Transient stability analysis of electric energy systems via a fuzzy ART-ARTMAP neural network

This work presents a methodology to analyze transient stability (first oscillation) of electric energy systems, using a neural network based on ART architecture (adaptive resonance theory), named fuzzy ART-ARTMAP neural network for real time applications. The security margin is used as a stability analysis criterion, considering three-phase short circuit faults with a transmission line outage. The neural network operation consists of two fundamental phases: the training and the analysis. The training phase needs a great quantity of processing for the realization, while the analysis phase is effectuated almost without computation effort. This is, therefore the principal purpose to use neural networks for solving complex problems that need fast solutions, as the applications in real time. The ART neural networks have as primordial characteristics the plasticity and the stability, which are essential qualities to the training execution and to an efficient analysis. The fuzzy ART-ARTMAP neural network is proposed seeking a superior performance, in terms of precision and speed, when compared to conventional ARTMAP, and much more when compared to the neural networks that use the training by backpropagation algorithm, which is a benchmark in neural network area. (c) 2005 Elsevier B.V. All rights reserved.

Electric load forecasting using a fuzzy ART&ARTMAP neural network

This work presents a neural network based on the ART architecture ( adaptive resonance theory), named fuzzy ART& ARTMAP neural network, applied to the electric load-forecasting problem. The neural networks based on the ARTarchitecture have two fundamental characteristics that are extremely important for the network performance ( stability and plasticity), which allow the implementation of continuous training. The fuzzy ART& ARTMAP neural network aims to reduce the imprecision of the forecasting results by a mechanism that separate the analog and binary data, processing them separately. Therefore, this represents a reduction on the processing time and improved quality of the results, when compared to the Back-Propagation neural network, and better to the classical forecasting techniques (ARIMA of Box and Jenkins methods). Finished the training, the fuzzy ART& ARTMAP neural network is capable to forecast electrical loads 24 h in advance. To validate the methodology, data from a Brazilian electric company is used. (C) 2004 Elsevier B.V. All rights reserved.

Análise da estabilidade transitória via rede neural Art-Artmap fuzzy Euclidiana modificada com treinamento continuado

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Previsão de carga multinodal usando a rede neural ART-ARTMAP fuzzy

Pós-graduação em Engenharia Elétrica - FEIS

Desenvolvimento de redes neurais para previsão de cargas elétricas de sistemas de energia elétrica

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Análise dinâmica de contingências de sistemas de energia elétrica por redes neurais baseadas na teoria da ressonância adaptativa

Pós-graduação em Engenharia Elétrica - FEIS

ArtMap geo-social street art

Il progetto ArtMap! mette a disposizione un applicativo user, destinato agli utenti, che tramite una struttura a social network, propone una mappatura globale di street art. Viene messo a disposizione un archivio di informazioni, aggiornate direttamente dagli utenti, relative a opere ed artisti e la possibilità di creare itinerari personali. Inoltre, è stato sviluppato un applicativo di supporto per la convalidazione delle informazioni inserite dagli utenti, destinato ai gestori del database di informazioni.

Uma contribuição ao estudo das categorias internas e de sua proliferação em redes ARTMAP

ART networks present some advantages: online learning; convergence in a few epochs of training; incremental learning, etc. Even though, some problems exist, such as: categories proliferation, sensitivity to the presentation order of training patterns, the choice of a good vigilance parameter, etc. Among the problems, the most important is the category proliferation that is probably the most critical. This problem makes the network create too many categories, consuming resources to store unnecessarily a large number of categories, impacting negatively or even making the processing time unfeasible, without contributing to the quality of the representation problem, i. e., in many cases, the excessive amount of categories generated by ART networks makes the quality of generation inferior to the one it could reach. Another factor that leads to the category proliferation of ART networks is the difficulty of approximating regions that have non-rectangular geometry, causing a generalization inferior to the one obtained by other methods of classification. From the observation of these problems, three methodologies were proposed, being two of them focused on using a most flexible geometry than the one used by traditional ART networks, which minimize the problem of categories proliferation. The third methodology minimizes the problem of the presentation order of training patterns. To validate these new approaches, many tests were performed, where these results demonstrate that these new methodologies can improve the quality of generalization for ART networks

Transient stability analysis of electrical power systems using a neural network based on fuzzy ARTMAP

This work presents a methodology to analyze transient stability for electric energy systems using artificial neural networks based on fuzzy ARTMAP architecture. This architecture seeks exploring similarity with computational concepts on fuzzy set theory and ART (Adaptive Resonance Theory) neural network. The ART architectures show plasticity and stability characteristics, which are essential qualities to provide the training and to execute the analysis. Therefore, it is used a very fast training, when compared to the conventional backpropagation algorithm formulation. Consequently, the analysis becomes more competitive, compared to the principal methods found in the specialized literature. Results considering a system composed of 45 buses, 72 transmission lines and 10 synchronous machines are presented. © 2003 IEEE.

Detecção e classificação de curto-circuitos em sistemas de distribuição usando rede neural artificial ARTMAP nebulosa

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise de estabilidade transitória de sistemas elétricos por redes neurais ARTMAP nebulosas modulares

Pós-graduação em Engenharia Elétrica - FEIS

Redes neurais artificiais artmap-fuzzy aplicadas ao estudo de agitação marítima e ondas de lagos

Pós-graduação em Engenharia Elétrica - FEIS

Art-Map: concept of moving curatorial project and its practical realization in Aveiro

In this dissertation, I present the results of a project which aim was to find out and try an effective model of independent curatorial project executable in small and medium cities in Portugal. The concept of Moving Curatorial Project ARTMAP is a result of theoretical research and reflection about municipal exhibition spaces and possibility of presentation of the contemporary art in these spaces. To test if this curatorial project is realizable and if there are conditions to continue it, a first trial was implemented in Aveiro. A curated international exhibition, entitled “A Poética do Visual" occupied two municipal and two private gallery spaces and brought together 111 artists from 25 different countries. The art event was carried out in collaboration with the Municipality of Aveiro and the University of Aveiro, and involved several private cultural spaces in the city. This first experience showed that there are all conditions for the presentation of contemporary art in small and medium size locations in Portugal, and for this project to be replicated in other regions of the country.

Engineered Nanoparticles And Organic Matter: A Review Of The State-of-the-art.

Growth in the development and production of engineered nanoparticles (ENPs) in recent years has increased the potential for interactions of these nanomaterials with aquatic and terrestrial environments. Carefully designed studies are therefore required in order to understand the fate, transport, stability, and toxicity of nanoparticles. Natural organic matter (NOM), such as the humic substances found in water, sediment, and soil, is one of the substances capable of interacting with ENPs. This review presents the findings of studies of the interaction of ENPs and NOM, and the possible effects on nanoparticle stability and the toxicity of these materials in the environment. In addition, ENPs and NOM are utilized for many different purposes, including the removal of metals and organic compounds from effluents, and the development of new electronic sensors and other devices for the detection of active substances. Discussion is therefore provided of some of the ways in which NOM can be used in the production of nanoparticles. Although there has been an increase in the number of studies in this area, further progress is needed to improve understanding of the dynamic interactions between ENPs and NOM.

PAH biomarkers for human health risk assessment: a review of the state-of-the-art

Polycyclic aromatic hydrocarbons (PAH) are widely distributed in the environment, and some are carcinogenic to human beings. The study of biomarkers has helped clarify the nature and magnitude of the human health risks posed by such substances. This article provides a review of the state-of-the-art on PAH biomarkers for human health risk assessment and also discusses their applicability within the context of environmental management in Brazil. The article discusses the methodologies for determination of some biomarkers such as 1-hydroxypyrene and PAH-DNA adducts. Cytogenetic markers, frequency of chromosomal aberrations, and micronucleus induction were considered for the evaluation of cancer risk. The current stage of studies on validation of such biomarkers was also approached.