Análise dos indicadores biométricos e nutricionais da cultura da alface (Lactuca sativa L.) irrigada com água tratada magneticamente utilizando modelagem fuzzy

Pós-graduação em Agronomia (Irrigação e Drenagem) - FCA

A support system that delineates location-choice sets for firms seeking office space

Factors influencing the location decisions of offices include traffic, accessibility, employment conditions, economic prospects and land-use policies. Hence tools for supporting real-estate managers and urban planners in such multidimensional decisions may be useful. Accordingly, the objective of this study is to develop a GIS-based tool to support firms who seek office accommodation within a given regional or national study area. The tool relies on a matching approach, in which a firm's characteristics (demand) on the one hand, and environmental conditions and available office spaces (supply) on the other, are analyzed separately in a first step, after which a match is sought. That is, a suitability score is obtained for every firm and for every available office space by applying some value judgments (satisfaction, utility etc.). The latter are powered by a focus on location aspects and expert knowledge about the location decisions of firms/organizations with respect to office accommodation as acquired from a group of real-estate advisers; it is stored in decision tables, and they constitute the core of the model. Apart from the delineation of choice sets for any firm seeking a location, the tool supports two additional types of queries. Firstly, it supports the more generic problem of optimally allocating firms to a set of vacant locations. Secondly, the tool allows users to find firms which meet the characteristics of any given location. Moreover, as a GIS-based tool, its results can be visualized using GIS features which, in turn, facilitate several types of analyses.

Expert system to detect incipient fauts in rotating machines using fuzzy logic and virtual instrumentation

This paper refers to the design of an expert system that captures a waveform through the use of an accelerometer, processes the signal and converts it to the frequency domain using a Fast Fourier Transformer to then, using artificial intelligence techniques, specifically Fuzzy Reasoning, it determines if there is any failure present in the underlying mode of the equipment, such as imbalance, misalignment or bearing defects.

Novas condições de estabilidade de sistemas não lineares utilizando funções de Lyapunov fuzzy

Pós-graduação em Engenharia Elétrica - FEIS

Sistema baseado em regras fuzzy do tipo Takagi-Sugeno aplicado a ecos de radares meteorológicos

Pós-graduação em Ciências Ambientais - Sorocaba

Análise da eficiência energética em indústrias madeireiras através da lógica fuzzy

This paper presents the application of fuzzy theory to support the decision of implementing energy efficiency program in sawmills operating in the processing of Pinustaeda and Pinuselliotii. The justification of using a system based on fuzzy theory for analysis of consumption and the specific factors involved, such is the diversity of rates / factors. With the fuzzy theory, we can build a reliable system for verifying actual energy efficiency. The indices and factors characteristic of industrial activity were measured and used as the basis for the fuzzy system. We developed a management system and technology. The system involves the management practices in energy efficiency, maintenance of plant and equipment and the presence of qualified staff. The technological system involves the power factor, load factor, the factor of demand and the specific consumption. The first response provides the possibility of increased energy efficiency and the second level of energy efficiency in the industry studied. With this tool, programs can be developed for energy conservation and energy efficiency in the industrial timber with wide application in this area that is as diverse as production processes. The same systems developed can be used in other industrial activities, provided they are used indices and characteristic features of the sectors involved.

Aplicação da teoria fuzzy no controle de sistemas de geração de energias alternativas

This paper presents the application and use of a methodology based on fuzzy theory and simulates its use in intelligent control of a hybrid system for generating electricity, using solar energy, photovoltaic and wind. When using a fuzzy control system, it reached the point of maximum generation of energy, thus shifting all energy generated from the alternative sources-solar photovoltaic and wind, cargo and / or batteries when its use not immediately. The model uses three variables used for entry, which are: wind speed, solar radiation and loading the bank of batteries. For output variable has to choose which of the batteries of the battery bank is charged. For the simulations of this work is used MATLAB software. In this environment mathematical computational are analyzed and simulated all mathematical modeling, rules and other variables in the system described fuzzy. This model can be used in a system of control of hybrid systems for generating energy, providing the best use of energy sources, sun and wind, so we can extract the maximum energy possible these alternative sources without any prejudice to the environment.

Fuzzy logic to evaluate vitality of Catasetum fimbiratum species (Orchidacea)

The fuzzy logic accepts infinite intermediate logical values between false and true. In view of this principle, a system based on fuzzy rules was established to provide the best management of Catasetum fimbriatum. For the input of the developed fuzzy system, temperature and shade variables were used, and for the output, the orchid vitality. The system may help orchid experts and amateurs to manage this species. ?Low? (L), ?Medium? (M) and ?High? (H) were used as linguistic variables. The objective of the study was to develop a system based on fuzzy rules to improve management of the Catasetum fimbriatum species, as its production presents some difficulties, and it offers high added value

Plataforma computacional fuzzy para avaliação nos estágios do tomateiro dos efeitos da irrigação e salinidade da água

Pós-graduação em Agronegócio e Desenvolvimento - Tupã

Análise envoltória de dados combinada com a lógica fuzzy em problemas de avaliação de eficiência de máquinas de consumo: um estudo em empresa do segmento farmacêutico

The pharmaceutical industry was consolidated in Brazil in the 1930s, and since then has become increasingly competitive. Therefore the implementation of the Toyota Production System, which aims to lean production, has become common among companies in the segment. The main efficiency indicator currently used is the Overall Equipment Effectiveness (OEE). This paper intends to, using the fuzzy model DEA-BCC, analyze the efficiency of the production lines of a pharmaceutical company in the Paraíba Valley, compare the values obtained by the model with those calculated by the OEE, identify the most sensitive machines to variation in the data input and develop a ranking of effectiveness between the consumer machinery. After the development, it is shown that the accuracy of the relationship between the two methods is approximately 57% and the line considered the most effective by the Toyota Production System is not the same as the one found by this paper

Modelagem fuzzy de dados climáticos estimados por modelo matemático - CCATT-BRAMS

Pós-graduação em Engenharia Mecânica - FEG

‘Gene shaving’ as a method for identifying distinct sets of genes with similar expression patterns

Background: Large gene expression studies, such as those conducted using DNA arrays, often provide millions of different pieces of data. To address the problem of analyzing such data, we describe a statistical method, which we have called ‘gene shaving’. The method identifies subsets of genes with coherent expression patterns and large variation across conditions. Gene shaving differs from hierarchical clustering and other widely used methods for analyzing gene expression studies in that genes may belong to more than one cluster, and the clustering may be supervised by an outcome measure. The technique can be ‘unsupervised’, that is, the genes and samples are treated as unlabeled, or partially or fully supervised by using known properties of the genes or samples to assist in finding meaningful groupings. Results: We illustrate the use of the gene shaving method to analyze gene expression measurements made on samples from patients with diffuse large B-cell lymphoma. The method identifies a small cluster of genes whose expression is highly predictive of survival. Conclusions: The gene shaving method is a potentially useful tool for exploration of gene expression data and identification of interesting clusters of genes worth further investigation.

Managing Large Data Sets Using Support Vector Machines

Hundreds of Terabytes of CMS (Compact Muon Solenoid) data are being accumulated for storage day by day at the University of Nebraska-Lincoln, which is one of the eight US CMS Tier-2 sites. Managing this data includes retaining useful CMS data sets and clearing storage space for newly arriving data by deleting less useful data sets. This is an important task that is currently being done manually and it requires a large amount of time. The overall objective of this study was to develop a methodology to help identify the data sets to be deleted when there is a requirement for storage space. CMS data is stored using HDFS (Hadoop Distributed File System). HDFS logs give information regarding file access operations. Hadoop MapReduce was used to feed information in these logs to Support Vector Machines (SVMs), a machine learning algorithm applicable to classification and regression which is used in this Thesis to develop a classifier. Time elapsed in data set classification by this method is dependent on the size of the input HDFS log file since the algorithmic complexities of Hadoop MapReduce algorithms here are O(n). The SVM methodology produces a list of data sets for deletion along with their respective sizes. This methodology was also compared with a heuristic called Retention Cost which was calculated using size of the data set and the time since its last access to help decide how useful a data set is. Accuracies of both were compared by calculating the percentage of data sets predicted for deletion which were accessed at a later instance of time. Our methodology using SVMs proved to be more accurate than using the Retention Cost heuristic. This methodology could be used to solve similar problems involving other large data sets.

Análise envoltória de dados combinada com a lógica fuzzy em problemas de avaliação de eficiência de máquinas de consumo: um estudo em empresa do segmento farmacêutico

The pharmaceutical industry was consolidated in Brazil in the 1930s, and since then has become increasingly competitive. Therefore the implementation of the Toyota Production System, which aims to lean production, has become common among companies in the segment. The main efficiency indicator currently used is the Overall Equipment Effectiveness (OEE). This paper intends to, using the fuzzy model DEA-BCC, analyze the efficiency of the production lines of a pharmaceutical company in the Paraíba Valley, compare the values obtained by the model with those calculated by the OEE, identify the most sensitive machines to variation in the data input and develop a ranking of effectiveness between the consumer machinery. After the development, it is shown that the accuracy of the relationship between the two methods is approximately 57% and the line considered the most effective by the Toyota Production System is not the same as the one found by this paper

Modelagem fuzzy de dados climáticos estimados por modelo matemático - CCATT-BRAMS

Pós-graduação em Engenharia Mecânica - FEG