Support vector regression-based heteroscedastic models for cryptocurrency risk forecasting

Autor: Muchtadi-Alamsyah, Intan, Viltoriano, Robin, Harjono, Ferdinand, Nazaretha, Martha, Susilo, Martin, Bayu, Ade, Josaphat, Bony, Hakim, Arief, Syuhada, Khreshna

Publikováno v: In Applied Soft Computing September 2024 162

Development of analytical "aroma wheels" for Oolong tea infusions (Shuixian and Rougui) and prediction of dynamic aroma release and colour changes during "Chinese tea ceremony" with machine learning.

Autor: Yang N; International Flavour Research Centre, Division of Food, Nutrition and Dietetics, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, United Kingdom.. Electronic address: ni.yang@nottingham.ac.uk., Simon J; International Flavour Research Centre, Division of Food, Nutrition and Dietetics, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, United Kingdom.; Graduate School of Materials, Food and Chemistry - ENSMAC in Bordeaux, France., Fang W; College of Horticulture, Nanjing Agricultural University, China., Ayed C; International Flavour Research Centre, Division of Food, Nutrition and Dietetics, University of Nottingham, Sutton Bonington Campus, Loughborough LE12 5RD, United Kingdom., Zhang WE; School of Computer and Mathematical Sciences, University of Adelaide, Adelaide, Australia., Axell M; School of Computer and Mathematical Sciences, University of Adelaide, Adelaide, Australia., Viltoriano R; School of Computer and Mathematical Sciences, University of Adelaide, Adelaide, Australia., Fisk I; School of Computer and Mathematical Sciences, University of Adelaide, Adelaide, Australia; International Flavour Research Centre (Adelaide), School of Agriculture, Food and Wine and Waite Research Institute, University of Adelaide, Adelaide, Australia.

Publikováno v: Food chemistry [Food Chem] 2024 Oct 04; Vol. 464 (Pt 1), pp. 141537. Date of Electronic Publication: 2024 Oct 04.