Analysis of the evolutionary path of early civilization agriculture based on the plain Bayesian model

Abstract

First, this paper focuses on the problem of nonlinear association between attributes and categories, combines inverse document frequency information and deep attribute weighting, improves the distance correlation coefficient, and proposes an attribute-weighted polynomial plain Bayesian text classification algorithm based on the improved distance correlation coefficient. Then a specific scheme for stage classification of early Chinese civilization provides a theoretical premise and expository framework for systematically exploring the relationship between primitive agricultural types and early Chinese civilization and also provides conditions for forming the agricultural revolution of early Chinese civilization in the Central Plains region. Finally, according to the research objectives, the 7000-year-old Ningzhen area was selected as the research object, and the attribute-weighted polynomial plain Bayesian text classification algorithm was used to analyze the data of the research object. The results show that: in the Neolithic burials of the North Yingying culture period alone, there are 240 burial relics with a total of 1,580 pieces of all burial relics, including 554 pieces of stone production workers, but the fundamental reason is the active change of human for the survival crisis. This study is a preliminary attempt to conduct an interdisciplinary study on the history of agriculture and civilization and provides an academic path for the sublimation of agricultural history to the study of the history of agricultural civilization.

Keywords

• plain bayesian model
• distance correlation coefficient
• attribute weighted polynomial
• early civilization agriculture
• 68t05