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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:构建添加剂模型,用于确定化学工业企业提供的产品数量的季节性影响

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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:研究下的问题的紧迫性是由于需要提高在不断变化的条件下运作的工业企业活动的效率。化学工业企业是企业对产品的季节性需求,特别是在生产矿物肥料的生产中。与此同时,他们经常面临大量有缺陷的产品和重大运输成本问题。此外,企业被迫储存大量购买产品。由于从供应商订购的需求和原材料的不准确性,因此出现了这个问题[11]。降低成本的方法之一是确定库存项目的最佳数量[3]。该物品的目的是开发一种添加剂模型,用于确定对化学工业提供的产品数量的季节性影响。领先的研究方法是一种确定季节性指数的统计方法,这使得可以创建一种趋势方程,这些趋势方程可以反映了研究期间每月的每月的每月的月平均值和增长率。文章的主要结果:确定了季节性指数,评估了化学工业企业产品供应添加剂模型的季节性成分。本文的材料对于在季节性需求条件下运行的任何业务实体都很有用。结果将允许预测最佳的交付数量。

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