Fuzzy logic and NeuroFuzzy applications in business and finance
Fuzzy logic and NeuroFuzzy applications in business and finance
Now comes the time to defuzzify neuro-fuzzy models
Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
A new approach of neuro-fuzzy learning algorithm for tuning fuzzy rules
Fuzzy Sets and Systems
Application of adaptive neuro-fuzzy controller for SRM
Advances in Engineering Software
A neuro fuzzy logic approach to material processing
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Complex systems modeling via fuzzy logic
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A systematic neuro-fuzzy modeling framework with application tomaterial property prediction
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A fuzzy-logic-based approach to qualitative modeling
IEEE Transactions on Fuzzy Systems
A neuro-fuzzy network to generate human-understandable knowledge from data
Cognitive Systems Research
Expert Systems with Applications: An International Journal
Design of real-time fuzzy bus holding system for the mass rapid transit transfer system
Expert Systems with Applications: An International Journal
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This paper proposes an adaptive neuro-fuzzy inference system (ANFIS) and a KERNEL System to solve the problem of predicting rush orders for regulating the capacity reservation mechanism in advance. The adopted approaches generalize the association rules among rush orders, as well as to forecast product items, quantities and the occasion of the contingent rush orders via learning from the sales data of an actual electronic manufacturing firm. Especially, we compare results with the traditional regression analysis and obtain preferable forecasts. In sum the overall forecasting correctness is 83% by ANFIS which is superior to regression manner with 63%. Preliminary results on the application of the proposed methods are also reported. It is expected to offer managers to refer to arrange the reserved capacity and to construct a robust schedule in anticipation.