977 resultados para Fuzzy linguistic variable
Resumo:
Increasing global competitiveness worldwide has forced manufacturing organizations to produce high-quality products more quickly and at a competitive cost. In order to reach these goals, they need good quality components from suppliers at optimum price and lead time. This actually forced all the companies to adapt different improvement practices such as lean manufacturing, Just in Time (JIT) and effective supply chain management. Applying new improvement techniques and tools cause higher establishment costs and more Information Delay (ID). On the contrary, these new techniques may reduce the risk of stock outs and affect supply chain flexibility to give a better overall performance. But industry people are unable to measure the overall affects of those improvement techniques with a standard evaluation model .So an effective overall supply chain performance evaluation model is essential for suppliers as well as manufacturers to assess their companies under different supply chain strategies. However, literature on lean supply chain performance evaluation is comparatively limited. Moreover, most of the models assumed random values for performance variables. The purpose of this paper is to propose an effective supply chain performance evaluation model using triangular linguistic fuzzy numbers and to recommend optimum ranges for performance variables for lean implementation. The model initially considers all the supply chain performance criteria (input, output and flexibility), converts the values to triangular linguistic fuzzy numbers and evaluates overall supply chain performance under different situations. Results show that with the proposed performance measurement model, improvement area for each variable can be accurately identified.
Resumo:
Backgrounds Ea aims: The boundaries between the categories of body composition provided by vectorial analysis of bioimpedance are not well defined. In this paper, fuzzy sets theory was used for modeling such uncertainty. Methods: An Italian database with 179 cases 18-70 years was divided randomly into developing (n = 20) and testing samples (n = 159). From the 159 registries of the testing sample, 99 contributed with unequivocal diagnosis. Resistance/height and reactance/height were the input variables in the model. Output variables were the seven categories of body composition of vectorial analysis. For each case the linguistic model estimated the membership degree of each impedance category. To compare such results to the previously established diagnoses Kappa statistics was used. This demanded singling out one among the output set of seven categories of membership degrees. This procedure (defuzzification rule) established that the category with the highest membership degree should be the most likely category for the case. Results: The fuzzy model showed a good fit to the development sample. Excellent agreement was achieved between the defuzzified impedance diagnoses and the clinical diagnoses in the testing sample (Kappa = 0.85, p < 0.001). Conclusions: fuzzy linguistic model was found in good agreement with clinical diagnoses. If the whole model output is considered, information on to which extent each BIVA category is present does better advise clinical practice with an enlarged nosological framework and diverse therapeutic strategies. (C) 2012 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Resumo:
Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.
Resumo:
Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.
Resumo:
Abstract A fuzzy linguistic model based on the Mamdani method with input variables, particulate matter, sulfur dioxide, temperature and wind obtained from CETESB with two membership functions each was built to predict the average hospitalization time due to cardiovascular diseases related to exposure to air pollutants in São José dos Campos in the State of São Paulo in 2009. The output variable is the average length of hospitalization obtained from DATASUS with six membership functions. The average time given by the model was compared to actual data using lags of 0 to 4 days. This model was built using the Matlab v. 7.5 fuzzy toolbox. Its accuracy was assessed with the ROC curve. Hospitalizations with a mean time of 7.9 days (SD = 4.9) were recorded in 1119 cases. The data provided revealed a significant correlation with the actual data according to the lags of 0 to 4 days. The pollutant that showed the greatest accuracy was sulfur dioxide. This model can be used as the basis of a specialized system to assist the city health authority in assessing the risk of hospitalizations due to air pollutants.
Resumo:
Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica
Resumo:
Pós-graduação em Engenharia Mecânica - FEG
Resumo:
Pós-graduação em Engenharia Mecânica - FEG
Resumo:
We propose a fuzzy approach to deal with risk analysis for information systems. We extend MAGERIT methodology that valuates the asset dependencies to a fuzzy framework adding fuzzy linguistic terms to valuate the different elements (terminal asset values, asset dependencies as well as the probability of threats and the resulting asset degradation) in risk analysis. Computations are based on the trapezoidal fuzzy numbers associated with these linguistic terms and, finally, the results of these operations are translated into a linguistic term by means of a similarity function.
Resumo:
In this paper, a fuzzy based Variable Structure Control (VSC) with guaranteed stability is presented. The main objective is to obtain an improved performance of highly non-linear unstable systems. The main contribution of this work is that, firstly, new functions for chattering reduction and error convergence without sacrificing invariant properties are proposed, which is considered the main drawback of the VSC control. Secondly, the global stability of the controlled system is guaranteed.The well known weighting parameters approach, is used in this paper to optimize local and global approximation and modeling capability of T-S fuzzy model.A one link robot is chosen as a nonlinear unstable system to evaluate the robustness, effectiveness and remarkable performance of optimization approach and the high accuracy obtained in approximating nonlinear systems in comparison with the original T-S model. Simulation results indicate the potential and generality of the algorithm. The application of the proposed FLC-VSC shows that both alleviation of chattering and robust performance are achieved with the proposed FLC-VSC controller. The effectiveness of the proposed controller is proven in front of disturbances and noise effects.
Resumo:
In the paper learning algorithm for adjusting weight coefficients of the Cascade Neo-Fuzzy Neural Network (CNFNN) in sequential mode is introduced. Concerned architecture has the similar structure with the Cascade-Correlation Learning Architecture proposed by S.E. Fahlman and C. Lebiere, but differs from it in type of artificial neurons. CNFNN consists of neo-fuzzy neurons, which can be adjusted using high-speed linear learning procedures. Proposed CNFNN is characterized by high learning rate, low size of learning sample and its operations can be described by fuzzy linguistic “if-then” rules providing “transparency” of received results, as compared with conventional neural networks. Using of online learning algorithm allows to process input data sequentially in real time mode.
Resumo:
Research on child bilingualism accounts for differences in the course and the outcomes of monolingual and different types of bilingual language acquisition primarily from two perspectives: age of onset of exposure to the language(s) and the role of the input (Genesee, Paradis, & Crago, 2004; Meisel, 2009; Unsworth et al., 2014). Some findings suggest that early successive bilingual children may pattern similarly to simultaneous bilingual children, passing through different trajectories from child L2 learners due to a later age of onset in the latter group. Studies on bilingual development have also shown that input quantity in bilingual acquisition is considerably reduced, i.e., in each of their two languages, bilingual children are likely exposed to much less input than their monolingual peers (Paradis & Genesee, 1996; Unsworth, 2013b). At the same time, simultaneous bilingual children develop and attain competence in the two languages, sometimes without even an attested age delay compared to monolingual children (Paradis, Genesee & Crago, 2011). The implication is that even half of the input suffices for early language development, at least with respect to ‘core’ aspects of language, in whatever way ‘core’ is defined.My aim in this article is to consider how an additional, linguistic variable interacts with age of onset and input in bilingual development, namely, the timing in L1 development of the phenomena examined in bilingual children’s performance. Specifically, I will consider timing differences attested in the monolingual development of features and structures, distinguishing between early, late or ‘very late’ acquired phenomena. I will then argue that this three-way distinction reflects differences in the role of narrow syntax: early phenomena are core, parametric and narrowly syntactic, in contrast to late and very late phenomena, which involve syntax-external or even language-external resources too. I explore the consequences of these timing differences in monolingual development for bilingual development. I will review some findings from early (V2 in Germanic, grammatical gender in Greek), late (passives) and very late (grammatical gender in Dutch) phenomena in the bilingual literature and argue that early phenomena can differentiate between simultaneous and (early) successive bilingualism with an advantage for the former group, while the other two reveal similarly (high or low) performance across bilingual groups, differentiating them from monolinguals. The paper proposes that questions about the role of age of onset and language input in early bilingual development can only be meaningfully addressed when the properties and timing of the phenomena under investigation are taken into account.
Resumo:
Um dos postulados da linguística do início do século XX é o de que o objeto da linguística deveria identificar-se com a parte homogênea dos fenômenos observáveis. Na segunda metade desse século, a sociolinguística representou uma ruptura significativa com o formalismo teórico mediante a introdução do conceito de variável linguística, mas, ao mesmo tempo, dele se aproximou ao adotar o conceito de regra variável. Este trabalho pretende discutir criticamente essa posição encarecendo a necessidade de repropor mais plenamente o falante enquanto agente condutor de seu próprio discurso e, consequentemente, a noção de variável linguística como o espaço privilegiado da construção do significado social da linguagem.
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Resumo:
This paper proposes a reflection on processes of variation and change that occurred with the portuguese prepositions a, ate, em and para, taken as a parameter for answers in a broader context, the confrontation between the norm and use and between standard and linguistic variation. We conducted the study based on a corpus composed of all occurrences of the prepositions in question removed news of the newspaper O Combate and O Estado de Sao Paulo. Whereas the main objective of the study is to present and describe the use of these particles in newspaper articles of the Imprensa Paulista, data were collected and quantified by using the statistical package GOLDVARB, and interpretation of results relied (i) assumptions regarding the process variation in the use of prepositions and prepositions replace weak, as the preposition to, for strong prepositions (para, em, até), (ii) in comparison with the grammatical rule in effect at the time, (iii) and in the search for the existence of some historical factor that justifies the selection of a preposition rather than another. Among the hypotheses, we investigate the relationship between these prepositions and whose kind of preachers they introduce supplements: the direction of motion (abstract or concrete) or transfer (material and verbal / perceptual). This theoretical perspective was the Labovian sociolinguistics (Labov, 1972, 1994), which defines the linguistic variable as a representation of two or more different ways to convey a certain information content, being necessary to define it the following criteria set exact number of variants to establish all the multiplicity of contexts in which it appears; develop a quantitative index for measuring the values of variables