Optimization of process conditions in casting aluminum matrix composites via interconnection of artificial neurons and progressive solutions
Source abstract
Abstract
Abstract A genetic algorithm is a machine learning technique that was inspired by the analogy of biological evolution which generates solutions by repeatedly mutating and recombining parts of the best currently known solutions. In order to model and optimize the properties of A356 matrix composites, a finite element method (FEM) with artificial neural network based genetic algorithm (ANN-GA) model was developed. The tribological and mechanical properties of the aluminum matrix composite were also experimentally investigated. The results verified the accuracy of the proposed model to find the optimal process conditions in aluminum matrix composite materials.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Aluminum Alloys Composites Properties · Aluminum Alloy Microstructure Properties · Advanced Machining and Optimization Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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