An Production Forecast Model Based on Accumulative Method
Jiang Shengguo
Cheng Li
Kong Lingshuai
Abstract：The least-squares method in production forecast model study is commonly used in regression parameter estimation.But it is premised on some statistical assumptions with complex calculation,and will be greatly limited especially in the application of short sequence data modeling.In accumulative method,the original data sequence is superposed according to certain rules,and then is used to establish linear model.Its estimator is unbiased,linear,effective and unique,and has the same effect with the least squares method for parameters estimating,but more simple.In this paper,applying this method,the yield production forecasting model of single season rice in Tongcheng,Anhui was built,and the modeling process and error analysis method were described.History back substitution error rate was averaged 3.90％.The reported accuracy was 95.7％ and 97.0％ respectively for 2011 and 2012.Comparatively,the error rate was similar but slightly smaller with the least squares method.The estimation accuracy could be full compliance with operational requirements.After used in operations,the actual prediction accuracy rate was 92.9％,98.5％ respectively in 2013 and 2014.The deficiencies for the accumulated method are that the normal equations coefficient matrix of ill-will would be increased with increasing num ber of independent variables and the sample size,thus affecting the parameter estimation accuracy.
Keywords：accumulative methodleast-squares methodparameter estimationproduction forecasting model
Publication Date：2017-01-01
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：5( 133-137 )