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休閒趨勢分析及評估 - 作業二 - PowerPoint PPT Presentation

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休閒趨勢分析及評估-作業二

• 從圖一可得知Naïve 1最接近實際值，反之Naïve2偏差最大。
• 其預測力Naïve1 > Seasonal Naïve > Naïve2。
• 由圖表得知，阿里山國家風景區之季節性因子可能是以一季(6個月)為單位之遊客量變動。

• 平均絕對百分比誤差(Mean Absolute Percent Error, MAPE)， MAPE值愈小表示預測能力愈好。
• Lewis (1982)依據MAPE大小將模式預測能力分為四種等級，如表1所示。

• 以上數據顯示出Naïve1預測能力最強，其次為S Naïve，最後是Naïve 2，其原因可能是因為受季節因素之影響，如花季推廣，因此 Naïve 1模式較能有效預測。
• 由於遊客量是隨時間點而改變，而阿里山國家風景區的預測模式可能也會因氣候而改變，像是2009年莫拉克颱風造成道路中斷，影響前往人潮。