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A Model for Knowledge Management in Software Industry Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Impact of Weight Initialization on Multilayer Perceptron Using Fuzzy Similarity Quality Measure

Authors : Lenniet Coello, Yumilka Fernández, Yaima Filiberto, Rafael Bello

Published in: Applied Computer Sciences in Engineering

Publisher: Springer International Publishing

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Abstract

This paper presents an algorithm for initializing the weights in multilayer perceptrons based on the new metrics called Fuzzy Similarity Quality. The new metric used a binary fuzzy relation for quantify the strength of the similarity between two objects. This measure computes the grade of similarity in a decision system in which the features can have discrete or continuous values. Experimental results show that the proposed initialization method performs better than other previously reported methods to calculate the weight of features.

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previous chapter Improving the Performance of Leaves Identification by Features Selection with Genetic Algorithms
next chapter A Genetic Optimized Cascade Multilevel Converter for Power Analysis
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Metadata
Title
Impact of Weight Initialization on Multilayer Perceptron Using Fuzzy Similarity Quality Measure
Authors
Lenniet Coello
Yumilka Fernández
Yaima Filiberto
Rafael Bello
Copyright Year
2016
Book
Applied Computer Sciences in Engineering

Print ISBN: 978-3-319-50879-5

Electronic ISBN: 978-3-319-50880-1

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-50880-1_11

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