scholarly journals Semi-Automatic Semantic Data Classification Expert System to Produce Thematic Maps

10.5772/51848 ◽  
2012 ◽  
Author(s):  
Luciene Stamato ◽  
Andre Luiz Alencar de Mendonca ◽  
Joao Vitor Meza Bravo ◽  
Monica Cristina de Castro ◽  
Pamela Andressa ◽  
...  
Keyword(s):  
Expert System ◽  
Data Classification ◽  
Thematic Maps ◽  
Semantic Data

Design of fuzzy expert system for microarray data classification using a novel Genetic Swarm Algorithm

2012 ◽  
Vol 39 (2) ◽  
pp. 1811-1821 ◽  
Author(s):  
P. Ganesh Kumar ◽  
T. Aruldoss Albert Victoire ◽  
P. Renukadevi ◽  
D. Devaraj
Keyword(s):  
Expert System ◽  
Microarray Data ◽  
Data Classification ◽  
Fuzzy Expert System ◽  
Swarm Algorithm

scholarly journals SIGNAL CHECKING OF STEGANO INSERTED ON IMAGE DATA CLASSIFICATION BY NFES-MODEL

CCIT Journal ◽  
2012 ◽  
Vol 5 (3) ◽  
pp. 312-328
Author(s):  
M. Givi Efgivia ◽  
Safaruddin A. Prasad ◽  
Al-Bahra .LB
Keyword(s):  
Neural Network ◽  
Expert System ◽  
Image Data ◽  
Data Classification ◽  
Fuzzy Expert System ◽  
Classification Result ◽  
Transform Method ◽  
Secret Information ◽  
Neuro Fuzzy ◽  
Image Data Classification

Abstract. In this paper, we propose an identification method of the land cover from remote sensing data with combining neuro-fuzzy and expert system. This combining then is called by Neuro-Fuzzy Expert System Model (NFES-Model). A Neural network (NN) is a part from neuro-fuzzy has the ability to recognize complex patterns, and classifies them into many desired classes. However, the neural network might produce misclassification. By adding fuzzy expert system into NN using geographic knowledge based, then misclassification can be decreased, with the result that improvement of classification result, compared with a neural network approximation. An image data classification result may be obtained the secret information with the inserted by steganography method and other encryption. For the known of secret information, we use a fast fourier transform method to detection of existence of that information by signal analyzing technique.

scholarly journals An Expert System for EMI Data Classification based on Complex Bispectrum Representation and Deep Learning Methods

2021 ◽  
pp. 114568
Author(s):  
Imene Mitiche ◽  
Mark D. Jenkins ◽  
Philip Boreham ◽  
Alan Nesbitt ◽  
Gordon Morison
Keyword(s):  
Deep Learning ◽  
Expert System ◽  
Data Classification ◽  
Learning Methods

scholarly journals Integrating DROOLS and R software for intelligent map system

2011 ◽  
Vol 7 ◽  
pp. 85-92
Author(s):  
Jan Růžička
Keyword(s):  
Expert System ◽  
Statistical Tests ◽  
Data Classification ◽  
R Software ◽  
Statistical Software ◽  
Selection Of

The paper describes intelligent map system that allows to check errors in map sheets or to help with a map sheet creation. The system is based on expert system DROOLS, ontology created in Protége and statistical software R. Prototype of the system should evaluate that this kind of integration is possible, so the system is not full of rules. The prototype is filled with twenty rules written in DRL language and with more than thirty items from the ontology. The paper should show how all of these components can be integrated together to allow such kind of a map sheet evaluation. The system is now used for selection of the best method for data classification. The selection is suggested by DROOLS system that uses R software to perform statistical tests of normality and uniformity.

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