Аннотация

Since the mid-1990's, symbolic regression via genetic programming (GP) has become a core component of a multi-disciplinary approach to empirical modeling at Dow Chemical. Herein we review the role of symbolic regression within an integrated empirical modeling methodology, discuss symbolic regression system design issues, best practices and lessons learned from industrial application, and present future directions for research and application

Линки и ресурсы

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