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The hybrid-model architectural modelling based on ARIMA-BPNN methods for building materials demands forecasting

机译：基于ARIMA-BPNN建筑材料方法的混合模型架构建模要求预测

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The development of hybrid acrhitectural model is made to facilitate the decision making in determining the demand for building materials procurement. The ARIMA time series and non-linear BPNN models are selected considered that they are able to have a high degree of accuracy of the generated output. The data used were the secondary data collected in the period of February 2015-October 2016 which consisted of month of sales period, product prices, sales history (per type of building materials), estimated number of renovation projects, estimated number of new construction projects, and number of competitors. This research was conducted through 2 stages, they were; the processing of time series using ARIMA through three basic steps, namely identification, assessment and testing, and diagnostic examination; and the BPNN processing through data training and data testing stages. The produced hybrid architectural model had 99% accuracy with an MSE of 0.00099926 on epoch 975 and training period of 00:00:01. The Regression results showed that the produced model has a high degree of accuracy in generating the ouput of building materials demand forecasting.
机译：制定混合校准模型的发展，促进了确定建筑材料采购需求的决策。选择ARIMA时间序列和非线性BPNN模型认为，它们能够具有产生的输出的高精度。所使用的数据是2016年2月期间收集的二级数据，由月份，由月份，产品价格，销售历史（每种类型的建筑材料），估计的装修项目数，估计新建项目数量和竞争对手的数量。这项研究通过2个阶段进行;通过三个基本步骤处理时间序列的处理，即识别，评估和测试，诊断检查;和通过数据培训和数据测试阶段的BPNN处理。制作的混合架构模型具有99％的精度，在EPOC 975上的MSE为0.00099926，00:00:01培训期。回归结果表明，所生产的模型具有高度准确性，在产生建筑材料需求预测的出口时。

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