Uneingeschränkter Zugang

RPA-supported digital workforce in the field of statistical work in the electricity market


Zitieren

Cabrera, Lopez, B., Schulz, & Franziska. (2017). Forecasting generalized quantiles of electricity demand: a functional data approach. JASA: Journal of the American Statistical Association. Search in Google Scholar

Liu, X., Ding, Y., Tang, H., & Xiao, F. (2021). A data mining-based framework for the identification of daily electricity usage patterns and anomaly detection in building electricity consumption data. Energy and buildings (Jan.), 231. Search in Google Scholar

Migdadi, H. S. (2015). On the power performance of test statistics for the generalized rayleigh interval grouped data. Open Journal of Statistics, 05(5), 474-482. Search in Google Scholar

Wan, Q., Yu, Y., Wu, K., Li, J., & Liu, W. (2019). Statistics and analysis of power consumption data based on big data. IEEE. Search in Google Scholar

Fields, E. C., & Kuperberg, G. R. (2019). Having your cake and eating it too: flexibility and power with mass univariate statistics for erp data. Psychophysiology, 57(1). Search in Google Scholar

A, J. W., C, G. D. A., B, J. G., & A, F. V. P. (2009). Generalised procrustes analysis with optimal scaling: exploring data from a power supplier. Computational Statistics & Data Analysis, 53( 12), 4546-4554. Search in Google Scholar

Lung-Yut-Fong, A., Céline Lévy-Leduc, & Olivier Cappé. (2011). Homogeneity and change-point detection tests for multivariate data using rank statistics. Statistics, 123(3), 523-531. Search in Google Scholar

Khedikar, S., Kirolikar, P., & Thombre, S. (2013). Data warehouse creation for preparing an electricity statistics dashboard. International Journal of Computer Science & Network, 2(6). Search in Google Scholar

Tricker, & A., R. (1990). The effect of rounding on the significance level and power of certain test statistics for non-normal data. Journal of Applied Statistics, 17(3), 329-340. Search in Google Scholar

Wang, K., Xu, C., Zhang, Y., Guo, S., & Zomaya, A. Y. (2017). Robust big data analytics for electricity price forecasting in the smart grid. IEEE Transactions on Big Data, PP(99), 1-1. Search in Google Scholar

Fezzi, C., & Fanghella, V. (2020). Tracking gdp in real-time using electricity market data: insights from the first wave of covid-19 across europe. Papers. Search in Google Scholar

eISSN:
2444-8656
Sprache:
Englisch
Zeitrahmen der Veröffentlichung:
Volume Open
Fachgebiete der Zeitschrift:
Biologie, andere, Mathematik, Angewandte Mathematik, Allgemeines, Physik