Biomass population dynamics predictive parsing worldwide general key factor presupposing array platform
A dynamic forecasting technology that is universally used globally. It is applied in the fields of electrical digital data processing, design optimization/simulation, and special data processing applications. It can solve problems such as poor timeliness of models, outliers in predicted values, and insufficient environmental information to reduce risks. performance, and the effect of improving accuracy
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Embodiment 1
[0045] It is used to construct the quantitative dynamic model of various natural life groups in the world in any period of time for many years:
[0046] The UKF-PAP data set in UKF-PAP is a global common key factor group with year as the time period, so it can be used to construct a variety of measurable natural life groups (such as population birth rate, population death rate) in any region of the world , the prevalence of certain human diseases, the prevalence of crop diseases, insect pests and rodents, the dynamic forecast of global crop production, the annual occurrence dynamics of some small wild animals with multiple generations in a year, the annual growth rate of some perennial wild plants, etc.) A numerical model of the dynamics of the quantity in any period of time for many years. The so-called "any period of time in many years" means that any year can be subdivided into the whole year, quarter, month, ten days, day, etc., or any time period within the year that is c...
Embodiment 2
[0048] Key Controlled Factors and Accompanying Factors for Screening Specific Living Objects:
[0049] After statistical analysis of hundreds of cases in different countries, different regions, different species of life, different historical years and different quantitative indicators, the results show that in the UKF-PAP, although the alternative UKF-PAP factors may reach dozens of There are as many as 10,000 items, but for each specific natural life body, the key controlled factors or accompanying factors reaching a statistically significant level of p≤0.05 do not exceed 10 at most, generally 2-6, but different life organisms, or the same species of life has different controlled factors or accompanying factors in different regions or different time periods. The discovery of this rule provides users with the ability to use UKF-PAP to analyze and screen the specific controlled factors or accompanying factors of each organism, or the key factors controlled by different organism...
Embodiment 3
[0051] Analyze the common dominant factors that affect the main life forms closely related to human beings in the world or in a certain place:
[0052] All the mathematical models built with UKF-PAP have all visible and well-known simple multiple linear regression models in form. The names of PAP variables correspond to each other, so the name of each independent variable represents a key influencing factor or its combination. At the same time, in the regression coefficient list of the regression analysis results, there will be another column showing its standardized regression coefficient, and each factor selected in the regression model will have a corresponding standardized regression coefficient. The size of this standard regression coefficient is Indicates the influence of each selected factor, and the user can obtain the percentage of the relative effect of each factor only through simple mathematical operations. If the user has modeled a variety of life forms, he only ...
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