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A decision support system for sales forecasting through fuzzy neural networks with asymmetric fuzzy weights

机译:具有不对称模糊权重的模糊神经网络的销售预测决策支持系统

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摘要

Sales forecasting plays a very prominent role in business strategy. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average (ARMA). However, sales forecasting is very complicated owing to influence by internal and external environments. Recently, artificial neural networks (ANNs) have also been applied in sales forecasting since their promising performances in the areas of control and Pattern recognition. However, further improvement is still necessary since unique circumstances, e-g-, promotion, cause a sudden change in the sales pattern. Thus, this study utilizes fuzzy logic a proposed fuzzy neural network (FNN) for the sake of learning fuzzy IF--THEN rules obtained from the marketing experts with respect to promotion. The result from FNN is further integrated with the forecast from ANN using the time series data and the promotion length through the other ANN. Model evaluation results indicate that the proposed system can more accurately perform than the conventional statistical method and single ANN.
机译:销售预测在业务战略中扮演着非常重要的角色。解决此问题的大量研究通常采用统计方法,例如回归或自回归和移动平均值(ARMA)。但是,由于受内部和外部环境的影响,销售预测非常复杂。近年来,由于人工神经网络(ANN)在控制和模式识别领域的良好表现,它们也已用于销售预测。但是,由于特殊情况(例如促销)会导致销售模式的突然变化,因此仍需要进一步的改进。因此,本研究利用模糊逻辑提出的模糊神经网络(FNN)来学习从营销专家那里获得的关于促销的模糊IF--THEN规则。 FNN的结果与时间序列数据和通过另一个ANN的促销长度进一步与ANN的预测相集成。模型评估结果表明,所提出的系统比常规的统计方法和单个ANN能够更准确地执行。

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