An efficient approach for large scale project planning based on fuzzy Delphi method
Fuzzy Sets and Systems
Fuzzy ARIMA model for forecasting the foreign exchange market
Fuzzy Sets and Systems
Linear regression analysis for fuzzy/crisp input and fuzzy/crisp output data
Computational Statistics & Data Analysis
International Journal of Systems Science
Neural network based flow forecast and diagnosis
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Interval regression analysis by quadratic programming approach
IEEE Transactions on Fuzzy Systems
Mathematical and Computer Modelling: An International Journal
Intelligent scheduling approaches for a wafer fabrication factory
Journal of Intelligent Manufacturing
Forecasting the yield of a semiconductor product with a collaborative intelligence approach
Applied Soft Computing
A flexible way of modeling the long-term cost competitiveness of a semiconductor product
Robotics and Computer-Integrated Manufacturing
Learning Fuzzy Network Using Sequence Bound Global Particle Swarm Optimizer
International Journal of Fuzzy System Applications
International Journal of Fuzzy System Applications
A PCA-FBPN Approach for Job Cycle Time Estimation in a Wafer Fabrication Factory
International Journal of Fuzzy System Applications
A Fuzzy Multiple Regression Approach for Optimizing Multiple Responses in the Taguchi Method
International Journal of Fuzzy System Applications
FSSC: An Algorithm for Classifying Numerical Data Using Fuzzy Soft Set Theory
International Journal of Fuzzy System Applications
International Journal of Intelligent Information Technologies
A collaborative and artificial intelligence approach for semiconductor cost forecasting
Computers and Industrial Engineering
A fuzzy-neural approach for global CO2 concentration forecasting
Intelligent Data Analysis
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Accurately forecasting the foreign exchange rate is important for export-oriented enterprises. For this purpose, a fuzzy and neural approach is applied in this study. In the fuzzy and neural approach, multiple experts construct fuzzy linear regression FLR equations from various viewpoints to forecast the foreign exchange rate. Each FLR equation can be converted into two equivalent nonlinear programming problems to be solved. To aggregate these fuzzy foreign exchange rate forecasts, a two-step aggregation mechanism is applied. At the first step, fuzzy intersection is applied to aggregate the fuzzy forecasts into a polygon-shaped fuzzy number to improve the precision. A back propagation network is then constructed to defuzzify the polygon-shaped fuzzy number and generate a representative/crisp value to enhance accuracy. To evaluate the effectiveness of the fuzzy and neural approach, a practical case of forecasting the foreign exchange rate in Taiwan is used. According to the experimental results, the fuzzy and neural approach improved both the precision and accuracy of the foreign exchange rate forecasting by 79% and 81%, respectively.