A Semantics based Symbolic Regression Framework for Mining Explicit and Implicit Equations from Data
Author:
Affiliation:
1. The University of New South Wales, Canberra ACT, Australia
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2908961.2908989
Reference5 articles.
1. Geometric Semantic Genetic Programming
2. Semantically-based crossover in genetic programming: application to real-valued symbolic regression
3. A multi-objective genetic programming approach to uncover explicit and implicit equations from data
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Sign Change Detection based Fitness Evaluation for Automatic Implicit Equation Discovery;Proceedings of the Genetic and Evolutionary Computation Conference;2024-07-14
2. Improved Genetic Programming for Symbolic Regression: Case Studies on Practical Applications;2022 IEEE Symposium Series on Computational Intelligence (SSCI);2022-12-04
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