In:
Applied Mechanics and Materials, Trans Tech Publications, Ltd., Vol. 590 ( 2014-6), p. 458-462
Abstract:
In the search for productivity increase, industry has invested on the development of intelligent, flexible and self-adjusting method, capable of controlling processes through the assistance of autonomous systems, independently whether they are hardware or software. Notwithstanding, simulating conventional computational techniques is rather challenging, regarding the complexity and non-linearity of the production systems. Compared to traditional models, the approach with Artificial Neural Networks (ANN) performs well as noise suppression and treatment of non-linear data. Therefore, the challenges in the wood industry justify the use of ANN as a tool for process improvement and, consequently, add value to the final product. Furthermore, Artificial Intelligence techniques such as Neuro-Fuzzy Networks (NFNs) have proven effective, since NFNs combine the ability to learn from previous examples and generalize the acquired information from the ANNs with the capacity of Fuzzy Logic to transform linguistic variables in rules.
Type of Medium:
Online Resource
ISSN:
1662-7482
DOI:
10.4028/www.scientific.net/AMM.590
DOI:
10.4028/www.scientific.net/AMM.590.458
Language:
Unknown
Publisher:
Trans Tech Publications, Ltd.
Publication Date:
2014
detail.hit.zdb_id:
2251882-4
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