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From: Symbolic regression accelerates the discovery of quantitative relationships in rubber material aging
Figure 1. The overall workflow of discovering the aging quantitative relationships of polymer materials through SR. (A) Diverse candidate SR algorithms, such as those based on reinforcement learning, genetic algorithms and transformer architecture; (B) Evaluation framework based on SR4Real dataset considering formulas with six characteristics: Base, Ops, Domain, Num, Noise and Dummy; (C) Aging material samples from aging experiments; (D) Aging sample characterization data from characterization experiments. (The schematic diagrams are generated by GPT4o); (E) The discovery of the internal relationships in the aging characterization data based on the selected SR method. SR: Symbolic regression.
