Improve Load Forecasting in Energy Communities through Transfer Learning using Open-Access Synthetic Profiles

Autor: Moosbrugger, Lukas, Seiler, Valentin, Huber, Gerhard, Kepplinger, Peter

According to a conservative estimate, a 1% reduction in forecast error for a 10 GW energy utility can save up to $ 1.6 million annually. In our context, achieving precise forecasts of future power consumption is crucial for operating flexible energy

Externí odkaz: http://arxiv.org/abs/2407.08434

First observation and study of the $K^{\pm} \rightarrow \pi^{0} \pi^{0} \mu^{\pm} \nu$ decay

Autor: Collaboration, NA48/2, Batley, J. R., Kalmus, G., Lazzeroni, C., Munday, D. J., Slater, M. W., Wotton, S. A., Arcidiacono, R., Ceccucci, A., Bocquet, G., Cabibbo, N., Cundy, D., Falaleev, V., Gatignon, L., Fidecaro, M., Gonidec, A., Kubischta, W., Maier, A., Norton, A., Patel, M., Peters, A., Balev, S., Frabetti, P. L., Gersabeck, E., Goudzovski, E., Hristov, P., Kekelidze, V., Madigozhin, D., Molokanova, N., Polenkevich, I., Potrebenikov, Yu., Korotkova, A., Stoynev, S., Zinchenko, A., Kozhuharov, V., Litov, L., Monnier, E., Swallow, E., Winston, R., Rubin, P., Walker, A., Baldini, W., Ramusino, A. Cotta, Dalpiaz, P., Damiani, C., Fiorini, M., Gianoli, A., Martini, M., Petrucci, F., Savrié, M., Scarpa, M., Wahl, H., Bizzeti, A., Veltri, M., Calvetti, M., Celeghini, E., Iacopini, E., Lenti, M., Ruggiero, G., Behler, M., Eppard, K., Hita-Hochgesand, M., Kleinknecht, K., Marouelli, P., Masetti, L., Moosbrugger, U., Morales, C. Morales, Renk, B., Wache, M., Winhart, A., Wanke, R., Coward, D., Dabrowski, A., Martin, T. Fonseca, Shieh, M., Szleper, M., Velasco, M., Wood, M. D., Cenci, P., Pepe, M., Petrucci, M. C., Anzivino, G., Imbergamo, E., Nappi, A., Piccini, M., Raggi, M., Valdata-Nappi, M., Cerri, C., Fantechi, R., Collazuol, G., Di Lella, L., Lamanna, G., Mannelli, I., Michetti, A., Costantini, F., Doble, N., Fiorini, L., Giudici, S., Pierazzini, G., Sozzi, M., Venditti, S., Bloch-Devaux, B., Peyaud, B., Cheshkov, C., Chèze, J. B., De Beer, M., Derré, J., Marel, G., Mazzucato, E., Vallage, B., Holder, M., Ziolkowski, M., Biino, C., Cartiglia, N., Marchetto, F., Bifani, S., Clemencic, M., Lopez, S. Goy, Dibon, H., Jeitler, M., Markytan, M., Mikulec, I., Neuhofer, G., Widhalm, L.

Publikováno v: JHEP 03(2024)137

The NA48/2 experiment at CERN reports the first observation of the $K^{\pm} \rightarrow \pi^{0} \pi^{0} \mu^{\pm} \nu$ decay based on a sample of 2437 candidates with 15% background contamination collected in 2003--2004. The decay branching ratio in

Externí odkaz: http://arxiv.org/abs/2310.20295

Exact and Approximate Moment Derivation for Probabilistic Loops With Non-Polynomial Assignments

Autor: Kofnov, Andrey, Moosbrugger, Marcel, Stankovič, Miroslav, Bartocci, Ezio, Bura, Efstathia

Many stochastic continuous-state dynamical systems can be modeled as probabilistic programs with nonlinear non-polynomial updates in non-nested loops. We present two methods, one approximate and one exact, to automatically compute, without sampling,

Externí odkaz: http://arxiv.org/abs/2306.07072

Automated Sensitivity Analysis for Probabilistic Loops

Autor: Moosbrugger, Marcel, Müllner, Julian, Kovács, Laura

We present an exact approach to analyze and quantify the sensitivity of higher moments of probabilistic loops with symbolic parameters, polynomial arithmetic and potentially uncountable state spaces. Our approach integrates methods from symbolic comp

Externí odkaz: http://arxiv.org/abs/2305.15259

Distribution Estimation for Probabilistic Loops

Autor: Karimi, Ahmad, Moosbrugger, Marcel, Stankovič, Miroslav, Kovács, Laura, Bartocci, Ezio, Bura, Efstathia

We present an algorithmic approach to estimate the value distributions of random variables of probabilistic loops whose statistical moments are (partially) known. Based on these moments, we apply two statistical methods, Maximum Entropy and Gram-Char

Externí odkaz: http://arxiv.org/abs/2205.07639