Application of the Intuitionistic Fuzzy InterCriteria Analysis Method with Triples to a Neural Network Preprocessing Procedure

The approach of InterCriteria Analysis (ICA) was applied for the aim of reducing the set of variables on the input of a neural network, taking into account the fact that their large number increases the number of neurons in the network, thus making them unusable for hardware implementation. Here, fo...

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Bibliographic Details
Published in:Computational Intelligence and Neuroscience 2017-01, Vol.2017 (2017), p.1-9
Main Authors: Tomov, Jivko, Bureva, Veselina, Doukovska, Lyubka, Sotirova, Evdokia, Atanassova, Vassia, Sotirov, Sotir, Mavrov, Deyan
Format: Article
Language:English
Subjects:
Algorithms
Bioinformatics
Data processing
Decision making
Electronic data processing
Fuzzy Logic
Fuzzy sets
Methods
Neural circuitry
Neural networks
Neural Networks (Computer)
Optimization techniques
Preprocessing
Training
Wavelet transforms
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Summary:The approach of InterCriteria Analysis (ICA) was applied for the aim of reducing the set of variables on the input of a neural network, taking into account the fact that their large number increases the number of neurons in the network, thus making them unusable for hardware implementation. Here, for the first time, with the help of the ICA method, correlations between triples of the input parameters for training of the neural networks were obtained. In this case, we use the approach of ICA for data preprocessing, which may yield reduction of the total time for training the neural networks, hence, the time for the network’s processing of data and images.
ISSN:1687-5265
1687-5273
DOI:10.1155/2017/2157852