Studies on Developing a Neuro Fuzzy Model to Predict the Properties of AlSi12 Alloy

The results of alteration and vibration are investigated and compared with unmodified alloy during solidification of Aluminum-Silicon eutectic alloy (AlSi12). As modifiers, Sodium and Strontium are used. Using a vibration table, horizontal sinusoidal vibration was imposed at various frequencies. Modification treatment has been found to enhance characteristics such as ultimate tensile strength (UTS), percentage elongation, stiffness, durability, cutting power, electrical conductivity, thermal conductivity, fluidity, porosity and fatigue strength, and optimum values have been found for modifier sodium and strontium weight addition. The network model of a self-organized feature map (SOFM) is created The kit uses Neuro Solutions. To optimise the model generated, genetic algorithms are used. In addition, the neuro fuzzy model (CANFIS) was developed and the results were compared with the developed neural network model. Sensitivity analysis is carried out to measure the relative value of the model’s inputs and how the output of the model differs in response to an input variance. The models developed were experimentally tested.

Author (s) Details

Dr. K. Srinivasulu Reddy
Mechanical Engineering Department, Sreenidhi Institute of Science and Technology, Hyderabad, Telangana-501 301, India.

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