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Relevant bibliographies by topics / Rough seas

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Dissertations / Theses

Academic literature on the topic 'Rough seas'

Author: Grafiati

Published: 10 March 2023

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Dissertations / Theses on the topic "Rough seas"

1

Mockutė, Agota [Verfasser]. "Suitability of Wave Loading Models for Offshore Wind Turbine Monopiles in Rough Seas / Agota Mockute." Düren : Shaker, 2020. http://nbn-resolving.de/urn:nbn:de:101:1-2020090605232739927321.

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2

Mockute, Agota [Verfasser]. "Suitability of Wave Loading Models for Offshore Wind Turbine Monopiles in Rough Seas / Agota Mockute." Düren : Shaker, 2020. http://d-nb.info/1217164081/34.

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3

Vural, Hulya. "Comparison Of Rough Multi Layer Perceptron And Rough Radial Basis Function Networks Using Fuzzy Attributes." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12605293/index.pdf.

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The hybridization of soft computing methods of Radial Basis Function (RBF) neural networks, Multi Layer Perceptron (MLP) neural networks with back-propagation learning, fuzzy sets and rough sets are studied in the scope of this thesis. Conventional MLP, conventional RBF, fuzzy MLP, fuzzy RBF, rough fuzzy MLP, and rough fuzzy RBF networks are compared. In the fuzzy neural networks implemented in this thesis, the input data and the desired outputs are given fuzzy membership values as the fuzzy properties &ldquo<br>low&rdquo<br>, &ldquo<br>medium&rdquo<br>and &ldquo<br>high&rdquo<br>. In the roug

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4

Ferone, A. "EXPLOITING HIGHER ORDER UNCERTAINTY IN IMAGE ANALYSIS." Doctoral thesis, Università degli Studi di Milano, 2011. http://hdl.handle.net/2434/155479.

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Soft computing is a group of methodologies that works synergistically to provide flexible information processing capability for handling real-life ambiguous situations. Its aim is to exploit the tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve tractability, robustness, and low-cost solutions. Soft computing methodologies (involving fuzzy sets, neural networks, genetic algorithms, and rough sets) have been successfully employed in various image processing tasks including image segmentation, enhancement and classification, both individually or

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5

Fernández, Oliva Alberto. "Estimación probabilística del grado de excepcionalidad de un elemento arbitrario en un conjunto finito de datos: aplicación de la teoría de conjuntos aproximados de precisión variable." Doctoral thesis, Universidad de Alicante, 2010. http://hdl.handle.net/10045/17570.

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6

Oukbir, Karim. "Indiscernibility and Vagueness in Spatial Information Systems." Doctoral thesis, KTH, Numerical Analysis and Computer Science, NADA, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3634.

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<p>We investigate the use of the concept of indiscernibilityand vagueness in spatial information systems. To representindiscernibility and vagueness we use rough sets, respectivelyfuzzy sets. We introduce a theoretical model to supportapproximate queries in information systems and we show howthose queries can be used to perform uncertain classi.cations.We also explore how to assess quality of uncertainclassi.cations and ways to compare those classi.cations to eachother in order to assess accuracies. We implement the querylanguage in an SQL relational language to demonstrate thefeasibility of a

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7

Mazzocco, Alessandro <1991&gt. "L'approccio dei Rough-sets applicato alla valutazione dello stato di salute aziendale." Master's Degree Thesis, Università Ca' Foscari Venezia, 2017. http://hdl.handle.net/10579/10469.

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- Introduzione sul fallimento aziendale e panoramiche dei metodi statistici e variabili utilizzati in letteratura per prevederlo - Rough set Theory - Applicazione dei rough set con indicatori di bilancio di aziende fallite e no per valutarne l’efficacia ai fini della previsione del fallimento aziendale - Conclusione con confronto con gli altri metodi

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8

Oliveira, Henrique Viana. "Refinamento de Consultas em Lógicas de Descrição Utilizando Teoria dos Rough Sets." reponame:Repositório Institucional da UFC, 2012. http://www.repositorio.ufc.br/handle/riufc/18114.

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OLIVEIRA, Henrique Viana. Refinamento de Consultas em Lógicas de Descrição Utilizando Teoria dos Rough Sets. 2012. 111 f. : Dissertação (mestrado) - Universidade Federal do Ceará, Centro de Ciências, Departamento de Computação, Fortaleza-CE, 2012.<br>Submitted by guaracy araujo (guaraa3355@gmail.com) on 2016-07-01T17:23:02Z No. of bitstreams: 1 2012_dis_hvoliveira.pdf: 789598 bytes, checksum: d75ef093adc56cc930f52c1e486ead5a (MD5)<br>Approved for entry into archive by guaracy araujo (guaraa3355@gmail.com) on 2016-07-01T17:23:47Z (GMT) No. of bitstreams: 1 2012_dis_hvoliveira.pdf: 789598 bytes,

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9

Oliveira, Henrique Viana. "Refinamento de Consultas em LÃgicas de DescriÃÃo Utilizando Teoria dos Rough Sets." Universidade Federal do CearÃ, 2012. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=8325.

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CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior<br>Refinamento de consulta consiste de tÃcnicas que modificam os termos de uma consulta com o objetivo de alterar os resultados obtidos inicialmente. Para a realizaÃÃo de tal fim, diversas abordagens podem ser aplicadas e diferentes tipos de refinamentos podem ser considerados. Este trabalho propÃe aplicar a teoria dos Rough Sets como uma nova alternativa de soluÃÃo para o problema. AtravÃs das noÃÃes presentes nessa teoria, iremos desenvolver tÃcnicas que serÃo aplicadas nas linguagens de LÃgicas de DescriÃÃo, que sÃo comumente utili

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10

Lee, Chang Su. "A framework of adaptive T-S type rough-fuzzy inference systems (ARFIS)." University of Western Australia. School of Electrical, Electronic and Computer Engineering, 2009. http://theses.library.uwa.edu.au/adt-WU2009.0192.

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[Truncated abstract] Fuzzy inference systems (FIS) are information processing systems using fuzzy logic mechanism to represent the human reasoning process and to make decisions based on uncertain, imprecise environments in our daily lives. Since the introduction of fuzzy set theory, fuzzy inference systems have been widely used mainly for system modeling, industrial plant control for a variety of practical applications, and also other decisionmaking purposes; advanced data analysis in medical research, risk management in business, stock market prediction in finance, data analysis in bioinforma

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