Research on the Distance-based Outlier Mining Algorithm to Identify the Outpatient Visits of Teachers and Students During Holidays

  • Tieshi Song, Huipeng Jin, Jiutao Zhang, Qi Zeng

Abstract

Background and Purpose: The health of teachers and students is particularly important to the development of the school. Forecasting of outpatient visits are benefit for hospital work efficiency. Research Methods: For forecasting of daily outpatient visits of teachers and students, distance-based outlier mining algorithm is proposed. In this approach, an algorithm for mining outliers based on distance is presented to compute holiday effect’s effective time. Solar term, as minimal time units of climate change, combining with other attributes, is used to describe the outpatient visits data of teachers and students.

How to Cite
Tieshi Song, Huipeng Jin, Jiutao Zhang, Qi Zeng. (1). Research on the Distance-based Outlier Mining Algorithm to Identify the Outpatient Visits of Teachers and Students During Holidays. Forest Chemicals Review, 59-70. Retrieved from http://forestchemicalsreview.com/index.php/JFCR/article/view/895
Section
Articles