Desenvolvimento de um sistema hierárquico de classificação com aplicação baseada em abordagem Fuzzy

Land cover mappings represent important tools for the regional planning. However, the current mappings are related to very specific purposes and, consequently, they are limited in their capacity to define the wide variety of existing types of land cover. In that context, this paper aims at developing a wide and including hierarchical classification system for land cover mapping in regional scale, which should contribute for a future standardization of classes. Besides, it is intended to test that system for a study case that contemplates the use of a classification method based on fuzzy approach, which has shown to be more appropriate than conventional approaches. Therefore, it was proposed a hierarchical classification system with three detailing levels and a study case was defined with the specification of the test area and of the classification project. Then, the georreferencing of a TM/Landsat-5 image that comprises the test area was carried out. Later, it was applied a fuzzy classification approach in the TM/Landsat-5 image, starting from images of probability for the mapped classes and an uncertainty image were generated. Finally, it was produced a conventional output that represents the thematic mapping of the test area.

Lógica BDI fuzzy

Intendding to understand how the human mind operates, some philosophers and psycologists began to study about rationality. Theories were built from those studies and nowadays that interest have been extended to many other areas such as computing engineering and computing science, but with a minimal distinction at its goal: to understand the mind operational proccess and apply it on agents modelling to become possible the implementation (of softwares or hardwares) with the agent-oriented paradigm where agents are able to deliberate their own plans of actions. In computing science, the sub-area of multiagents systems has progressed using several works concerning artificial intelligence, computational logic, distributed systems, games theory and even philosophy and psycology. This present work hopes to show how it can be get a logical formalisation extention of a rational agents architecture model called BDI (based in a philosophic Bratman s Theory) in which agents are capable to deliberate actions from its beliefs, desires and intentions. The formalisation of this model is called BDI logic and it is a modal logic (in general it is a branching time logic) with three access relations: B, D and I. And here, it will show two possible extentions that tranform BDI logic in a modal-fuzzy logic where the formulae and the access relations can be evaluated by values from the interval [0,1]

Sistema especialista fuzzy para dimensionamento de bombeio mecânico

Despite the emergence of other forms of artificial lift, sucker rod pumping systems remains hegemonic because of its flexibility of operation and lower investment cost compared to other lifting techniques developed. A successful rod pumping sizing necessarily passes through the supply of estimated flow and the controlled wear of pumping equipment used in the mounted configuration. However, the mediation of these elements is particularly challenging, especially for most designers dealing with this work, which still lack the experience needed to get good projects pumping in time. Even with the existence of various computer applications on the market in order to facilitate this task, they must face a grueling process of trial and error until you get the most appropriate combination of equipment for installation in the well. This thesis proposes the creation of an expert system in the design of sucker rod pumping systems. Its mission is to guide a petroleum engineer in the task of selecting a range of equipment appropriate to the context provided by the characteristics of the oil that will be raised to the surface. Features such as the level of gas separation, presence of corrosive elements, possibility of production of sand and waxing are taken into account in selecting the pumping unit, sucker-rod strings and subsurface pump and their operation mode. It is able to approximate the inferente process in the way of human reasoning, which leads to results closer to those obtained by a specialist. For this, their production rules were based on the theory of fuzzy sets, able to model vague concepts typically present in human reasoning. The calculations of operating parameters of the pumping system are made by the API RP 11L method. Based on information input, the system is able to return to the user a set of pumping configurations that meet a given design flow, but without subjecting the selected equipment to an effort beyond that which can bear

A fuzzy inference system for identification of crossflow filtration processes

The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behavior. In this paper, a system based on fuzzy logic systems is developed to overcome the problems usually found in the conventional mathematical models. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the fuzzy approach. Simulation results are presented to justify the validity of the proposed approach.

Lógica fuzzy na avaliação da fertilidade do solo e produtividade do café conilon

The objective of this study was to analyze, using the geoestatistic and a system of classification fuzzy, the fertility of an experimental area with base in chemical attributes of the soil and its relationship with the productivity of the conilon coffee. The study was accomplished in the experimental farm of the INCAPER - ES. The soil samples were collected in the depth of 0 - 0.2 m, being analyzed the attributes: matches, potassium, calcium and magnesium, aluminum, sum of bases, cation exchange capacity (pH 7), and saturation percentage. The data were submitted to a descriptive, exploratory, and geostatistical analysis. A system of fuzzy classification was applied using the attributes described to infer about the fertility of the soil and its relationship with the productivity of the culture. The fertility possibility presented positive spatial relationship with the productivity of the culture, with higher values of this where the possibility of fertile soil is superior.

Efficient parametric adjustment of fuzzy inference system using unconstrained optimization

This paper presents a new methodology for the adjustment of fuzzy inference systems, which uses technique based on error back-propagation method. The free parameters of the fuzzy inference system, such as its intrinsic parameters of the membership function and the weights of the inference rules, are automatically adjusted. This methodology is interesting, not only for the results presented and obtained through computer simulations, but also for its generality concerning to the kind of fuzzy inference system used. Therefore, this methodology is expandable either to the Mandani architecture or also to that suggested by Takagi-Sugeno. The validation of the presented methodology is accomplished through estimation of time series and by a mathematical modeling problem. More specifically, the Mackey-Glass chaotic time series is used for the validation of the proposed methodology. © Springer-Verlag Berlin Heidelberg 2007.

Development of a water quality index using a fuzzy logic: A case study for the sorocaba river

Due to growing urbanization and industrialization, the environment is suffering from pollution of rivers, degradation of soils and deteriorated air quality. Quality indices appear to be useful to evaluate the conditions of these media. The aim of this study was the development of a water quality index using a fuzzy inference system, since such an approach has proved advantageous in addressing problems that are subjective by nature or for which the data are uncertain. The methodology employed was based on this inference system, and considered the nine water quality parameters employed by CETESB (Companhia de Tecnologia de Saneamento Ambiental, São Paulo, Brazil) to evaluate water quality. After assessment of the data using the index, a comparison was made with the WQI (Water Quality Index), which is used for the monitoring of various water bodies, including in the study region. The results obtained using the index developed on the basis of fuzzy inference were found to be more useful than those derived from the method currently used by CETESB, since losses and/or omissions concerning individual parameters were minimized. © 2010 IEEE.

Aplicação de um sistema de Inferência Fuzzy de suporte à decisão para estimação de valores de ações cotadas na Bolsa de Valores de São Paulo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estimação da densidade de solos utilizando sistemas de inferência fuzzy

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Simulação e controle de um quadcopter utilizando lógica fuzzy

The present work develops a model to simulate the dynamics of a quadcopter being controlled by a PD fuzzy controller. Initially is presented a brief history of quadcopters an introduction to fuzzy logic and fuzzy control systems. Afterwards is presented an overview of the quadcopter dynamics and the mathematical modelling development applying Newton-Euler method. Then the modelling are implemented in a Simulink model in addition to a PD fuzzy controller. A prototype proposition is made, by describing each necessary component to build up a quadcopter. In the end the results from the simulators are discussed and compared due to the discrepancy between the model using ideal sensor and the model using non-ideal sensors

Classification of histological images based on the stationary wavelet transform

Non-Hodgkin lymphomas are of many distinct types, and different classification systems make it difficult to diagnose them correctly. Many of these systems classify lymphomas only based on what they look like under a microscope. In 2008 the World Health Organisation (WHO) introduced the most recent system, which also considers the chromosome features of the lymphoma cells and the presence of certain proteins on their surface. The WHO system is the one that we apply in this work. Herewith we present an automatic method to classify histological images of three types of non-Hodgkin lymphoma. Our method is based on the Stationary Wavelet Transform (SWT), and it consists of three steps: 1) extracting sub-bands from the histological image through SWT, 2) applying Analysis of Variance (ANOVA) to clean noise and select the most relevant information, 3) classifying it by the Support Vector Machine (SVM) algorithm. The kernel types Linear, RBF and Polynomial were evaluated with our method applied to 210 images of lymphoma from the National Institute on Aging. We concluded that the following combination led to the most relevant results: detail sub-band, ANOVA and SVM with Linear and RBF kernels.

Development of a new galaxy classification technique and its application to the zCOSMOS survey

The purpose of this Thesis is to develop a robust and powerful method to classify galaxies from large surveys, in order to establish and confirm the connections between the principal observational parameters of the galaxies (spectral features, colours, morphological indices), and help unveil the evolution of these parameters from $z \sim 1$ to the local Universe. Within the framework of zCOSMOS-bright survey, and making use of its large database of objects ($\sim 10\,000$ galaxies in the redshift range $0 < z \lesssim 1.2$) and its great reliability in redshift and spectral properties determinations, first we adopt and extend the \emph{classification cube method}, as developed by Mignoli et al. (2009), to exploit the bimodal properties of galaxies (spectral, photometric and morphologic) separately, and then combining together these three subclassifications. We use this classification method as a test for a newly devised statistical classification, based on Principal Component Analysis and Unsupervised Fuzzy Partition clustering method (PCA+UFP), which is able to define the galaxy population exploiting their natural global bimodality, considering simultaneously up to 8 different properties. The PCA+UFP analysis is a very powerful and robust tool to probe the nature and the evolution of galaxies in a survey. It allows to define with less uncertainties the classification of galaxies, adding the flexibility to be adapted to different parameters: being a fuzzy classification it avoids the problems due to a hard classification, such as the classification cube presented in the first part of the article. The PCA+UFP method can be easily applied to different datasets: it does not rely on the nature of the data and for this reason it can be successfully employed with others observables (magnitudes, colours) or derived properties (masses, luminosities, SFRs, etc.). The agreement between the two classification cluster definitions is very high. ``Early'' and ``late'' type galaxies are well defined by the spectral, photometric and morphological properties, both considering them in a separate way and then combining the classifications (classification cube) and treating them as a whole (PCA+UFP cluster analysis). Differences arise in the definition of outliers: the classification cube is much more sensitive to single measurement errors or misclassifications in one property than the PCA+UFP cluster analysis, in which errors are ``averaged out'' during the process. This method allowed us to behold the \emph{downsizing} effect taking place in the PC spaces: the migration between the blue cloud towards the red clump happens at higher redshifts for galaxies of larger mass. The determination of $M_{\mathrm{cross}}$ the transition mass is in significant agreement with others values in literature.

Classification of thoracolumbar fractures and dislocations

A classification of injuries is necessary in order to develop a common language for treatment indications and outcomes. Several classification systems have been proposed, the most frequently used is the Denis classification. The problem of this classification system is that it is based on an assumption, which is anatomically unidentifiable: the so-called middle column. For this reason, few years ago, a group of spine surgeons has developed a new classification system, which is based on the severity of the injury. The severity is defined by the pathomorphological findings, the prognosis in terms of healing and potential of neurological damage. This classification is based on three major groups: A = isolated anterior column injuries by axial compression, B = disruption of the posterior ligament complex by distraction posteriorly, and group C = corresponding to group B but with rotation. There is an increasing severity from A to C, and within each group, the severity usually increases within the subgroups from .1, .2, .3. All these pathomorphologies are supported by a mechanism of injury, which is responsible for the extent of the injury. The type of injury with its groups and subgroups is able to suggest the treatment modality.

Classification of intervertebral disk degeneration with axial T2 mapping

OBJECTIVE: The aim of this study was to establish an MRI classification system for intervertebral disks using axial T2 mapping, with a special focus on evaluating early degenerative intervertebral disks. MATERIALS AND METHODS: Twenty-nine healthy volunteers (19 men, 10 women; age range, 20-44 years; mean age, 31.8 years) were studied, and axial T2 mapping was performed for the L3-L4, L4-L5, and L5-S1 intervertebral disks. Grading was performed using three classification systems for degenerative disks: our system using axial T2 mapping and two other conventional classification systems that focused on the signal intensity of the nucleus pulposus or the structural morphology in sagittal T2-weighted MR images. We analyzed the relationship between T2, which is known to correlate with change in composition of intervertebral disks, and degenerative grade determined using the three classification systems. RESULTS: With axial T2 mapping, differences in T2 between grades I and II were smaller and those between grades II and III, and between grades III and IV, were larger than those with the other grading systems. The ratio of intervertebral disks classified as grade I was higher with the conventional classification systems than that with axial T2 mapping. In contrast, the ratio of intervertebral disks classified as grade II or III was higher with axial T2 mapping than that with the conventional classification systems. CONCLUSION: Axial T2 mapping provides a more T2-based classification. The new system may be able to detect early degenerative changes before the conventional classification systems can.

Towards a consensus on a hearing preservation classification system

The comprehensive Hearing Preservation classification system presented in this paper is suitable for use for all cochlear implant users with measurable pre-operative residual hearing. If adopted as a universal reporting standard, as it was designed to be, it should prove highly beneficial by enabling future studies to quickly and easily compare the results of previous studies and meta-analyze their data. Objectives: To develop a comprehensive Hearing Preservation classification system suitable for use for all cochlear implant users with measurable pre-operative residual hearing. Methods: The HEARRING group discussed and reviewed a number of different propositions of a HP classification systems and reviewed critical appraisals to develop a qualitative system in accordance with the prerequisites. Results: The Hearing Preservation Classification System proposed herein fulfills the following necessary criteria: 1) classification is independent from users' initial hearing, 2) it is appropriate for all cochlear implant users with measurable pre-operative residual hearing, 3) it covers the whole range of pure tone average from 0 to 120 dB; 4) it is easy to use and easy to understand.