- author = "Sean Stijven and Ekaterina Vladislavleva and Arthur Kordon and Mark Kotanchek",
- title = "Prime-Time: Symbolic Regression Takes its Place in Industrial Analysis",
- booktitle = "Genetic Programming Theory and Practice XIII",
- year = "2015",
- editor = "Rick Riolo and William P. Worzel and M. Kotanchek and A. Kordon",
- series = "Genetic and Evolutionary Computation",
- pages = "241--260",
- address = "Ann Arbor, USA",
- month = "14-16 " # may,
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming, Symbolic regression, Forecasting, DataModeler, Extrapolation, Prediction, Simulation-based optimization",
- isbn13 = "978-3-319-34223-8",
-
URL = "
http://www.springer.com/us/book/9783319342214",
-
DOI = "
doi:10.1007/978-3-319-34223-8_14",
- abstract = "we review a number of real-world applications where symbolic regression was used recently and with great success. Industrial scale symbolic regression armed with the power to select right variables and variable combinations, build robust trustable predictions and guide experimentation has undoubtedly earned its place in industrial process optimization, business forecasting, product design and now complex systems modelling and policy making.",
-
notes = "
Part of \cite{Riolo:2015:GPTP} Published after the workshop in 2016",
