国土资源科技管理
國土資源科技管理
국토자원과기관리
Scientific and Technological Management of Land and Resources
2015年
5期
109-114
,共6页
日客流量预测%分类模型%SVR%黄山风景区
日客流量預測%分類模型%SVR%黃山風景區
일객류량예측%분류모형%SVR%황산풍경구
daily visitor numbers forecasting%classification model%SVR%Huangshan scenic area
日客流量的准确预测能为景区管理决策提供科学可靠的依据.由于受到各种客观因素影响 ,日客流量不光呈现出强非线性特征 ,而且具有明显的季节性特征.整年度的日客流量数据跳跃波动过大 ,整年度模型很难对其进行准确预测.针对这一问题 ,根据黄山风景区日客流量的分布特点 ,建立了1、2和12月 ,3、6和11月 , 4和5月 ,7和8月 ,9和10月以及法定节假日六类预测模型 ,通过S V R预测方法的实证仿真显示 ,同年度模型相比基于客流量分布特征的分类模型明显消除了日客流量跳跃波动 ,有效地提高了预测精度.
日客流量的準確預測能為景區管理決策提供科學可靠的依據.由于受到各種客觀因素影響 ,日客流量不光呈現齣彊非線性特徵 ,而且具有明顯的季節性特徵.整年度的日客流量數據跳躍波動過大 ,整年度模型很難對其進行準確預測.針對這一問題 ,根據黃山風景區日客流量的分佈特點 ,建立瞭1、2和12月 ,3、6和11月 , 4和5月 ,7和8月 ,9和10月以及法定節假日六類預測模型 ,通過S V R預測方法的實證倣真顯示 ,同年度模型相比基于客流量分佈特徵的分類模型明顯消除瞭日客流量跳躍波動 ,有效地提高瞭預測精度.
일객류량적준학예측능위경구관리결책제공과학가고적의거.유우수도각충객관인소영향 ,일객류량불광정현출강비선성특정 ,이차구유명현적계절성특정.정년도적일객류량수거도약파동과대 ,정년도모형흔난대기진행준학예측.침대저일문제 ,근거황산풍경구일객류량적분포특점 ,건립료1、2화12월 ,3、6화11월 , 4화5월 ,7화8월 ,9화10월이급법정절가일륙류예측모형 ,통과S V R예측방법적실증방진현시 ,동년도모형상비기우객류량분포특정적분류모형명현소제료일객류량도약파동 ,유효지제고료예측정도.
The accurate forecasting of daily visitor numbers can provide scientific and reliable basis for the decision-making management of scenic area .Due to various objective factors ,the daily visitor numbers not only shows nonlinear characteristics but also has obvious seasonal characteristics .It is difficult to forecast daily visitor numbers accurately by the annual model because of the heavy fluctuation of annual daily data .In order to solve this problem ,based on the distribution characteristics of daily visitor numbers of Huangshan scenic area ,this paper established six classification forecasting models (January February and December ,March June and November , April and May ,July and August ,September and October ,official holiday ) .Through simulation by SVR and compared with annual model ,the results showed that six classification models eliminated the jump and fluctuations obviously ,and improved the forecasting precision effectively .
