Application of Artificial Neural Network Based on GA-BP Algorithm to Predicting Mechanical Properties of TC4

Zhe Zhe Hou; Yan Liang Du

doi:10.4028/www.scientific.net/AMR.146-147.1698

Paper Titles

Preparation and Modification of Nano- TiO₂ Pigment for Coating
p.1675

Comparative Study on Data Editing Techniques for Fatigue Time Series Signals
p.1681

Analyzing Si Precipitation on Age Hardening of an Al-Si-Mg Cast Alloy
p.1685

Influences of Slag and Fly Ash on the Microstructure Property and Compressive Strength of Concrete
p.1690

Application of Artificial Neural Network Based on GA-BP Algorithm to Predicting Mechanical Properties of TC4
p.1698

Microstructure and Creep Property of As-Cast Mg-6Al-xNd (x=2,4,6) Alloys
p.1702

Effective Service Life Assessment of Aluminum Alloy Alclad Corrosion Protection under Equivalent Accelerated Condition
p.1708

Kinetics of Mg₂Sn Synthesis Reaction under Isothermal Condition
p.1712

Study of TiAl Alloy Surface Plasma Modified Corrosion Resistance
p.1717

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 146-147Application of Artificial Neural Network Based on...

Application of Artificial Neural Network Based on GA-BP Algorithm to Predicting Mechanical Properties of TC4

Abstract:

On the basis of numerous experimental results the effect of heat treatment on mechanical properties of TC4 alloy is studied. A computer model expressing the relationships between heat treatment and mechanical properties has been established with a back propagation feed forword artificial neural network method. The optimization methods based on artificial neural network and the genetic algorithm, using binary system, optimize the weight and threshold by the genetic algorithm. The calculation results show that the model has good learning precision and generalization and it can be used for predicting the mechanical properties of TC4 alloy.