This task introduces a novel demand forecasting method using concatenated Convolutional Neural Network(CNN)with an Adaptive Network-based Fuzzy Inference System(ANFIS).The data regarding the historical demand and sale...This task introduces a novel demand forecasting method using concatenated Convolutional Neural Network(CNN)with an Adaptive Network-based Fuzzy Inference System(ANFIS).The data regarding the historical demand and sales data in integration with'advertising effectiveness,expenditure,promotions,and marketing events data'are collected initially.Then,the first-order statistical metrics and second-order statistical metrics are determined as the significant features of the data.Finally,the forecasting is performed by the concatenation of modified CNN with ANFIS termed Concatenated Learning Model(CLM),in which the CNN learns the optimal features that are forecasted by the ANFis layer instead of the fully connected layer.Deer Hunting with Modified Wind Angle Search(DH-MWS)is used to enhance the CNN and ANFIS architecture,ensuring better performance during forecasting.Simulation findings demonstrate that when the proposed solution is applied to public data,the store achieves improved accuracies concerning intelligent demand forecasting in the marketing sector.展开更多
文摘This task introduces a novel demand forecasting method using concatenated Convolutional Neural Network(CNN)with an Adaptive Network-based Fuzzy Inference System(ANFIS).The data regarding the historical demand and sales data in integration with'advertising effectiveness,expenditure,promotions,and marketing events data'are collected initially.Then,the first-order statistical metrics and second-order statistical metrics are determined as the significant features of the data.Finally,the forecasting is performed by the concatenation of modified CNN with ANFIS termed Concatenated Learning Model(CLM),in which the CNN learns the optimal features that are forecasted by the ANFis layer instead of the fully connected layer.Deer Hunting with Modified Wind Angle Search(DH-MWS)is used to enhance the CNN and ANFIS architecture,ensuring better performance during forecasting.Simulation findings demonstrate that when the proposed solution is applied to public data,the store achieves improved accuracies concerning intelligent demand forecasting in the marketing sector.
