Evaluation and Analysis of Research Project Funding Calculation Method Based on Random Forest Algorithm
By analyzing the funding data of more than one thousand projects,we explored the characteristic factors of research span and the value of scientific research and development,constructing a sample set of scientific projects.Using entity embedding to vectorize discrete variables,we then applied random forest methods,iteratively calculating to determine the correlation between the value of scientific research and development and the amount of funding for research projects.This led to the formation of a method for allocating research project funds that reflects the value of scientific research and development.The study results indicate that the random forest approach has significant advantages in predicting the correlation between the value of scientific research and development and the amount of funding for research projects.By constructing multiple decision trees,the risk of overfitting in a single model is reduced,improving the accuracy and stability of the predictions.Additionally,assessing the importance of various characteristic variables effectively identifies factors that have a substantial impact on the prediction of research funding,thus providing a scientific basis for the allocation of research funds.
random forestentity embeddingscientific research fundingprediction
NETL
NSTL
万方数据
