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An Artificial Neural Network Approach to Predict the Properties of AlSi12 Alloy

Authors: K. Srinivasulu Reddy; G. Ranga Janardhana; K. Krishna Mohan Reddy;

An Artificial Neural Network Approach to Predict the Properties of AlSi12 Alloy

Abstract

The effects of modification and vibration during solidification of Aluminum-Silicon eutectic alloy (AlSi12) are studied and compared with unmodified alloy. Sodium and Strontium are used as modifiers. Horizontal sinusoidal vibration at different frequencies was imposed using a vibration table. It was found that modification treatment improves properties such as ultimate tensile strength (UTS), percentage elongation, hardness, toughness, cutting force, electrical conductivity, thermal conductivity, fluidity, porosity and fatigue strength and optimum values were found for sodium and strontium weight addition of modifier. Self organized feature map (SOFM) network model is developed using Neuro Solutions package. Genetic algorithm is used to optimize the model developed. Further, neuro fuzzy model (CANFIS) is developed and compared the results with neural network model developed. Sensitivity analysis is carried out to measure the relative importance of the inputs of the model and how the model output varies in response to variation of an input. The developed models were validated experimentally.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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