台灣白肉雞產地價格之灰預測模型研究

Grey Prediction Models for Broiler Farm Price in Taiwan

本研究根據灰預測的方法，利用相關變數的原始資料，建構適合白肉雞產地價格之灰預測模型（grey prediction models, GM）GM（1, N）預測模型，並分析相關之影響因素。其結果顯示以GM（1, 1）模型來預測，價格資訊運用的最佳筆數為八筆；而以GM（1, N）模型中之GM（1, 6）模型來預測準確度可達95.26%，表示白肉雞產地價格適合以此推估模式進行預測，並可獲得精確的預測結果，故本研究結果可提供農政單位在價格預警及產業輔導的基礎，與業者作為調整出雞及入雞時間決策的參考依據。 This study, based on the grey prediction methodology, builds up the GM (1, N) prediction model for broiler farm price and used the primary data of related variables to analyze related affecting factors. The result shows that the count for the application of price information to get best GM (1, 1) model is 8 periods. In the GM (1, N) model, the result indicates that the GM (1, 6) model is suitable for the farm price prediction of broiler. Therefore, this implies that the result of this study could provide the price information basis for consulting measure decisions, such as price warning, of related agricultural authorities and production decisions, such as the suitable time to buy chick and sell out broiler, of farmers.

This study, based on the grey prediction methodology, builds up the GM (1, N) prediction model for broiler farm price and used the primary data of related variables to analyze related affecting factors. The result shows that the count for the application of price information to get best GM (1, 1) model is 8 periods. In the GM (1, N) model, the result indicates that the GM (1, 6) model is suitable for the farm price prediction of broiler. Therefore, this implies that the result of this study could provide the price information basis for consulting measure decisions, such as price warning, of related agricultural authorities and production decisions, such as the suitable time to buy chick and sell out broiler, of farmers.