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Building an Additive Model for Determining the Seasonal Effect on the Quantity of Products Supplied by the Chemical Industry Enterprises

机译:建立用于确定化工企业提供的产品数量的季节性影响的加性模型

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The urgency of the problem under study is due to the need to improve the efficiency of the activities of industrial enterprises operating in constantly changing conditions. Chemical industry enterprises are enterprises with seasonal demand for products, especially in the production of mineral fertilizers. At the same time, they often face the problem of a large number of defective products and significant transportation costs. In addition, enterprises are forced to store significant volumes of purchased products. This problem arises because of inaccurate forecasts of demand and volumes of raw materials ordered from suppliers [11]. One of the ways to reduce costs is to determine the optimal number of deliveries of inventory items [3]. The purpose of the article is to develop an additive model for determining the seasonal effect on the quantity of products supplied to the chemical industry. The leading method of research is a statistical method for determining the seasonality index, which made it possible to create a trend equation that reflects the average monthly supply of raw materials and the growth rate in each month of the study period. The main results of the article: seasonality indices were determined, the seasonal component of the additive model of product supply by chemical industry enterprises was evaluated. Materials of the article can be useful for any business entities that operate in conditions of seasonal demand. The results will allow to make a forecast of the optimal number of deliveries.
机译:正在研究的问题的紧迫性是由于需要提高在不断变化的条件下运行的工业企业的活动效率。化学工业企业是对产品有季节性需求的企业,特别是在矿物肥料生产方面。同时,它们经常面临大量次品和大量运输成本的问题。另外,企业被迫存储大量购买的产品。出现此问题的原因是对需求的预测和从供应商处订购的原材料数量不准确[11]。降低成本的方法之一是确定库存物品的最佳交付数量[3]。本文的目的是开发一种附加模型,以确定对供应给化学工业的产品数量的季节性影响。领先的研究方法是确定季节性指数的统计方法,该方法可以创建一个趋势方程,该方程反映出研究期间每个月的原材料平均每月供应量和增长率。本文的主要结果是:确定季节性指数,评估化学工业企业产品供应附加模型的季节性成分。本文的材料对于在季节性需求条件下运营的任何业务实体都可能有用。结果将有助于预测最佳交付数量。

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