NDLI: Intelligent operating conditions design by means of bio-inspired models

Content Provider	IEEE Xplore Digital Library
Author	Villar, J.R. Sedano, J. Corchado, E. Vera, V. Hernando, B. Redondo, R.
Copyright Year	2011
Description	Author affiliation: Dept. of A.I. & Applied Electronics, Castilla y León Technological Institute, (ITCL), Burgos, Spain (Sedano, J.) \|\| Informatics and Automatica Department, University of Salamanca, Spain (Corchado, E.) \|\| Department of Civil Engineering, University of Burgos, Spain (Redondo, R.) \|\| Odontology Faculty, Universidad Complutense of Madrid, Spain (Vera, V.; Hernando, B.) \|\| Computer Science Department, University of Oviedo, Gijón, Spain (Villar, J.R.)
Abstract	This study presents a novel hybrid intelligent system, which focuses on the optimisation of machine parameters for dental milling purposes. The basis of this approach is hybridizing two bio-inspired algorithms, as Neural Networks with Genetic Algorithms for choosing and modelling the feature subset that best descript the operation conditions. These operating conditions are given as parameters for a dental drill machine. The aim of this approach is twofold: a feature selection process is carried out while the modelling of the operating conditions is achieved. The reliability of the proposed novel hybrid system is validated with a real industrial use case, based on the optimisation of a high-precision machining centre with five axes for dental milling purposes.
Starting Page	608
Ending Page	613
File Size	368744
Page Count	6
File Format	PDF
ISBN	9781457711220
e-ISBN	9781457711244
DOI	10.1109/NaBIC.2011.6089731
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-19
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bio-inspired Systems Optimising Operating Conditions Computational modeling Biological system modeling Artificial neural networks Neural Networks Data models Manufacturing Dentistry Genetic Algorithms Genetic algorithms
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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