Transformer Winding Fault Classification and Condition Assessment Based on Random Forest Using FRA.. Energies 2023, (16)3714April 2023. [PUMA: Assessment Classification Condition FRA Fault Forest Random Transformer Using Winding]
Computing the feasible operating region of active distribution networks: Comparison and validation of random sampling and optimal power flow based methods. IET Generation, Transmission & Distribution, (15)10:1600-1612, May 2021. [PUMA: Comparison Computing active and based distribution feasible flow methods networks: of operating optimal power random region sampling the validation]
Reconstructing science networks from the past. Journal of Historical Network Research, (3)1:92--117, November 2019. [PUMA: Elite, Eponyms, Exponential Graph Historical History Malacology Models, Random networks, of social] URL
Verification of Linear Flexibility Range Assessment in Distribution Grids. 2019. [PUMA: Aggregation Coordination DSO Flexibility Linear Optimization Random Sampling TSO aggregation myown]
Dynamic river masks from multi-temporal satellite imagery: an automatic algorithm using graph cuts optimization. 2016. [PUMA: Optical water body satellite Hydrology, image Markov random fields, classification, area cuts imagery, graph sensing, Remote monitoring, from:mantoni]
Dynamic river masks from multi-temporal satellite imagery: an automatic algorithm using graph cuts optimization. 2016. [PUMA: Hydrology, Markov Optical Remote area body classification, cuts fields, graph image imagery, monitoring, random satellite sensing, water]
UNCERTAINTY QUANTIFICATION FOR HYPERBOLIC CONSERVATION LAWS WITH FLUX COEFFICIENTS GIVEN BY SPATIOTEMPORAL RANDOM FIELDS. SIAM JOURNAL ON SCIENTIFIC COMPUTING, (38)4:A2209-A2231, SIAM PUBLICATIONS, 3600 UNIV CITY SCIENCE CENTER, PHILADELPHIA, PA 19104-2688 USA, 2016. [PUMA: Carlo Gaussian Monte Ornstein-Uhlenbeck differential equation; field; field} finite flux function; hyperbolic method; partial process; quantification; random spatiotemporal uncertainty volume {stochastic]
Gaussian and non-Gaussian inverse modeling of groundwater flow using copulas and random mixing. WATER RESOURCES RESEARCH, (52)6:4504-4526, AMER GEOPHYSICAL UNION, 2000 FLORIDA AVE NW, WASHINGTON, DC 20009 USA, June 2016. [PUMA: copula; mixing; modeling; non-Gaussianity} random {inverse]