基于Clementine神经网络的商品促销效果预测模型应用  

Application of BP Algorithm Based on Clementine for Forecasting Effects of Commodity Promotion

作　　者：林耀斌[1] 杜友福[1] LIN Yao-bin, DU You-fu （College of Computer Science,Yangtze Universiw,Jingzhou 434023,China）

机构地区：[1]长江大学计算机科学学院,湖北荆州434023

出　　处：《电脑知识与技术》2009年第12期9790-9792,共3页Computer Knowledge and Technology

摘　　要：介绍了人工神经网络的基本原理，将神经网络的BP算法引入商品促销研究领域，并运用Clementine建立BP神经网络模型，以某个历史促销数据为原始数据样拳，对网络进行训练后，对商品促销效果进行预测，预测模型在预测精度和收敛速度方面都达到了较好的效果．对商家的决策支持产生了积极的影响。This article introduced the artificial neural network basic concept.BP algorithm of Neural Networks was introduced into commodity promotion, established the BP neural network model by Clementine, took some historical sales data as the primary datasample, carried on the training after the network, had carried on the forecast to the effects of commodity promotion, Forecastaccuracy and algorithmic convergence speed of the forecast model reached fairly good effect, which had a positive impact on the business decision support.

关 键 词：商品促销 数据挖掘 CLEMENTINE BP神经网络 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论;自动化与计算机技术—计算机科学与技术]