With the change of life style, more and more people are eating out, and the dietary content is high in calories, fat and sugar, resulting in the increasing number of obesity in children, adolescents and adults, and the prevalence of chronic diseases continues to grow. Therefore, preventive health care has become the focus of health policy in the 21st century. The pursuit of health must start from the daily diet. This paper proposes an intelligent recipe recommendation model based on integer planning, which customize personalized balanced diet according to the limitations of food type and meal cost and other restrictions.
The Heston–Hull–White three-dimensional time-dependent partial differential equation (PDE) is one of the important models in mathematical finance, at which not only the volatility is modeled based on a stochastic process but also the rate of interest is assumed to follow a stochastic dynamic. Hence, an efficient method is derived in this paper based on the methodology of the localized radial basis function generated finite difference (RBF-FD) scheme. The proposed solver uses the RBF-FD approximations on graded meshes along all three spatial variables and a high order time-stepping scheme. Stability is also studied in detail to show under what conditions the proposed method is stable. Computational simulations are given to support the theoretical discussions.
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