An Efficient LS-SVM-Based Method for Fuzzy System Construction

This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the LS-SVMs have their computational advantage over conventional SVMs in the model training process; however, the model sparseness is lost, which is the main drawback of LS-SVMs. This is an open problem for the LS-SVMs. To tackle the nonsparseness issue, a new regression alternative to the Lagrangian solution for the LS-SVM is first presented. A novel efficient learning mechanism is then proposed in this paper to extract a sparse set of support vectors for generating fuzzy IF-THEN rules. This novel mechanism works in a stepwise subset selection manner, including a forward expansion phase and a backward exclusion phase in each selection step. The implementation of the algorithm is computationally very efficient due to the introduction of a few key techniques to avoid the matrix inverse operations to accelerate the training process. The computational efficiency is also confirmed by detailed computational complexity analysis. As a result, the proposed approach is not only able to achieve the sparseness of the resultant LS-SVM-based fuzzy systems but significantly reduces the amount of computational effort in model training as well. Three experimental examples are presented to demonstrate the effectiveness and efficiency of the proposed learning mechanism and the sparseness of the obtained LS-SVM-based fuzzy systems, in comparison with other SVM-based learning techniques.

Privacy-Protected Facial Biometric Verification via Fuzzy Forest Learning

Although visual surveillance has emerged as an effective technolody for public security, privacy has become an issue of great concern in the transmission and distribution of surveillance videos. For example, personal facial images should not be browsed without permission. To cope with this issue, face image scrambling has emerged as a simple solution for privacyrelated applications. Consequently, online facial biometric verification needs to be carried out in the scrambled domain thus bringing a new challenge to face classification. In this paper, we investigate face verification issues in the scrambled domain and propose a novel scheme to handle this challenge. In our proposed method, to make feature extraction from scrambled face images robust, a biased random subspace sampling scheme is applied to construct fuzzy decision trees from randomly selected features, and fuzzy forest decision using fuzzy memberships is then obtained from combining all fuzzy tree decisions. In our experiment, we first estimated the optimal parameters for the construction of the random forest, and then applied the optimized model to the benchmark tests using three publically available face datasets. The experimental results validated that our proposed scheme can robustly cope with the challenging tests in the scrambled domain, and achieved an improved accuracy over all tests, making our method a promising candidate for the emerging privacy-related facial biometric applications.

Towards Possibilistic Fuzzy Answer Set Programming

Fuzzy answer set programming (FASP) is a generalization of answer set programming to continuous domains. As it can not readily take uncertainty into account, however, FASP is not suitable as a basis for approximate reasoning and cannot easily be used to derive conclusions from imprecise information. To cope with this, we propose an extension of FASP based on possibility theory. The resulting framework allows us to reason about uncertain information in continuous domains, and thus also about information that is imprecise or vague. We propose a syntactic procedure, based on an immediate consequence operator, and provide a characterization in terms of minimal models, which allows us to straightforwardly implement our framework using existing FASP solvers.

Modelling of Evaporator in Waste Heat Recovery System using Finite Volume Method and Fuzzy Technique

The evaporator is an important component in the Organic Rankine Cycle (ORC)-based Waste Heat Recovery (WHR) system since the effective heat transfer of this device reflects on the efficiency of the system. When the WHR system operates under supercritical conditions, the heat transfer mechanism in the evaporator is unpredictable due to the change of thermo-physical properties of the fluid with temperature. Although the conventional finite volume model can successfully capture those changes in the evaporator of the WHR process, the computation time for this method is high. To reduce the computation time, this paper develops a new fuzzy based evaporator model and compares its performance with the finite volume method. The results show that the fuzzy technique can be applied to predict the output of the supercritical evaporator in the waste heat recovery system and can significantly reduce the required computation time. The proposed model, therefore, has the potential to be used in real time control applications.

Secagem convectiva de produtos alimentares: otimização e controlo

O presente trabalho tem como objetivo analisar a cinética de secagem do bacalhau salgado verde (Gadus morhua) em secador convectivo. É apresentada a análise da composição físico-química dos bacalhaus utilizados nos ensaios experimentais, bem como o estudo das isotermas de sorção do produto, através de experiências e modelação matemática. Dos modelos usados para o ajuste das isotermas de sorção do bacalhau salgado verde, o que melhor se adaptou aos resultados experimentais foi o modelo de GAB Modificado, com coeficientes de correlação variando entre 0,992 e 0,998. Para o controlo do processo de secagem (nomeadamente os parâmetros temperatura, humidade relativa e velocidade do ar) foi utilizada lógica difusa, através do desenvolvimento de controladores difusos para o humidificador, desumidificador, resistências de aquecimento e ventilador. A modelação do processo de secagem foi realizada através de redes neuronais artificiais (RNA), modelo semi-empírico de Page e modelo difusivo de Fick. A comparação entre dados experimentais e simulados, para cada modelo, apresentou os seguintes erros: entre 1,43 e 11,58 para o modelo de Page, 0,34 e 4,59 para o modelo de Fick e entre 1,13 e 6,99 para a RNA, com médias de 4,38, 1,67 e 2,93 respectivamente. O modelo obtido pelas redes neuronais artificiais foi submetido a um algoritmo de otimização, a fim de buscar os parâmetros ideais de secagem, de forma a minimizar o tempo do processo e maximizar a perda de água do bacalhau. Os parâmetros ótimos obtidos para o processo de secagem, após otimização realizada, para obter-se uma humidade adimensional final de 0,65 foram: tempo de 68,6h, temperatura de 21,45°C, humidade relativa de 51,6% e velocidade de 1,5m/s. Foram também determinados os custos de secagem para as diferentes condições operacionais na instalação experimental. Os consumos por hora de secagem variaram entre 1,15 kWh e 2,87kWh, com uma média de 1,94kWh.

Apuntes del curso Lógica 2, semestre 2009-2

Conjunto de archivos relacionados con los temas de la asignatura Lógica 2: Reglas de Inferencia, ejercicios de lógica resueltos y tareas propuestas para los alumnos de la licenciatura en Filosofía que cursan esta asignatura.

Apuntes del curso de Lógica 2

Contiene la segunda tarea del curso ("TAREA 2-LEF 2ª parte")y una fe de errata a la primera tarea.

La síntesis fenomeno-lógica. Aspectos metódicos de la apropiación heideggeriana de la fenomenología de Husserl

Sabemos que la relación filosófica entre la obra de Edmund Husserl y Martin Heidegger no es un asunto sencillo de abordar. Con facilidad se inclina la balanza hacia uno u otro autor.1 Eso por sí no sería grave, excepto por el hecho de que múltiples interpretaciones de entrada impiden cualquier posibilidad de acercamiento.2 De esa forma uno estaría obligado a tomar posición a favor de uno y en contra del otro. Ese camino evidentemente empobrece la discusión filosófica. Sin embargo, al intentar abordar una posible relación nos encontramos con ciertas interpretaciones de Heidegger que parecen colocar algo en donde todavía no había tal propuesta en su momento. Ante este panorama quisiera intentar destacar algunos aspectos que den luz sobre la relación fenomenológica entre Husserl y Heidegger tomando como hilo conductor las aseveraciones enfáticas de Heidegger en torno al papel que desempeñaron las Investigaciones lógicas (IL) de Husserl en la conformación de su pensar. Evidentemente con este retorno a las IL buscamos poner a prueba la propia interpretación de Heidegger. De esta forma se verá al final si los señalamientos de Heidegger proporcionan el espacio para llevar a cabo un diálogo fructífero que supere posiciones cerradas.