Genetic programming and bacterial algorithm for neural networks and fuzzy systems design

In the field of control systems it is common to use techniques based on model adaptation to carry out control for plants for which mathematical analysis may be intricate. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this line, this paper gives a perspective on the quality of results given by two different biologically connected learning algorithms for the design of B-spline neural networks (BNN) and fuzzy systems (FS). One approach used is the Genetic Programming (GP) for BNN design and the other is the Bacterial Evolutionary Algorithm (BEA) applied for fuzzy rule extraction. Also, the facility to incorporate a multi-objective approach to the GP algorithm is outlined, enabling the designer to obtain models more adequate for their intended use.

B-spline and neuro-fuzzy models design with function and derivative equalities

The design of neuro-fuzzy models is still a complex problem, as it involves not only the determination of the model parameters, but also its structure. Of special importance is the incorporation of a priori information in the design process. In this paper two known design algorithms for B-spline models will be updated to account for function and derivatives equality restrictions, which are important when the neural model is used for performing single or multi-objective optimization on-line.

Design of neuro-fuzzy models by evolutionary and gradient-based algorithms

All systems found in nature exhibit, with different degrees, a nonlinear behavior. To emulate this behavior, classical systems identification techniques use, typically, linear models, for mathematical simplicity. Models inspired by biological principles (artificial neural networks) and linguistically motivated (fuzzy systems), due to their universal approximation property, are becoming alternatives to classical mathematical models. In systems identification, the design of this type of models is an iterative process, requiring, among other steps, the need to identify the model structure, as well as the estimation of the model parameters. This thesis addresses the applicability of gradient-basis algorithms for the parameter estimation phase, and the use of evolutionary algorithms for model structure selection, for the design of neuro-fuzzy systems, i.e., models that offer the transparency property found in fuzzy systems, but use, for their design, algorithms introduced in the context of neural networks. A new methodology, based on the minimization of the integral of the error, and exploiting the parameter separability property typically found in neuro-fuzzy systems, is proposed for parameter estimation. A recent evolutionary technique (bacterial algorithms), based on the natural phenomenon of microbial evolution, is combined with genetic programming, and the resulting algorithm, bacterial programming, advocated for structure determination. Different versions of this evolutionary technique are combined with gradient-based algorithms, solving problems found in fuzzy and neuro-fuzzy design, namely incorporation of a-priori knowledge, gradient algorithms initialization and model complexity reduction.

Estimating fuzzy membership functions parameters by the levenberg-marquardt algorithm

In previous papers from the authors fuzzy model identification methods were discussed. The bacterial algorithm for extracting fuzzy rule base from a training set was presented. The Levenberg-Marquardt algorithm was also proposed for determining membership functions in fuzzy systems. In this paper the Levenberg-Marquardt technique is improved to optimise the membership functions in the fuzzy rules without Ruspini-partition. The class of membership functions investigated is the trapezoidal one as it is general enough and widely used. The method can be easily extended to arbitrary piecewise linear functions as well.

A utilização de sistemas solares térmicos nas unidades hoteleiras de 3 estrelas do Algarve

A região do Algarve é uma das regiões da União Europeia com maior potencialidade no aproveitamento da energia solar nomeadamente através da utilização de sistemas solares térmicos para aquecimento de água. A tecnologia utilizada nestes sistemas é relativamente simples e bem conhecida mas infelizmente verifica-se que, por diversas razões, nem sempre é aplicada. A alternativa, é a utilização de sistemas de aquecimento de água que utilizam combustíveis fósseis, quer de forma directa, como por exemplo através da queima de um combustível (gasóleo, gás propano, etc), ou de forma indirecta, através da electricidade. A utilização de combustíveis fósseis esta na origem de um dos maiores problemas ambientais da nossa época, o aquecimento global. Além disso, dependendo do tipo de combustível e da

Análise de sistemas de comunicação óptica com multiplexagem de subportadora e transmissão em banda lateral única

Tese dout., Engenharia Electrónica e Computação, Universidade do Algarve, 2005

Certificação ambiental de campos de golfe - custos e benefícios associados à implementação de sistemas de gestão ambiental

Dissertação mest., Engenharia do Ambiente, Universidade do Algarve, 2009

Modelización del sector turístico y simulación de estrategias mediante dinámica de sistemas : aplicación al Algarbe portugués

Tese dout., Universidad de Huelva. Departamento de Economía Financiera, Contabilidad y Dirección de Operaciones.

A integração dos sistemas de informação e do turismo, o caso IMPACTUR

Os SI e o turismo formam uma aliança bem conseguida e com inegáveis potencialidades para os agentes de decisão e investigadores. O objectivo deste artigo é o de apresentar um caso concreto e real desta aliança, o Sistema de Informação para apoio ao IMPACTUR (Indicadores de Monitorização e Previsão da Actividade Turística), que se encontra em funcionamento e disponível através da Internet, onde se pode verificar e analisar os benefícios obtidos pela conjugação entre os conceitos associados à actividade turística e às tecnologias de informação e de comunicação. O presente artigo resulta do desenvolvimento metodológico de uma componente do projecto de investigação científica denominado IMPACTUR - Indicadores de Monitorização e Previsão da Actividade Turística, sendo este beneficiário da parceria estabelecida entre o Instituto de Turismo de Portugal e a Universidade do Algarve / Centro Internacional de Investigação em Território e Turismo, aos quais a autora agradece o apoio concedido.

Dynamic Packaging e os Sistemas de Informação Turísticos: características, potencialidades e desafios

O aparecimento da Internet revolucionou as operações dentro do canal da distribuição turística, obrigando à reavaliação dos intervenientes a nível da forma de actuação e de posicionamento. A distribuição turística transformou-se num dos factores mais críticos para a competitividade dos destinos e das empresas turísticas, uma vez que tem como principal função o tratamento, a combinação e a organização da informação. A Internet permitiu e facilitou o acesso instantâneo à informação turística bem como a efectuar reservas e compras de produtos turísticos. Neste contexto tecnológico, emergiram na World Wide Web sites que permitem ao turista a criação de um pacote personalizado, que apresenta o preço em tempo real, designados por Dynamic Packaging. Neste artigo, apresentamos a sua ligação com os sistemas de informação turísticos, analisando as suas potencialidades e desafios inerentes ao desenvolvimento de uma arquitectura tecnológica, que integra a complexidade e especificidade da informação relacionada com a actividade turística, bem como está sujeita às constantes alterações sofridas pelo sector do turismo, numa sociedade onde todos os dias emergem novas funcionalidades e novos conceitos.

Sistemas de informação para a gestão turística

Nowadays, to be competitive in society means to have a technological framework that fi ts customer responses. In tourism, the need for ICT (Information and Communication Technologies) is even more important, since to sell the tourist product it is crucial to disclose the information that characterizes it, plus, it is necessary to organize, manage and deal with it in accordance with the tourists’ expectations. After the tourist product has been consumed, it is important to share the experience with other travellers. The process of purchase and consumption of a tourist product is possible only if tourists and professionals have access to the information required, and for this it is necessary to use systems that can: manage results, flights and customer loyalty, distribute information and travel planning, among other things. All these systems have tourist information management in common, which leads to the conclusion that they are indispensable to tourism. This paper presents several information systems that coexist in the tourism sector, as well as those used in tourist distribution channels. Finally we show the trends that these systems are causing in tourism.

Vantagens, limitações e soluções na utilização de sistemas ERP (Enterprise Resource Planning): um estudo de caso na indústria hoteleira

Tese de dout., Ciências Económicas e Empresariais, Faculdade de Economia, Univ. do Algarve, 2012

Bacterial algorithm applied for fuzzy rule extraction

This paper presents a method of using the so-colled "bacterial algorithm" (4,5) for extracting a fuzzy rule base from a training set. The bewly proposed bacterial evolutionary algorithm (BEA) is shown. In our application one bacterium corresponds to a fuzzy rule system.

Anytime information processing based on fuzzy and neural network models

In modern measurement and control systems, the available time and resources are often not only limited, but could change during the operation of the system. In these cases, the so-called anytime algorithms could be used advantageously. While diflerent soft computing methods are wide-spreadly used in system modeling, their usability in these cases are limited.

Completely supervised training algorithms for B-spline neural networks and neuro-fuzzy systems

Complete supervised training algorithms for B-spline neural networks and fuzzy rule-based systems are discussed. By interducing the relationship between B-spline neural networks and certain types of fuzzy models, training algorithms developed initially for neural networks can be adapted by fuzzy systems.