Assessment of Exported Tea Quantity using Fuzzy Neural Model - Roy, Arindam; Singh, Dharmpal; Sahana, Sudipta; Nath, Ira; Rakshit, Pranati (International Journal of Computer Sciences and Engineering, 2020)
In the field of prediction Assessment plays a major role. The prediction result becomes incorrect if a Assessment is not selected properly and the scope of future work becomes lost or unpredictable. Therefore an appropriate technique needs to be selected for the purpose of forecasting. There are lot of soft computing models which are being used in various application for the purpose of forecasting. The performance of fuzzy logic and Artificial Neural Network, in the field of soft computing, are being examined for the purpose of Assessment on the basis of average error. Here an effort is being used to select the proper soft computing technique to predict the futuristic information of quantity of exported tea to be exported in near future. Initially, the concept of Fuzzy Logic based on Fuzzy Membership Function has been applied and therefore after concept of Feed Forward Back propagation Neural Network of soft computing has been used to optimize the error.