物流工程与管理
物流工程與管理
물류공정여관리
Logistics Engineering and Management
2015年
9期
114-115,109
,共3页
联络中心%小波变换%粒子群算法%BP神经网络%任务量预测
聯絡中心%小波變換%粒子群算法%BP神經網絡%任務量預測
련락중심%소파변환%입자군산법%BP신경망락%임무량예측
contact center%wavelet transform%particle swarm optimization%back propagation (BP )neural network%tasks prediction
随着物流快递等业务的迅速发展，联络中心作为一个新兴服务行业也随之变成了服务机构和客户沟通的最重要的桥梁。联络中心任务量预测的准确性对基础设施和人员投入至关重要。因此，文中提出了一种结合小波变换和PSO－BP的组合预测模型，通过小波变换把任务量序列分解成高频和低频序列，再为分解序列建立合适的PSO－BP预测模型，求出最优解。最后，实例分析表明，该模型对非线性时间序列有更好的拟合能力和更高的预测精度。
隨著物流快遞等業務的迅速髮展，聯絡中心作為一箇新興服務行業也隨之變成瞭服務機構和客戶溝通的最重要的橋樑。聯絡中心任務量預測的準確性對基礎設施和人員投入至關重要。因此，文中提齣瞭一種結閤小波變換和PSO－BP的組閤預測模型，通過小波變換把任務量序列分解成高頻和低頻序列，再為分解序列建立閤適的PSO－BP預測模型，求齣最優解。最後，實例分析錶明，該模型對非線性時間序列有更好的擬閤能力和更高的預測精度。
수착물류쾌체등업무적신속발전，련락중심작위일개신흥복무행업야수지변성료복무궤구화객호구통적최중요적교량。련락중심임무량예측적준학성대기출설시화인원투입지관중요。인차，문중제출료일충결합소파변환화PSO－BP적조합예측모형，통과소파변환파임무량서렬분해성고빈화저빈서렬，재위분해서렬건립합괄적PSO－BP예측모형，구출최우해。최후，실례분석표명，해모형대비선성시간서렬유경호적의합능력화경고적예측정도。
With the rapid development of logistic,express delivery and so on,the contact center,as a new service industry, has become the most important bridge between the service organizations and their customers.The accuracy of tasks prediction in contact centers of logistic is very important to infrastructure investment and staffing.Therefore,a model that combines the wavelet transform and PSO-BP neural network is proposed.By the wavelet transform,the tasks are decomposed into high frequency and low frequency series,for which the suitable PSO-BP models are established to search the optimal solution.Finally,the analysis of the example indicates that the fitting ability and prediction accuracy of the method are better than other methods.
