Research And Development Of ATM Cash Flow Forecasting System Based On Combination Algorithm

With the popularity of ATM,the prediction of ATM cash flow has become a hot and difficult issue for major banks.To maximize the benefits of banks on the ground of maintaining good operation,the accurate prediction of ATM cash flow is of great importance.For ATM cash flow is influenced by many uncertain factors,the use of one single prediction could not satisfy our prediction needs.So against this background,a combined prediction algorithm is proposed in the prediction of ATM cash flowBased on the research of ATM cash flow prediction algorithm at home and abroad,four prediction methods are selected as the prediction individuals,including BP artificial neural network,Support Vector Machine(SVM),Autoregressive Integrated Moving Average Model(ARIMA)and statistical analysis.By studying the above four prediction methods,it can be found out that BP artificial neural network has the disadvantages of slow error convergence rate and long learning time due to fixed learning rates in the back propagation process,so the different learning rates are adopted in the back propagation process which can improve BP artificial neural network.ARIMA,as a frequently used prediction model in statistics,will lead to artificial errors in determining the parameters of models.Therefore,to improve ARIMA,the method of identifying model parameters dynamically is put forward,which is the optimal option with minimum errors.In the end,the comparisons of the prediction advantages of the four prediction methods through concrete experiments are given.The essence of combined prediction algorithm is obtaining a high-accuracy and strong-adaptability prediction algorithm by combining the advantages of each single prediction algorithm and through the automatic adjustment of the weights of each prediction model in the system.Based on the study of the existing combined prediction algorithm,the combined prediction method of changing indexes into weights is proposed when determining the weights of each single prediction algorithm.The result of concrete experiment proves that combined prediction algorithm has higher accuracy than each single prediction algorithm in predicting the cash flow data of the same period of time period.The ultimate goal of this thesis is to develop an ATM cash flow prediction system that takes the combined prediction algorithm as the core algorithm by combining the Spring MVC framework.Finally,through the analysis of the requirements of the prediction system and the display of the functional pages,the summary of this thesis is made by pointing out the shortcomings of the research process and the direction of the future search and by looking into the future.