caa a22 4500 475834186 CHVBK 20180406123849.0 cr unu---uuuuu 170329e20000701xx s 000 0 eng 10.1007/s005210070024 doi (NATIONALLICENCE)springer-10.1007/s005210070024 Marzban C. National Severe Storms Laboratory, Norman, OK, USA; Cooperative Institute for Mesoscale and Meteorological Studies; and Department of Physics, University of Oklahoma, Norman, OK, USA, US aut A Neural Network for Tornado Diagnosis: Managing Local Minima [Elektronische Daten] [C. Marzban] There exist radar-based algorithms designed to detect circulations in the atmosphere. Not all detected circulations, however, are associated with tornados on the ground. Outlined herein is the development of a multi-layered perceptron designed to classify the two types of circulations - nontor-nadic and tornadic - based on various attributes of the circulations. Special emphasis is placed on the role of local minima in determining the optimal architecture via bootstrapping, and on the performance of the network in terms of probabilistic measures.: Springer-Verlag London Limited, 2000 Keywords:Neural network nationallicence Tornado nationallicence Weather forecast nationallicence https://doi.org/10.1007/s005210070024 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s005210070024 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Marzban C. National Severe Storms Laboratory, Norman, OK, USA; Cooperative Institute for Mesoscale and Meteorological Studies; and Department of Physics, University of Oklahoma, Norman, OK, USA, US aut Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer