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Grey modelling based forecasting system for return flow of end-of-life vehicles

机译:基于灰色建模的报废车辆回流预测系统

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Due to legislation and economic reasons, firms in most industries are forced to be responsible and manage their products at the end of their lives. Management of product returns is critical for the stability and profitability of a reverse supply chain. Forecasting the return amounts and timing is beneficial. The purpose of this paper is to develop a forecasting system for discarded end-of-life vehicles and to predict the number of end-of-life vehicles that will be generated in the future. To create the forecasting system, grey system theory, which uses a small amount of the most recent data, is employed. The accuracy of the grey model is improved with parameter optimization, Fourier series and Markov chain correction. The proposed models are applied to the case of Turkey and data sets of twelve regions in Turkey are considered. The obtained results show that the proposed forecasting system can successfully govern the phenomena of the data sets, and high accuracy can be provided for each region in Turkey. The proposed forecasting system can be used as a strategic tool in similar forecasting problems, and supportive guidance can be achieved. (C) 2016 Elsevier Inc. All rights reserved.
机译:由于立法和经济原因,大多数行业的公司被迫在产品生命周期末负责并管理其产品。产品退货的管理对于逆向供应链的稳定性和获利能力至关重要。预测退货金额和时机是有益的。本文的目的是为报废的报废车辆开发一个预测系统,并预测将来将要报废的报废车辆的数量。为了创建预测系统,采用了使用少量最新数据的灰色系统理论。通过参数优化,傅里叶级数和马尔可夫链校正提高了灰色模型的准确性。提议的模型适用于土耳其的情况,并考虑了土耳其十二个地区的数据集。获得的结果表明,所提出的预测系统可以成功地控制数据集的现象,并且可以为土耳其的每个区域提供高精度。所提出的预测系统可以用作类似预测问题中的战略工具,并可以提供支持性指导。 (C)2016 Elsevier Inc.保留所有权利。

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