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Shape-constrained multi-objective genetic programming for symbolic regression

  • Published:2023-01 Issue: Volume:132 Page:109855
  • ISSN:1568-4946
  • Container-title:Applied Soft Computing
  • language:en
  • Short-container-title:Applied Soft Computing

Author:

Haider C.ORCID,de Franca F.O.,Burlacu B.,Kronberger G.

Funder

Christian Doppler Forschungsgesellschaft

Bundesministerium für Digitalisierung und Wirtschaftsstandort

Fundação de Amparo à Pesquisa do Estado de São Paulo

Publisher

Elsevier BV

Subject

Software

Reference43 articles.

1. Workshop report on basic research needs for scientific machine learning: Core technologies for artificial intelligence;Baker,2019

2. Shape-constrained symbolic regression – improving extrapolation with prior knowledge;Kronberger;Evol. Comput.,2021

3. Isotonic, convex and related splines;Wright;Ann. Statist.,1980

4. Monotonic calibrated interpolated look-up tables;Gupta;J. Mach. Learn. Res.,2016

5. Interval arithmetic: from principles to implementation;Hickey;J. ACM,2001

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