Implicit Equation Discovery

Abstract: Implicit equation is loose in form, which makes it more powerful than explicit equation for data regression. The mainstream method for  automatic implicit equation discovery is based on calculating derivatives.  However, this derivative-based mechanism requires high time consumption  and it is difficult to solve problems with sparse data. In this project, we aim to propose effective and efficient approaches to solve the  above deciencies.

Figure 1 Example curves of implicit equations.

Related paper:

  1. Y. Chen, J. Zhong*, M. Tan, “Comprehensive Learning Gene Expression Programming for Automatic Implicit Equation Discovery, ” International Conference on Computational Science (ICCS). Springer, Cham, 2018: 114-128. [Link]
  2. J. Zhong, J. Yang, Y. Chen, W. -L. Liu and L. Feng, “Mining Implicit Equations from Data using Gene Expression Programming,”  IEEE Transactions on Emerging Topics in Computing, 2021, doi: 10.1109/TETC.2021.3068651.
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