Automatic synthesis of fuzzy systems: An evolutionary overview with a genetic programming perspective

Studies in Evolutionary Fuzzy Systems (EFSs) began in the 90s and have experienced a fast development since then, with applications to areas such as pattern recognition, curve‐fitting and regression, forecasting and control. An EFS results from the combination of a Fuzzy Inference System (FIS) with an Evolutionary Algorithm (EA). This relationship can be established for multiple purposes: fine‐tuning of FIS's parameters, selection of fuzzy rules, learning a rule base or membership functions from scratch, and so forth. Each facet of this relationship creates a strand in the literature, as membership function fine‐tuning, fuzzy rule‐based learning, and so forth and the purpose here is to outline some of what has been done in each aspect. Special focus is given to Genetic Programming‐based EFSs by providing a taxonomy of the main architectures available, as well as by pointing out the gaps that still prevail in the literature. The concluding remarks address some further topics of current research and trends, such as interpretability analysis, multiobjective optimization, and synthesis of a FIS through Evolving methods

An Application of Combined Neural Networks to Remotely Sensed Images

Studies in the area of pattern recognition have indicated that in most cases a classifier performs differently from one pattern class to another. This observation gave birth to the idea of combining the individual results from different classifiers to derive a consensus decision. This work investigates the potential of combining neural networks to remotely sensed images. A classifier system is built by integrating the results of a plurarity of feed-forward neural networks, each of them designed to have the best performance for one class. Fuzzy Integrals are used as the combining strategy. Experiments carried out to evaluate the system, using a satellite image of an area undergoing a rapid degradation process, have shown that the combination may yield a better performance than that of a single neural network

Warning systems in a computerized nursing process for Intensive Care Units

A hybrid study combining technological production and methodological research aiming to establish associations between the data and information that are part of a Computerized Nursing Process according to the ICNP® Version 1.0, indicators of patient safety and quality of care. Based on the guidelines of the Agency for Healthcare Research and Quality and the American Association of Critical Care Nurses for the expansion of warning systems, five warning systems were developed: potential for iatrogenic pneumothorax, potential for care-related infections, potential for suture dehiscence in patients after abdominal or pelvic surgery, potential for loss of vascular access, and potential for endotracheal extubation. The warning systems are a continuous computerized resource of essential situations that promote patient safety and enable the construction of a way to stimulate clinical reasoning and support clinical decision making of nurses in intensive care

GPFIS - control : a genetic fuzzy system for control tasks

This work presents a Genetic Fuzzy Controller (GFC), called Genetic Programming Fuzzy Inference System for Control tasks (GPFISControl). It is based on MultiGene Genetic Programming, a variant of canonical Genetic Programming. The main characteristics and concepts of this approach are described, as well as its distinctions from other GFCs. Two benchmarks application of GPFISControl are considered: the CartCentering Problem and the Inverted Pendulum. In both cases results demonstrate the superiority and potentialities of GPFISControl in relation to other GFCs found in the literature

La Categoría precisión en la meta-evaluación: aspectos prácticos y teóricos en un nuevo enfoque A categoria precisão na avaliação e na meta-avaliação: aspectos práticos e teóricos em um novo enfoque The category precision in the evaluation and meta- evaluation: practical and theoretical aspects

Este artículo trata de la categoría precisión de una verdadera evaluación en el ámbito de la evaluación y de la meta evaluación (evaluación de la evaluación). Presenta, inicialmente, la conceptuación moderna de la evaluación y de la meta evaluación para, entonces, discutir el papel de la meta evaluación de asegurar la calidad de un proceso evaluativo, en sus diferentes enfoques, a partir de las cuatro categorías de una verdadera evaluación (utilidad, viabilidad, ética y precisión). La énfasis del artículo está en la categoría precisión: (i) su importancia en una meta evaluación, en todas las fases o etapas de una evaluación, con sus avances y sus limitaciones y; (ii) su aplicación en la propia meta evaluación que, como proceso evaluativo, también debe respetar los cuatro patrones de una verdadera evaluación. En este contexto se presentan aspectos teóricos y prácticos que merecen atención en la negociación, en el diseño, en la implantación y en la dirección de una meta evaluación cuando se discute, incluso, el paradigma del tratamiento de los datos de una meta evaluación a través de la lógica clásica y no de la lógica fuzzy. También se presenta una propuesta de metodología para realizar meta evaluación con base en la lógica fuzzy.Este artigo trata da categoria precisão de uma verdadeira avaliação no âmbito da avaliação e da meta-avaliação (avaliação da avaliação). Apresenta, inicialmente, a conceituação moderna da avaliação e da meta-avaliação para, então, discutir o papel da meta-avaliação de assegurar à qualidade de um processo avaliativo, nas suas diferentes abordagens, a partir das quatro categorias de uma verdadeira avaliação (utilidade, viabilidade, ética e precisão). A ênfase do artigo está na categoria precisão: (i) a sua importância em uma meta-avaliação, em todas as fases ou etapas de uma avaliação, com seus avanços e suas limitações e; (ii) a sua aplicação na própria meta-avaliação que, enquanto processo avaliativo, também deve respeitar os quatro padrões de uma verdadeira avaliação. Neste contexto são apresentados aspectos teóricos e práticos que merecem atenção na negociação, no desenho, na implantação e na condução de uma meta-avaliação quando se discute, inclusive, o paradigma do tratamento dos dados de uma meta-avaliação através da lógica clássica e não da lógica fuzzy.This article deals with the category precision of a true evaluation in the scope of evaluation and meta-evaluation (evaluation of evaluation). First, it presents the modern conceptualization of evaluation and meta-evaluation and then discusses the role of meta-evaluation to ensure the quality of an evaluation process, in its different approaches, from the four categories of a true evaluation (utility, viability, ethics and precision). The emphasis of the article is on the category precision: (1) its importance in a meta-evaluation, in all the phases or stages of an evaluation, with its advances and its limitations and; (2) its application in the meta-evaluation itself which, while an evaluative process, must also follow the four patterns of a true evaluation. In this sense, practical and theoretical aspects which merit attention in the negotiation, the design, the implementation and the conduction of a meta-evaluation are presented, when the paradigm of the treatment of the data of a meta-evaluation, through the classical logic and not the fuzzy logic, is discussed