The mathematical derivation of the model and its physical explanation are the main points of the study. Thirdly, the concept of periphery gate is embedded into the self-retrospect equation, the self-retrospect gate model has been proposed, and the physical implication of the model is mentioned. It has been applied in many fields since the periphery theory was put forward, such as physics, meteorology, water resources, economy, as well as sports. It is a part of the system and is adjacent to the environment. Secondly, the periphery is defined as an intermediary that can protect the system and exchange with the environment. The principle of system self-retrospect has been applied to modeling, calculating, and forecasting in many fields such as meteorology, oceanography, hydrology, market, agriculture, transportation, energy, and so on. The principle of constructing and solving the difference-integral equation of the system is referred to as the principle of self-retrospect dynamic systems, and the corresponding mathematical model is called the self-retrospect model. Firstly, for the equation with a time difference term that controls the motion of the system, a difference-integral equation can be derived by introducing a retrospect function and applying the inner product, partial integral, and mean value theorem. Thus, a self-retrospect periphery gate model, a new expression of temporal-spatial concept, has been derived to investigate the change of a system and forecast it in physics. We try to integrate the principle of the self-retrospect system and periphery theory in this study. Afterward, the periphery theory was established, which studies the boundary of a system. 3China Meteorological Administration Training Centre, Beijing, Chinaīy not only relying on the initial state but also relying on states before, the principle of a self-retrospect dynamic system has been developed to represent the changes in a system since 1991.2China Meteorological Administration (CMA), Public Meteorological Service Center, Beijing, China.
1Chinese Academy of Meteorological Sciences, Beijing, China.Xiuhua Cai 1, Hongxing Cao 1, Xiaoyi Fang 1 *, Jingli Sun 2, Chen Cheng 1, Wenjie Fan 3 and Ying Yu 1
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