- author = "Sergio Contador and J. Manuel Colmenar and Oscar Garnica and J. Ignacio Hidalgo",
- title = "Short and Medium Term Blood Glucose Prediction Using Multi-objective Grammatical Evolution",
- booktitle = "23rd International Conference, EvoApplications 2020",
- year = "2020",
- month = "15-17 " # apr,
- editor = "Pedro A. Castillo and Juan Luis {Jimenez Laredo} and Francisco {Fernandez de Vega}",
- series = "LNCS",
- volume = "12104",
- publisher = "Springer Verlag",
- address = "Seville, Spain",
- pages = "494--509",
- organisation = "EvoStar, Species",
- keywords = "genetic algorithms, genetic programming, Grammatical Evolution, Multi-objective optimization, medicine, Human Glucose blood concentration prediction, Diabetes",
- isbn13 = "978-3-030-43721-3",
-
video_url = "
https://www.youtube.com/watch?v=OyNQC5Drbx4",
-
DOI = "
doi:10.1007/978-3-030-43722-0_32",
- abstract = "we investigate the benefits of applying a multi-objective approach for solving a symbolic regression problem by means of grammatical evolution. In particular, we continue with previous research about finding expressions to model the glucose levels in blood of diabetic patients. We use here a multi-objective Grammatical Evolution approach based on NSGA-II algorithm, considering the root mean squared error and an ad-hoc fitness function as objectives. This ad-hoc function is based on the Clarke Error Grid analysis, which is useful for showing the potential danger of mispredictions. Experimental results show that the multi-objective approach improves previous results in terms of Clarke Error Grid analysis reducing the number of dangerous mispredictions.",
-
notes = "Universidad Complutense de Madrid,
Spain
http://www.evostar.org/2020/ EvoApplications2020 held in conjunction with EuroGP'2020, EvoMusArt2020 and EvoCOP2020",
