DSpace Collection:http://hdl.handle.net/10174/11192024-03-29T10:09:49Z2024-03-29T10:09:49ZMUSMAR based switching control of a solar collector fieldRato, LuisBorrelli, DonatoMosca, EdoardoLemos, João MBalsa, Pedrohttp://hdl.handle.net/10174/159802020-02-11T16:53:35Z1997-01-01T00:00:00ZTitle: MUSMAR based switching control of a solar collector field
Authors: Rato, Luis; Borrelli, Donato; Mosca, Edoardo; Lemos, João M; Balsa, Pedro
Editors: Aeyels, Dirk
Abstract: This paper presents a switching controller for the distributed collector eld of a solar
power plant. The switching control strategy has been used to cope with the changes in plant dynamic behavior induced by di erent operating conditions. The underlying predictive models and controllers were designed using the MUSMAR adaptive algorithm. Experimental results obtained at Plataforma Solar de Almeria (in Spain), are presented.1997-01-01T00:00:00ZUsing Support Vector Machine Model for Fault Detection along a Water canalDuarte, JRato, LRijo, Mhttp://hdl.handle.net/10174/126002015-02-18T12:24:59Z2014-10-31T00:00:00ZTitle: Using Support Vector Machine Model for Fault Detection along a Water canal
Authors: Duarte, J; Rato, L; Rijo, M
Editors: Alexandre, L; Proença, H; Fazendeiro, P
Abstract: This paper reports a work in progress, the training of a Support Vector Machine model to detect faults in an experimental water supply canal. The work took place at the experimental canal of Núcleo de Hidráulica
e Controlo de Canais at the Universidade de Évora. The main objective is to identify faults in the water depth sensors and to detect unauthorized water withdrawals using pattern recognition. The preliminary accuracy
tests, in and out of sample, have shown an accuracy over 90% to identify 28 different patterns.2014-10-31T00:00:00ZProcessing and classification of biological images: Application to histologyNunes, BRato, LuisCapela e Silva, FRafael, ACabrita, AShttp://hdl.handle.net/10174/39172012-10-09T15:58:03Z2011-01-01T00:00:00ZTitle: Processing and classification of biological images: Application to histology
Authors: Nunes, B; Rato, Luis; Capela e Silva, F; Rafael, A; Cabrita, AS
Editors: Jorge, RM; Tavares, JM; Barbosa, MP; Slade, AP
Abstract: This article deals with a histological problem by using image processing and feature extraction in images of renal tissues of rats and their classification through various methods such as: Bayesian inference, decision trees and support vector machines.2011-01-01T00:00:00Z