Techniques of Forecasting University Enrollment

Schmid, Calvin F.; Shanley, Fred J.

doi:10.2307/1976933

Cited by 5 publications

(1 citation statement)

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“…Supply is mainly the conditions for running a school, especially the scale of teachers, the living standards of residents, etc. Among them, some of the factors both have the demand and supply factors, such as population, economic development, living standards of residents and so on [4][5][6]. As everyone knows, GDP is the most important indicator of a country's economic development.…”

Section: Introductionmentioning

confidence: 99%

Application of the Cosine Gray Model Based on System Cloud in the Forecast of Higher Education Scale

Ge¹,

Li²

2015

Int. J. Emerg. Technol. Learn.

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Abstract-The scale of higher education is an essential link in the process of the formulation of education planning and reasonable allocation of teaching resources. At the same time, it also provides the required basis and support for the government to formulate educational planning and policy. The scale of higher education development is influenced not only by the level of economic development and industrial structure, but also by the total population and the living standards of residents. We take these elements as the influence factors, which contain noise information. Because the scale of higher education and its impact factors have complex nonlinear relationship, the traditional forecasting method cannot describe their changing trends, which leads to the low accuracy of prediction. In order to solve the above problems, this paper bases on the traditional GM (1,1) model to judge the number of students in the future, and uses the weakening buffer operator to amend the historical data. Secondly, this paper analyzes the structure of the system cloud gray forecasting model, and demonstrates its integral generation principle. We propose a new method for the cosine gray forecasting model which is based on the system cloud�SCOS-GM (1, 1), and prove the effectiveness of SCOS-GM (1, 1) model by the residual test. Finally, the SCOS-GM (1, 1) model is utilized to predict the scale of higher education in China during the period of 2012-2014. The results show that the scale of higher education will demonstrate a gradual upward trend in the next few years.

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Section: Introductionmentioning

confidence: 99%