以類神經網路建立物流中心出貨預測模式doc-資料下載頁
2025-07-17 16:42本頁面
【正文】 gh, . Pattie, D. C. and Haas, G. (1996), Forecasting Wilderness Recreation Use NeuralNetwork Vs. Regression”, AI Applications, , , .Tamada, T., Maruyama, M., Nakamura, Y., Abe, S. and Maeda, K. (1993), Water Demand Forecasting by Memory based Learning, Water Science and Technology, , , 140.Tang, Z., De Almeida, C. and Fishwick, P. A. (1991), Time Series Forecasting Using Neural Networks Vs. BoxJenkins Methodology, Simulation, , , .Villers, J. and Barnard, E. (1992), Back Propagation Neural Nets with One and Two Hidden Layers, IEEE Transactions on Neural Network, , .Wasserman, P. D. (1989), Neural Computing: Theory and Practice, NY: Van Nostrand Teinhold.作者簡介林哲宏，1998年取得國立中山大學企業(yè)管理博士學位，現為正修科技大學資訊管理系副教授暨系主任，研究領域為供應鏈管理、類神經網路應用、電子化企業(yè)、服務作業(yè)管理，其文章曾發(fā)表於International Journal of Production Economics、Journal of Statistics amp。 Management Systems、商業(yè)現代化學刊、品質學報、正修學報等期刊，為本論文之通訊作者。盧淵源，1978年取得日本義塾大學管理工學博士，現為國立中山大學企業(yè)管理系教授，研究領域為科技管理、供應鏈管理、全面品質管理，其文章曾發(fā)表於International Journal of Technology Management、International Journal of Production Economics、中山管理評論、科技管理學刊、亞太經濟管理評論等期刊。(Received Mar. 2004。 1st revised Jul. 2004。 2nd revised Oct. 2004。 accepted Feb. 2005)A Shipping Forecasting Model of Distribution Center based on Artificial Neural NetworkCheHung Lin＊Department of Information ManagementChengShiu UniversityIuanYuan LuDepartment of Business ManagementNational Sun YatSen UniversityABSTRACTThis paper proposed the constructing procedure of a shipping forecasting model of distribution center (DC) based on artificial neural network (ANN). The relevant forecasting variables can be screened through examining the operational characteristics and merchandise properties of a DC. The proposed procedure proposes some data preprocessing methods to manipulate forecasting variables to enhance the forecasting performance. Finally, two products are used as examples to illustrated the proposed procedure and examine its validation. Keywords: Distribution Center, Shipping Forecasting, Artificial Neural Network
研究報告相關推薦
鄂ICP備17016276號-1