Adaptive Penalty and Barrier function based on Fuzzy Logic

Optimization methods have been used in many areas of knowledge, such as Engineering, Statistics, Chemistry, among others, to solve optimization problems. In many cases it is not possible to use derivative methods, due to the characteristics of the problem to be solved and/or its constraints, for example if the involved functions are non-smooth and/or their derivatives are not know. To solve this type of problems a Java based API has been implemented, which includes only derivative-free optimization methods, and that can be used to solve both constrained and unconstrained problems. For solving constrained problems, the classic Penalty and Barrier functions were included in the API. In this paper a new approach to Penalty and Barrier functions, based on Fuzzy Logic, is proposed. Two penalty functions, that impose a progressive penalization to solutions that violate the constraints, are discussed. The implemented functions impose a low penalization when the violation of the constraints is low and a heavy penalty when the violation is high. Numerical results, obtained using twenty-eight test problems, comparing the proposed Fuzzy Logic based functions to six of the classic Penalty and Barrier functions are presented. Considering the achieved results, it can be concluded that the proposed penalty functions besides being very robust also have a very good performance.

Recursive neuro fuzzy techniques for online identification and control

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Unfuzzying fuzzy parsing

Dissertação de Mestrado em Engenharia Informática

Fuzzy-Clusteranalyse : Methoden zur Exploration von Daten mit fehlenden Werten sowie klassifizierten Daten

Fuzzy-Clusteranalyse, Fuzzy-Datenanlayse

Objective function based fuzzy clustering in air traffic management

Data analysis, fuzzy clustering, fuzzy rules, air traffic management

Partially supervised learning of fuzzy classification rules

Fuzzy classification, semi-supervised learning, data mining

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Systemidentification, evolutionary automatic, data-driven model, fuzzy Takagi-Sugeno grammar, genotype interpretability, toxicity-prediction

Representations of lattice point sets : theory, algorithms, applications

Magdeburg, Univ., Fak. für Mathematik, Habil.-Schr., 2006

Difference sets from projective planes

Magdeburg, Univ., Fak. für Mathematik, Diss., 2013

Application of Fuzzy Variables for Systems of Management Decision Support

The following article describes an approach covering the variety of opinions and uncertainties of estimates within the chosen technique of decision support. Mathematical operations used for assessment of options are traced to operations of working with functions that are used for assessment of possible options of decision-making. Approach proposed could be used within any technique of decision support based on elementary mathematical operations. In this article the above-mentioned approach is described under analytical hierarchy process.

Illustrative visualization of medical data sets

Magdeburg, Univ., Fak. für Informatik, Diss., 2014

Illustrative visualization of medical data sets

Magdeburg, Univ., Fak. für Informatik, Diss., 2014

Lipschitz harmonic capacity and Bilipschitz images of cantor sets

For bilipschitz images of Cantor sets in Rd we estimate the Lipschitz harmonic capacity and show this capacity is invariant under bilipschitz homeomorphisms.

Regulación del proceso de secado de embutidos crudos-curados mediante la aplicación de lógica borrosa (fuzzy logic)

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Stochastic Choice and Consideration Sets

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