Modelo matemático baseado em lógica nebulosa para tratamento de variáveis e avaliação de contexto de sistemas dinâmicos.

A pesquisa apresenta uma adaptação do modelo matemático de lógica nebulosa. A adaptação é uma alternativa capaz de representar o comportamento de uma variável subjetiva ao longo de um intervalo de tempo, assim como tratar variáveis estáticas (como o modelo computacional existente). Pesquisas realizadas apontam para uma lacuna no tratamento de variáveis dinâmicas (dependência no tempo) e a proposta permite que o contexto em que as variáveis estão inseridas tenha um papel no entendimento e tomada de decisão de problemas com estas características. Modelos computacionais existentes tratam a questão temporal como sequenciador de eventos ou custo, sem considerar a influência de fenômenos passados na condição corrente, ao contrário do modelo proposto que permite uma contribuição dos acontecimentos anteriores no entendimento e tratamento do estado atual. Apenas para citar alguns exemplos, o uso da solução proposta pode ser aplicado na determinação de nível de conforto em transporte público ou auxiliar na aferição de grau de risco de investimentos no mercado de ações. Em ambos os casos, comparações realizadas entre o modelo de lógica nebulosa existente e a adaptação sugerida apontam uma diferença no resultado final que pode ser entendida como uma maior qualidade na informação de suporte à tomada de decisão.

Mitigação de falhas críticas em sistemas produtivos.

O cenário competitivo e globalizado em que as empresas estão inseridas, sobretudo a partir do século XXI, associados a ciclos de vida cada vez menores dos produtos, rigorosos requisitos de qualidade, além de políticas de preservação do meio ambiente, com redução de consumo energético e de recursos hídricos, somadas às exigências legais de melhores condições de trabalho, resultaram em uma quebra de paradigma nos processos produtivos até então concebidos. Como solução a este novo cenário produtivo pode-se citar o extenso uso da automação industrial, fato que resultou em sistemas cada vez mais complexos, tanto do ponto de vista estrutural, em função do elevado número de componentes, quanto da complexidade dos sistemas de controle. A previsibilidade de todos os estados possíveis do sistema torna-se praticamente impossível. Dentre os estados possíveis pode-se citar os estados de falha que, dependendo da severidade do efeito associado à sua ocorrência, podem resultar em sérios danos para o homem, o meio ambiente e às próprias instalações, caso não sejam corretamente diagnosticados e tratados. Fatos recentes de catástrofes relacionadas à sistemas produtivos revelam a necessidade de se implementar medidas para prevenir e para mitigar os efeitos da ocorrência de falhas, com o objetivo de se evitar a ocorrência de catástrofes. De acordo com especialistas, os Sistemas Instrumentados de Segurança SIS, referenciados em normas como a IEC 61508 e IEC 61511, são uma solução para este tipo de problema. Trabalhos publicados tratam de métodos para a implementação de camadas SIS de prevenção, porém com escassez de trabalhos para camadas SIS de mitigação. Em função do desconhecimento da dinâmica do sistema em estado de falha, técnicas tradicionais de modelagem tornam-se inviáveis. Neste caso, o uso de inteligência artificial, como por exemplo a lógica fuzzy, pode se tornar uma solução para o desenvolvimento do algoritmo de controle, associadas a ferramentas de edição, modelagem e geração dos códigos de controle. A proposta deste trabalho é apresentar uma sistemática para a implementação de um sistema de controle para a mitigação de falhas críticas em sistemas produtivos, com referência às normas IEC 61508/61511, com ação antecipativa à ocorrência de catástrofes.

Phase equilibria of the water + 1-butanol + toluene ternary system at 101.3 kPa

Isobaric vapour–liquid and vapour–liquid–liquid equilibrium data for the water + 1-butanol + toluene ternary system were measured at 101.3 kPa with a modified VLE 602 Fischer apparatus. In addition, the liquid–liquid equilibrium data at 313.15 K were measured and compared with data from other authors at different temperatures. The system exhibits a ternary heterogeneous azeotrope whose temperature and composition have been determined by interpolation. The thermodynamic consistency of the experimental vapour–liquid and vapour–liquid–liquid data was checked by means of the Wisniak’s Li/Wi consistency test. Moreover, the vapour–liquid and the liquid–liquid equilibrium correlation for the ternary system with NRTL and UNIQUAC models, together with the prediction made with the UNIFAC model, were studied and discussed.

Controlo fuzzy semi-activo para aparelhos de amortecimento variável na protecção sísmica

Trabalho apresentado no 10º Congresso Nacional de Sismologia e Engenharia Sísmica, 20-22 abril de 2016, Ponta Delgada, Açores, Portugal

An analysis of the distinction between deep and shallow expert systems /

This paper analyzes the relationship between the techniques used to build expert systems and the behaviors they exhibit to show that there is not sufficient evidence to link the behavioral shortcomings of first-generation expert systems to the shallow methods of representation and inference they employ. There is only evidence that the shortcomings are a consequence of a general lack of knowledge. Moreover, the paper shows that the first-generation of expert systems employ both shallow methods and most of the so-called deep methods. Lastly, we show that deeper methods augment but do not replace shallow reasoning methods; most expert systems should possess both."

A knowledge-based system for liquid retaining structure design with blackboard architecture

Owing to the high degree of vulnerability of liquid retaining structures to corrosion problems, there are stringent requirements in its design against cracking. In this paper, a prototype knowledge-based system is developed and implemented for the design of liquid retaining structures based on the blackboard architecture. A commercially available expert system shell VISUAL RULE STUDIO working as an ActiveX Designer under the VISUAL BASIC programming environment is employed. Hybrid knowledge representation approach with production rules and procedural methods under object-oriented programming are used to represent the engineering heuristics and design knowledge of this domain. It is demonstrated that the blackboard architecture is capable of integrating different knowledge together in an effective manner. The system is tailored to give advice to users regarding preliminary design, loading specification and optimized configuration selection of this type of structure. An example of application is given to illustrate the capabilities of the prototype system in transferring knowledge on liquid retaining structure to novice engineers. (C) 2004 Elsevier Ltd. All rights reserved.

The parameterless self-organizing map algorithm

The parameterless self-organizing map (PLSOM) is a new neural network algorithm based on the self-organizing map (SOM). It eliminates the need for a learning rate and annealing schemes for learning rate and neighborhood size. We discuss the relative performance of the PLSOM and the SOM and demonstrate some tasks in which the SOM fails but the PLSOM performs satisfactory. Finally we discuss some example applications of the PLSOM and present a proof of ordering under certain limited conditions.

Real-Time Gene-Expression Extraction with Fast Classification (FC) Networks

Fast Classification (FC) networks were inspired by a biologically plausible mechanism for short term memory where learning occurs instantaneously. Both weights and the topology for an FC network are mapped directly from the training samples by using a prescriptive training scheme. Only two presentations of the training data are required to train an FC network. Compared with iterative learning algorithms such as Back-propagation (which may require many hundreds of presentations of the training data), the training of FC networks is extremely fast and learning convergence is always guaranteed. Thus FC networks may be suitable for applications where real-time classification is needed. In this paper, the FC networks are applied for the real-time extraction of gene expressions for Chlamydia microarray data. Both the classification performance and learning time of the FC networks are compared with the Multi-Layer Proceptron (MLP) networks and support-vector-machines (SVM) in the same classification task. The FC networks are shown to have extremely fast learning time and comparable classification accuracy.

An empirical study of Hoelfding Racing for model selction in K-nearest neighbor classification

Racing algorithms have recently been proposed as a general-purpose method for performing model selection in machine teaming algorithms. In this paper, we present an empirical study of the Hoeffding racing algorithm for selecting the k parameter in a simple k-nearest neighbor classifier. Fifteen widely-used classification datasets from UCI are used and experiments conducted across different confidence levels for racing. The results reveal a significant amount of sensitivity of the k-nn classifier to its model parameter value. The Hoeffding racing algorithm also varies widely in its performance, in terms of the computational savings gained over an exhaustive evaluation. While in some cases the savings gained are quite small, the racing algorithm proved to be highly robust to the possibility of erroneously eliminating the optimal models. All results were strongly dependent on the datasets used.

On building a principled framework for evaluating and testing evolutionary algorithms: A continuous landscape generator

In this paper, we address some issue related to evaluating and testing evolutionary algorithms. A landscape generator based on Gaussian functions is proposed for generating a variety of continuous landscapes as fitness functions. Through some initial experiments, we illustrate the usefulness of this landscape generator in testing evolutionary algorithms.

Playing in continuous spaces: Some analysis and extension of population-based incremental learning

As an alternative to traditional evolutionary algorithms (EAs), population-based incremental learning (PBIL) maintains a probabilistic model of the best individual(s). Originally, PBIL was applied in binary search spaces. Recently, some work has been done to extend it to continuous spaces. In this paper, we review two such extensions of PBIL. An improved version of the PBIL based on Gaussian model is proposed that combines two main features: a new updating rule that takes into account all the individuals and their fitness values and a self-adaptive learning rate parameter. Furthermore, a new continuous PBIL employing a histogram probabilistic model is proposed. Some experiments results are presented that highlight the features of the new algorithms.

Classifying an opponent's behaviour in robot soccer

This paper illustrates the prediction of opponent behaviour in a competitive, highly dynamic, multi-agent and partially observableenvironment, namely RoboCup small size league robot soccer. The performance is illustrated in the context of the highly successful robot soccer team, the RoboRoos. The project is broken into three tasks; classification of behaviours, modelling and prediction of behaviours and integration of the predictions into the existing planning system. A probabilistic approach is taken to dealing with the uncertainty in the observations and with representing the uncertainty in the prediction of the behaviours. Results are shown for a classification system using a Naïve Bayesian Network that determines the opponent’s current behaviour. These results are compared to an expert designed fuzzy behaviour classification system. The paper illustrates how the modelling system will use the information from behaviour classification to produce probability distributions that model the manner with which the opponents perform their behaviours. These probability distributions are show to match well with the existing multi-agent planning system (MAPS) that forms the core of the RoboRoos system.

Proceedings of the Eighth Australian and New Zealand Intelligent Information Systems Conference

These are the full proceedings of the conference.