A Neural Network Realization of Fuzzy ART

A neural network realization of the fuzzy Adaptive Resonance Theory (ART) algorithm is described. Fuzzy ART is capable of rapid stable learning of recognition categories in response to arbitrary sequences of analog or binary input patterns. Fuzzy ART incorporates computations from fuzzy set theory into the ART 1 neural network, which learns to categorize only binary input patterns, thus enabling the network to learn both analog and binary input patterns. In the neural network realization of fuzzy ART, signal transduction obeys a path capacity rule. Category choice is determined by a combination of bottom-up signals and learned category biases. Top-down signals impose upper bounds on feature node activations.

Comparative Performance Measures of Fuzzy ARTMAP, Learned Vector Quantization, and Back Propagation for Handwritten Character Recognition

This article compares the performance of Fuzzy ARTMAP with that of Learned Vector Quantization and Back Propagation on a handwritten character recognition task. Training with Fuzzy ARTMAP to a fixed criterion used many fewer epochs. Voting with Fuzzy ARTMAP yielded the highest recognition rates.

Comparison of deterministic, stochastic and fuzzy logic uncertainty modelling for capacity extension projects of DI/WFI pharmaceutical plant utilities with variable/dynamic demand

The last 30 years have seen Fuzzy Logic (FL) emerging as a method either complementing or challenging stochastic methods as the traditional method of modelling uncertainty. But the circumstances under which FL or stochastic methods should be used are shrouded in disagreement, because the areas of application of statistical and FL methods are overlapping with differences in opinion as to when which method should be used. Lacking are practically relevant case studies comparing these two methods. This work compares stochastic and FL methods for the assessment of spare capacity on the example of pharmaceutical high purity water (HPW) utility systems. The goal of this study was to find the most appropriate method modelling uncertainty in industrial scale HPW systems. The results provide evidence which suggests that stochastic methods are superior to the methods of FL in simulating uncertainty in chemical plant utilities including HPW systems in typical cases whereby extreme events, for example peaks in demand, or day-to-day variation rather than average values are of interest. The average production output or other statistical measures may, for instance, be of interest in the assessment of workshops. Furthermore the results indicate that the stochastic model should be used only if found necessary by a deterministic simulation. Consequently, this thesis concludes that either deterministic or stochastic methods should be used to simulate uncertainty in chemical plant utility systems and by extension some process system because extreme events or the modelling of day-to-day variation are important in capacity extension projects. Other reasons supporting the suggestion that stochastic HPW models are preferred to FL HPW models include: 1. The computer code for stochastic models is typically less complex than a FL models, thus reducing code maintenance and validation issues. 2. In many respects FL models are similar to deterministic models. Thus the need for a FL model over a deterministic model is questionable in the case of industrial scale HPW systems as presented here (as well as other similar systems) since the latter requires simpler models. 3. A FL model may be difficult to "sell" to an end-user as its results represent "approximate reasoning" a definition of which is, however, lacking. 4. Stochastic models may be applied with some relatively minor modifications on other systems, whereas FL models may not. For instance, the stochastic HPW system could be used to model municipal drinking water systems, whereas the FL HPW model should or could not be used on such systems. This is because the FL and stochastic model philosophies of a HPW system are fundamentally different. The stochastic model sees schedule and volume uncertainties as random phenomena described by statistical distributions based on either estimated or historical data. The FL model, on the other hand, simulates schedule uncertainties based on estimated operator behaviour e.g. tiredness of the operators and their working schedule. But in a municipal drinking water distribution system the notion of "operator" breaks down. 5. Stochastic methods can account for uncertainties that are difficult to model with FL. The FL HPW system model does not account for dispensed volume uncertainty, as there appears to be no reasonable method to account for it with FL whereas the stochastic model includes volume uncertainty.

Contribution of SO3 to the acid neutralizing capacity of Andosols exposed to strong volcanogenic acid and SO2 deposition

info:eu-repo/semantics/published

Uma abordagem da lógica fuzzy no ensino médio

O uso cada vez mais intenso de conceitos subjetivos - provenientes da lógica fuzzy - aplicados a problemas reais nos motivou a desenvolver procedimentos para a introdução destas idéias no âmbito do ensino médio. O projeto propõe inicialmente o estudo de conjuntos fuzzy que podem ser entendidos com exemplos - de variação populacional, de controle de pragas e de epidemias. Posteriormente, usar as “operações fuzzy” Sup e Inf em produtos de matrizes para realizar diagnósticos e avaliações subjetivas. As situações abordadas já estão na literatura (Barros e Bassanezi, 2006), entretanto não como fonte para o Ensino Médio. Um dos objetivos principais deste trabalho é contrapor a crença de exatidão da matemática clássica com os resultados provenientes de lógica subjetiva, utilizando conceitos apropriados para os estudantes destas séries: teoria dos conjuntos, relações e funções, matrizes, equações de diferenças e outros.

Strong ergodicity of monotone transition functions

By revealing close links among strong ergodicity, monotone, and the Feller–Reuter–Riley (FRR) transition functions, we prove that a monotone ergodic transition function is strongly ergodic if and only if it is not FRR. An easy to check criterion for a Feller minimal monotone chain to be strongly ergodic is then obtained. We further prove that a non-minimal ergodic monotone chain is always strongly ergodic. The applications of our results are illustrated using birth-and-death processes and branching processes.

In vitro-in vivo correlations of self-emulsifying drug delivery systems combining the dynamic lipolysis model and neuro-fuzzy networks

The aim of the current study was to evaluate the potential of the dynamic lipolysis model to simulate the absorption of a poorly soluble model drug compound, probucol, from three lipid-based formulations and to predict the in vitro-in vivo correlation (IVIVC) using neuro-fuzzy networks. An oil solution and two self-micro and nano-emulsifying drug delivery systems were tested in the lipolysis model. The release of probucol to the aqueous (micellar) phase was monitored during the progress of lipolysis. These release profiles compared with plasma profiles obtained in a previous bioavailability study conducted in mini-pigs at the same conditions. The release rate and extent of release from the oil formulation were found to be significantly lower than from SMEDDS and SNEDDS. The rank order of probucol released (SMEDDS approximately SNEDDS > oil formulation) was similar to the rank order of bioavailability from the in vivo study. The employed neuro-fuzzy model (AFM-IVIVC) achieved significantly high prediction ability for different data formations (correlation greater than 0.91 and prediction error close to zero), without employing complex configurations. These preliminary results suggest that the dynamic lipolysis model combined with the AFM-IVIVC can be a useful tool in the prediction of the in vivo behavior of lipid-based formulations.

Strong preference for decapod prey by the western rock lobster Panulirus cygnus

Western rock lobsters, Panulirus cygnus are an abundant benthic consumer distributed along the temperate west coast of Australia and constitute the largest single species fishery in Australia. As a dominant consumer, it is important to understand their predator-prey interactions as they can potentially exert strong trophic effects, and may influence ecosystem function as seen in other spiny lobster species. While previous field studies have focused on the diet composition of P. cygnus, this study investigated their preference for various benthic invertebrate prey to better understand the likely predator-prey interactions of P. cygnus. Prey preferences of small sub-legal juvenile lobsters, as well as medium and large legal-sized mature lobsters were investigated using laboratory feeding trials to identify size-associated differences in lobster prey preference. Handling time and diet quality were investigated to estimate energetic cost and gain from consuming different prey which may explain prey choice by lobsters. It was found that large lobsters preferred crabs and mussels while medium and small lobsters preferred crabs over mussels, gastropods, and sea urchins. This suggests that strong predator-prey interactions between P. cygnus and crabs may occur in the wild.

Strong links between phytoplankton community physiology and dimethylsulphoniopropionate (DMSP) concentrations in the sub-tropical/tropical Atlantic

We present an extensive dataset of dimethylsulphide (DMS, n = 651) and dimethylsulphoniopropionate (DMSP, n = 590) from the Atlantic Meridional Transect programme. These data are used to derive representative depth profiles that illustrate observed natural variations and can be used for DMS and DMSP model-validation in oligotrophic waters. To further understand our dataset, we interpret the data with a wide range of accompanying parameters that characterise the prevailing biogeochemical conditions and phytoplankton community physiology, activity, taxonomic composition, and capacity to cope with light stress. No correlations were observed with typical biomarker pigments for DMSP-producing species. However, strong correlations were found between DMSP and primary production by cells >2 µm in diameter, and between DMSP and some photo-protective pigments. These parameters are measures of mixed phytoplankton communities, so we infer that such associations are likely to be stronger in DMSP-producing organisms. Further work is warranted to develop links between community parameters, DMS and DMSP at the global scale.

Strong responses of Southern Ocean phytoplankton communities to volcanic ash

Volcanic eruptions have been hypothesized as an iron supply mechanism for phytoplankton blooms; however, little direct evidence of stimulatory responses has been obtained in the field. Here we present the results of twenty-one 1–2 day bottle enrichment experiments from cruises in the South Atlantic and Southern Ocean which conclusively demonstrated a photophysiological and biomass stimulation of phytoplankton communities following supply of basaltic or rhyolitic volcanic ash. Furthermore, experiments in the Southern Ocean demonstrated significant phytoplankton community responses to volcanic ash supply in the absence of responses to addition of dissolved iron alone. At these sites, dissolved manganese concentrations were among the lowest ever measured in seawater, and we therefore suggest that the enhanced response to ash may have been a result of the relief of manganese (co)limitation. Our results imply that volcanic ash deposition events could trigger extensive phytoplankton blooms, potentially capable of significant impacts on regional carbon cycling.