Juan Luis Castro, José Jesús Castro-Sánchez, Antonio Espin, José Manuel Zurita (1998)
Mathware and Soft Computing
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This paper presents a methodology for developing fuzzy knowledge based systems (KBS), which permits a complete automatization. This methodology will be useful for approaching more complex problems that those in which machine learning from examples are successful.
José Manuel Benítez, Armando Blanco, Miguel Delgado, Ignacio Requena (1996)
Mathware and Soft Computing
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In previous papers, we presented an empirical methodology based on Neural Networks for obtaining fuzzy rules which allow a system to be described, using a set of examples with the corresponding inputs and outputs. Now that the previous results have been completed, we present another procedure for obtaining fuzzy rules, also based on Neural Networks with Backpropagation, with no need to establish beforehand the labels or values of the variables that govern the system.
D. Vlachos, Y. A. Tolias (2003)
The Yugoslav Journal of Operations Research
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José Manuel Benítez, Armando Blanco, Miguel Delgado, Ignacio Requena (1998)
Mathware and Soft Computing
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In previous works, we have presented two methodologies to obtain fuzzy rules in order to describe the behaviour of a system. We have used Artificial Neural Netorks (ANN) with the Backpropagation algorithm, and a set of examples of the system. In this work, some modifications which allow to improve the results, by means of an adaptation or refinement of the variable labels in each rule, or the extraction of local rules using distributed ANN, are showed. An interesting application on the...
Chunshien Li, Tai-Wei Chiang (2012)
International Journal of Applied Mathematics and Computer Science
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Financial investors often face an urgent need to predict the future. Accurate forecasting may allow investors to be aware of changes in financial markets in the future, so that they can reduce the risk of investment. In this paper, we present an intelligent computing paradigm, called the Complex Neuro-Fuzzy System (CNFS), applied to the problem of financial time series forecasting. The CNFS is an adaptive system, which is designed using Complex Fuzzy Sets (CFSs) whose membership functions...
Jesús A. Domínguez, Steven J. Klinko (2003)
Mathware and Soft Computing
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A visual system prototype that detects anomalies or defects in real time under normal lighting operating conditions was built for NASA at the Kennedy Space Center (KSC). The system prototype is basically a learning machine that integrates the three elements of soft computing, Fuzzy Logic (FL), Artificial Neural Network (ANN), and Genetic Algorithm (GA) schemes to process the image, run the learning process, and finally detect the anomalies or defects. The system acquires the image, performs...
Stephen G. Matthews, Mario A. Gongora, Adrian A. Hopgood (2013)
International Journal of Applied Mathematics and Computer Science
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A novel method is presented for mining fuzzy association rules that have a temporal pattern. Our proposed method contributes towards discovering temporal patterns that could otherwise be lost from defining the membership functions before the mining process. The novelty of this research lies in exploring the composition of fuzzy and temporal association rules, and using a multi-objective evolutionary algorithm combined with iterative rule learning to mine many rules. Temporal patterns...
Piotr Czekalski (2006)
International Journal of Applied Mathematics and Computer Science
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While using automated learning methods, the lack of accuracy and poor knowledge generalization are both typical problems for a rule-based system obtained on a given data set. This paper introduces a new method capable of generating an accurate rule-based fuzzy inference system with parameterized consequences using an automated, off-line learning process based on multi-phase evolutionary computing and a training data covering algorithm. The presented method consists of the following steps:...
R. Marín, S. Barro, F. Palacios, R. Ruiz, F. Martín (1994)
Mathware and Soft Computing
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In this work we propose an approach for the application of a fuzzy temporal constraint model to intelligent patient monitoring tasks. After analyzing the requirements of the domain, we describe the approach that was followed in order to represent temporal information and solve queries on temporal relations. These processes require the cooperation of a temporal specialist with the domain reasoning mechanisms. The integration solution presented here corresponds to a stage of the implementation...
Julio García, José Manuel Molina, Juan Alberto Besada, Javier I. Portillo (2003)
Mathware and Soft Computing
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A fuzzy system has been developed to ponder update decisions both for the trajectories and shapes estimated for targets. It is embedded in an A-SMGCS Surveillance function for airport surface, based on video data processing, in charge of the automatic detection, identification and tracking of all interesting targets (aircraft and relevant ground vehicles). The tracking system captures a sequence of images, preprocesses them to extract the moving regions (blobs), and associates the blobs...