Design of Forecasting for Perishable Product with Artficial Neural Network

Chintya Salwa Sabhira
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Abstract

Raw materials are an important part of the manufacturing industry, especially for raw materials that do not last long or have a lifespan. To be able to produce good products, the raw materials used must be of good quality. This happened to company XYZ which operates in the cereal and snack food industry. Inventory control is quite a big challenge for companies. In this year the company experienced losses due to a shortage of finished snacks products, due to finished goods being obsolete due to a lack of accuracy in forecasting snack demand. The research raised forecasting using the Artificial Neural Network method. ANN is known to be able to produce good accuracy values in predicting sales.
利用人工神经网络设计易腐产品的预测方法
原材料是制造业的重要组成部分,尤其是那些使用寿命不长的原材料。要想生产出优质产品,所使用的原材料必须质量上乘。从事谷物和休闲食品行业的 XYZ 公司就遇到了这种情况。库存控制是公司面临的一大挑战。这一年,由于对零食需求预测不够准确,导致零食成品过期,公司因零食成品短缺而蒙受损失。研究提出使用人工神经网络方法进行预测。众所周知,人工神经网络在预测销售方面能够产生良好的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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