Research Article

Modeling and Analysis of Mechanical Properties of Aluminium Alloy (A413) Processed through Squeeze Casting Route Using Artificial Neural Network Model and Statistical Technique

Table 6

Experimental and ANN results of training and testing data.

S. numberExperimental resultsANN resultsPredicted error
UTSYSUTSYSUTSYS

Training set
17225214974.17924255.3464150.7671−3.02672−1.32792−1.18595
27626614778.15725255.9242142.0319−2.838493.7878943.379629
36523613670.89582238.4725135.2735−9.07049−1.047650.534189
47124914671.6759247.9369147.3548−0.951970.426944−0.92793
57826915281.66384271.4753153.9232−4.69723−0.92017−1.26526
67223913571.65555240.363139.24880.478404−0.57029−3.14725
77524814175.12859247.1022141.6824−0.171450.362011−0.48396
88728916785.63843285.8119164.38991.5650271.1031391.562942
97925814278.52493257.8554143.31120.6013490.056062−0.92335
108829316788.26898291.553167.574−0.305660.493862−0.34373
118127415882.02498274.0065155.8774−1.26541−0.002391.343432
128729116189.01555286.0511163.069−2.316721.70066−1.28508
137925814978.54525258.7912148.66460.575627−0.306680.225122
149229917492.93316300.7147172.4506−1.0143−0.573480.89045
159530517694.58353304.0236174.81260.4383890.3201270.674637
169128516690.14581286.8076166.11760.938668−0.63424−0.07087
179229917194.87449304.6269175.3976−3.12444−1.8819−2.57167
188328416284.7705283.1482163.473−2.133140.299932−0.90924

Testing set
196623713572.33027240.346135.6869−9.59132−1.41181−0.50878
206223213160.56261237.9408135.52712.318365−2.56069−3.45579
218428515892.38562296.7993170.5431−9.98288−4.14011−7.93869
228928416689.62359286.8772166.2851−0.70067−1.01309−0.17177
237826515677.80651272.6354158.47030.248062−2.88128−1.58353
249429817193.83024300.7667172.69610.180592−0.92844−0.99188
258728616283.94891282.625163.08933.5070021.180066−0.67239
269430116791.36167291.7642168.40752.8067393.068358−0.84281
278728716984.6408284.7666164.58692.711720.7781742.611294

Correlation coefficient (): for hardness = 0.95, for UTS , and for YS .