tubulointerstitial fibrosis by Hao et al which is used to explore potential drugs for Lupus Nephritis, against a real data set of 84 patients. For this purpose, we present a general calibration procedure whi... Read More about Calibrations and validations of biological models with an application on the renal fibrosis.

Application of fuzzy multiplexing of learning Gaussian processes for the interval forecasting of wind speed (2019)
Journal Article
Alamaniotis, M., & Karagiannis, G. (2020). Application of fuzzy multiplexing of learning Gaussian processes for the interval forecasting of wind speed. IET Renewable Power Generation, 14(1), 100-109. https://doi.org/10.1049/iet-rpg.2019.0538

Robust forecasting of wind speed values is a key element to effectively accommodate renewable generation from wind in smart power systems. However, the stochastic nature of wind and the uncertainties associated with it impose high challenge in its fo... Read More about Application of fuzzy multiplexing of learning Gaussian processes for the interval forecasting of wind speed.

ELM-Fuzzy Method for Automated Decision-Making in Price Directed Electricity Markets (2019)
Presentation / Conference Contribution
Alamaniotis, M., & Karagiannis, G. (2019, September). ELM-Fuzzy Method for Automated Decision-Making in Price Directed Electricity Markets. Presented at 2019 16th International Conference on the European Energy Market (EEM), Ljubljana, Slovenia

Among many domains application of information technologies has also transformed electricity markets. Price directed markets refer to the driving the electricity consumption by controlling the electricity prices in real time. This paper frames itself... Read More about ELM-Fuzzy Method for Automated Decision-Making in Price Directed Electricity Markets.

Minute Ahead Wind Speed Forecasting Using a Gaussian Process and Fuzzy Assimilation (2019)
Presentation / Conference Contribution
Alamaniotis, M., & Karagiannis, G. (2019, December). Minute Ahead Wind Speed Forecasting Using a Gaussian Process and Fuzzy Assimilation. Presented at 2019 IEEE Milan PowerTech

This paper presents an intelligent data driven method for forecasting minute ahead wind speed, which is essential in predicting the power output coming from wind generators. The proposed methodology, is based on the principle that “the most recent pa... Read More about Minute Ahead Wind Speed Forecasting Using a Gaussian Process and Fuzzy Assimilation.

Learning Uncertainty of Wind Speed Forecasting Using a Fuzzy Multiplexer of Gaussian Processes (2018)
Presentation / Conference Contribution
Alamaniotis, M., & Karagiannis, G. (2018, November). Learning Uncertainty of Wind Speed Forecasting Using a Fuzzy Multiplexer of Gaussian Processes. Presented at Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2018), Dubrovnik, Croatia

The smart power systems of the future will be able to accommodate wind power at a maximum efficiency by utilizing available information. For instance, information pertained to wind speed is essential in forecasting the overall amount of power generat... Read More about Learning Uncertainty of Wind Speed Forecasting Using a Fuzzy Multiplexer of Gaussian Processes.

A three-stage scheme for consumers' partitioning using hierarchical clustering algorithm (2017)
Presentation / Conference Contribution
Nasiakou, A., Alamaniotis, M., Tsoukalas, L. H., & Karagiannis, G. (2017, December). A three-stage scheme for consumers' partitioning using hierarchical clustering algorithm. Presented at 2017 8th International Conference on Information, Intelligence, Systems & Applications (IISA)

The clustering of any type of consumers (residential, commercial, industrial) is of great importance in the operation of Smart Grids. In this paper, we propose a three-stage hierarchical scheme for residential consumers' partitioning using the Hierar... Read More about A three-stage scheme for consumers' partitioning using hierarchical clustering algorithm.

On the Bayesian calibration of expensive computer models with input dependent parameters (2017)
Journal Article
Karagiannis, G., Konomi, B., & Lin, G. (2019). On the Bayesian calibration of expensive computer models with input dependent parameters. Spatial Statistics, 34, Article 100258. https://doi.org/10.1016/j.spasta.2017.08.002

Computer models, aiming at simulating a complex real system, are often calibrated in the light of data to improve performance. Standard calibration methods assume that the optimal values of calibration parameters are invariant to the model inputs. In... Read More about On the Bayesian calibration of expensive computer models with input dependent parameters.

Integration of Gaussian Processes and Particle Swarm Optimization for Very-Short-Term Wind Speed Forecasting in Smart Power (2017)
Journal Article
Alamaniotis, M., & Karagiannis, G. (2017). Integration of Gaussian Processes and Particle Swarm Optimization for Very-Short-Term Wind Speed Forecasting in Smart Power. International Journal of Monitoring and Surveillance Technologies Research, 5(3), 1-14. https://doi.org/10.4018/ijmstr.2017070101

This article describes how the integration of renewable energy in the power grid is a critical issue in order to realize a smart grid infrastructure. To that end, intelligent methods that monitor and currently predict the values of critical variables... Read More about Integration of Gaussian Processes and Particle Swarm Optimization for Very-Short-Term Wind Speed Forecasting in Smart Power.

Bayesian Treed Calibration: an application to carbon capture with AX sorbent (2017)
Journal Article
Konomi, B., Karagiannis, G., Lai, C., & Lin, G. (2017). Bayesian Treed Calibration: an application to carbon capture with AX sorbent. Journal of the American Statistical Association, 112(517), 37-53. https://doi.org/10.1080/01621459.2016.1190279

In cases where field (or experimental) measurements are not available, computer models can model real physical or engineering systems to reproduce their outcomes. They are usually calibrated in light of experimental data to create a better representa... Read More about Bayesian Treed Calibration: an application to carbon capture with AX sorbent.