Determination of Hardness of Pre-Aged AA 6063 Aluminum Alloy by Means of Artificial Neural Networks Method

Mathematical and Computational Applications
doi 10.3390/mca9020249
Full Text
Abstract

Available in full text

Date
Authors
Publisher

MDPI AG

Related search

Effect of Artificial Aging on Hardness and Intergranular Corrosion of 6063 Al Alloy

Pamukkale University Journal of Engineering Sciences
2017English

Interpretation of Artificial Neural Networks by Means of Fuzzy Rules

IEEE Transactions on Neural Networks
2002English

Preparation of Trivalent Chromium Coating on 6063 Aluminum Alloy

DEStech Transactions on Materials Science and Engineering
2017English

Determination of Relationship Between Hardness and Groundwater Quality Parameters by Neural Networks

Desalination and Water Treatment
Ocean EngineeringTechnologyWater SciencePollution
2009English

Study of Fatigue Crack Growth in 6063-T6 Aluminum Alloy

Independent Journal of Management & Production
2015English

Prediction of Jominy Hardness Profiles of Steels Using Artificial Neural Networks

Journal of Materials Engineering and Performance
Mechanics of MaterialsMaterials ScienceMechanical Engineering
1996English

Foaming Process and Properties of 6063 Aluminum Foams by Melt Foaming Method

Materials Transactions
Mechanics of MaterialsMaterials ScienceCondensed Matter PhysicsMechanical Engineering
2017English

Prediction of the Consistency of Concrete by Means of the Use of Artificial Neural Networks

2006English

Elimination of Iron Interference in the Molecular Spectrophotometric Determination of Aluminum in Soil Extracts Using Artificial Neural Networks

Analytical Sciences
Analytical Chemistry
2008English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy