How does the gray phytophthora system predict models?

At present, more than 200 international and domestic journals publish gray system papers, and many international conferences list gray system as a discussion topic. The application of gray system theory has been expanded to many scientific fields such as industry, agriculture, society, economy, energy, geology, petroleum, etc. It has successfully solved a large number of practical problems in production, life and scientific research, and achieved remarkable results, and has also been applied within the discipline of plant pathology.

The characteristics of the gray prediction method performance: first of all, it is the discrete data as a continuous variable in the process of its change in the discrete value, so that the use of differential equations can be used to deal with the data; and do not directly use the original data but by it to produce cumulative generating number, on the generating series of the use of differential equation model. In this way, most of the random errors can be canceled out and regularity can be shown.

The study of a system, generally should first establish a mathematical model of the system, and then the overall function of the system, the coordination function and the correlation between the various factors of the system, cause and effect relationship, dynamic relationship to carry out specific quantitative research. This kind of research must be preceded by qualitative analysis, and quantitative and qualitative are closely integrated. The establishment of the system model, generally go through the idea development, factor analysis, quantification, dynamization, optimization of five steps, so it is called five-step modeling.

The first step: developing ideas, forming concepts. Through qualitative analysis, research, clear research direction, goals, ways, measures, and the results are expressed in accurate and concise language, which is the language model.

Step 2: Analyze the factors in the language model and the relationship between the factors to find out the antecedents and consequences that affect the development of things. A pair of antecedents and consequences (or a set of antecedents and a consequence) constitutes a link. A system contains many such links. Sometimes, the same quantity is both the antecedent of one link and the consequence of another link, connecting all these relationships, we get an interrelated, composed of multiple links, that is, the network model.

The third step: quantitative study of the causal relationships of the links, the initial low-level approximate quantitative relationships, that is, quantitative model.

Step 4: Further collect input data and output data from each link, and utilize the resulting data series to build a dynamic GM model, i.e., a dynamic model. The dynamic model is a high-level quantitative model, which reveals more profoundly the quantitative relationship or conversion law between input and output, and is the basis for system analysis and optimization.

Step 5: Systematic research and analysis of the dynamic model. Through the structure, mechanism, parameters of the adjustment, system reorganization, to achieve the purpose of optimizing the configuration, improve the dynamic quality of the system. The model thus obtained is called the optimization model.

The whole process of five-step modeling is the process of establishing five kinds of models in five different stages: language model; network model; quantitative model; dynamic model; optimization model. In the modeling process, the results obtained in the next stage should be continuously fed back, after many cycles, so that the whole model gradually tends to be perfect.

The emergence and development of gray system theory, the basic concepts of gray system, gray system and fuzzy mathematics, the difference between the black box approach, gray system prediction GM (1, 1) model, GM (1, N) model, gray system model test, application examples.