No description available.

No description available.

No description available.

Complex fuzzy logic is a new type of multi-valued logic, in which truth values are drawn from the unit disc of the complex plane; it is thus a generalization of the familiar infinite-valued fuzzy logic. At the present time, all published research on complex fuzzy logic is theoretical in nature, with no practical applications demonstrated. The utility of complex fuzzy logic is thus still very debatable. In this thesis, the performance of ANCFIS is evaluated. ANCFIS is the first machine learning architecture to fully implement the ideas of complex fuzzy logic, and was designed to solve the important machine-learning problem of time-series forecasting. We then explore extensions to the ANCFIS architecture. The basic ANCFIS system uses batch (offline) learning, and was restricted to univariate time series prediction. We have developed both an online version of the univariate ANCFIS system, and a multivariate extension to the batch ANCFIS system. / Software Engineering and Intelligent Systems

Thesis (Ph. D.)--State University of New York at Binghamton, Department of Systems Science and Industrial Engineering, Thomas J. Watson School of Engineering and Applied Science, 2007. / Includes bibliographical references.

Thesis (Ph.D.)--Murdoch University, 2006. / Thesis submitted to the Division of Arts. Includes bibliographical references.

Thesis (Ph. D.)--West Virginia University, 1998. / Title from document title page. Document formatted into pages; contains xvii, 90 p. : ill. Vita. Includes abstract.

Stuttgart, Univ., Studienarb., 2004.

Thesis (M. Sc. (Mathematics))--Rhodes University, 2006. / A thesis submitted in partial fulfilment of the requirements for the degree of Master of Science in Mathematics.

Submitted by Lara Oliveira (lara@ufersa.edu.br) on 2017-05-25T21:49:55Z No. of bitstreams: 1 FelipeBV_DISSERT.pdf: 2851541 bytes, checksum: feaf905c8afe0355a8439b48a27a8a35 (MD5) / Approved for entry into archive by Vanessa Christiane (referencia@ufersa.edu.br) on 2017-05-26T11:53:21Z (GMT) No. of bitstreams: 1 FelipeBV_DISSERT.pdf: 2851541 bytes, checksum: feaf905c8afe0355a8439b48a27a8a35 (MD5) / Approved for entry into archive by Vanessa Christiane (referencia@ufersa.edu.br) on 2017-05-26T11:54:17Z (GMT) No. of bitstreams: 1 FelipeBV_DISSERT.pdf: 2851541 bytes, checksum: feaf905c8afe0355a8439b48a27a8a35 (MD5) / Made available in DSpace on 2017-05-26T11:54:50Z (GMT). No. of bitstreams: 1 FelipeBV_DISSERT.pdf: 2851541 bytes, checksum: feaf905c8afe0355a8439b48a27a8a35 (MD5) Previous issue date: 2017-03-21 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In the current industrial park, there is a number of problems with varied level of difficulty, one of the most recurrent is the control of levels of reservoirs or tanks. These systems contain some factors that hinder their control. One of the objectives of this work is the construction of various format tanks, which can impair the performance of classical controllers such as PID. One of the objectives of the work is a tank construction, a modeling test and thus building a simulator without Simulink®. The correct modeling has vital importance for the development of simulated systems, for poorly designed modeling invalidate this study and possible validation of controllers in the system. A comparative study will be made between classic control techniques and the Fuzzy controller, performing a comparison between the behavior of the controllers / No parque industrial atual, existe uma série de problemas com nível de dificuldade variada, um dos mais recorrentes é o de controle de níveis de reservatórios ou tanques. Esses sistemas contêm alguns fatores que dificultam o seu controle. Um dos principais fatores é a não linearidade do sistema, que pode prejudicar o desempenho de controladores clássicos como o PID. Um dos objetivos desse trabalho é a construção de tanques de formato variados, o levantamento dos modelos matemáticos, a elaboração de um simulador no ambiente Simulink®, e o estudo de controladores para os sistemas construídos. A modelagem correta é de vital importância para o desenvolvimento dos sistemas simulados, pois uma modelagem pouco eficaz pode invalidar o estudo e consequentemente a análise de controladores no sistema. Será feito um estudo comparativo entre técnicas de controle clássico e o controlador Fuzzy, realizando uma comparação entre o comportamento dos controladores / 2017-05-25