Surface roughness prediction using hybrid neural networks
- Author
- JESUTHANAM, C. P1 ; KUMANAN, S1 ; ASOKAN, P1
[1] Department of Production Engineering, National Institute of Technology, Tiruchirappalli, India - Source
Machining science and technology. 2007, Vol 11, Num 2, pp 271-286, 16 p ; ref : 1 p.3/4
- ISSN
- 1091-0344
- Scientific domain
- Mechanics acoustics; Metallurgy, welding; Polymers, paint and wood industries
- Publisher
- Taylor & Francis, Philadelphia, PA
- Publication country
- United States
- Document type
- Article
- Language
- English
- Author keyword
- Genetic algorithm Neural network Particle swarm optimization Surface roughness
- Keyword (fr)
- Algorithme génétique Algorithme évolutionniste Condition opératoire Hybridation Optimisation PSO Optimisation essaim particule Productivité Rugosité Réseau neuronal Surface rugueuse Système information Système production Théorie implicite Usinage
- Keyword (en)
- Genetic algorithm Evolutionary algorithm Operating conditions Hybridization Particle swarm optimization Swarm intelligence Productivity Roughness Neural network Rough surface Information system Production system Implicit theory Machining
- Keyword (es)
- Algoritmo genético Algoritmo evoluciónista Condición operatoria Hibridación Optimización PSO Optimización enjambre partícula Productividad Rugosidad Red neuronal Superficie rugosa Sistema información Sistema producción Teoría implícita Mecanizado
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D12 Mechanical engineering. Machine design / 001D12A General
- Discipline
- Mechanical engineering. Mechanical construction. Handling
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 18906563
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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DOI
10.1080/10910340701340141 
https://dx.doi.org/10.1080/10910340701340141
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