How to cite this paper
& . (2014). Predicting product life cycle using fuzzy neural network.Management Science Letters , 4(9), 2057-2064.
Refrences
Altug, S., Chen, M. Y., & Trussell, H. J. (1999). Fuzzy inference systems implemented on neural architectures for motor fault detection and diagnosis. Industrial Electronics, IEEE Transactions on, 46(6), 1069-1079.
Bezdek, J. C. (1981). Pattern recognition with fuzzy objective function algorithms. Kluwer Academic Publishers.
Chang, L. C., & Chang, F. J. (2001). Intelligent control for modelling of real?time reservoir operation. Hydrological Processes, 15(9), 1621-1634.
Djukanovic, M. B., Calovic, M. S., Vesovic, B. V., & Sobajic, D. J. (1997). Neuro-fuzzy controller of low head hydropower plants using adaptive-network based fuzzy inference system. Energy Conversion, IEEE Transactions on,12(4), 375-381.
Gallo, A. E. (1992). Record number of new products in 1991. Food Review,15(3), 19-21.
Ham, F. M., & Kostanic, I. (2000). Principles of neurocomputing for science and engineering. McGraw-Hill Higher Education.
Jang, J. S. (1993). ANFIS: adaptive-network-based fuzzy inference system.Systems, Man and Cybernetics, IEEE Transactions on, 23(3), 665-685.
Liao, H. P., Su, J. P., & Wu, H. M. (2001). An Application of ANFIS to Modeling of a Forecasting System for the Demand of Teacher Human Resources (Article written in Chinese). Journal of Education and Psychology,24(1), 1-17.
Li, R. P., Mukaidono, M., & Turksen, I. B. (2002). A fuzzy neural network for pattern classification and feature selection. Fuzzy Sets and Systems, 130(1), 101-108.
Madhani, P. M. (2011). Restructuring fixed and variable pay in sales organizations: a product life cycle approach. Compensation & Benefits Review,43(4), 245-258.
Oonsivilai, A., & El-Hawary, M. E. (1999, May). Power system dynamic load modeling using adaptive-network-based fuzzy inference system. In Electrical and Computer Engineering, 1999 IEEE Canadian Conference on (Vol. 3, pp. 1217-1222). IEEE.
Ryan, C., & Riggs, W. E. (1996). Redefining the product life cycle: the five-element product wave. Business Horizons, 39(5), 33-40.
Rink, D. R., Roden, D. M., & Fox, H. W. (1999). Financial management and planning with the product life cycle concept. Business Horizons, 42(5), 65-72.
Sfetsos, A. (2000). A comparison of various forecasting techniques applied to mean hourly wind speed time series. Renewable energy, 21(1), 23-35.
Turksen, I. B. (1991). Measurement of membership functions and their acquisition. Fuzzy sets and systems, 40(1), 5-38.
Takagi, T., & Sugeno, M. (1985). Fuzzy identification of systems and its applications to modeling and control. Systems, Man and Cybernetics, IEEE Transactions on, (1), 116-132.
Watanabe, S. (1985). Pattern recognition: human and mechanical. John Wiley & Sons, Inc.
Zadeh, L.A. (1965). Fuzzy Sets. Information and Control, 8, 338–353.
Bezdek, J. C. (1981). Pattern recognition with fuzzy objective function algorithms. Kluwer Academic Publishers.
Chang, L. C., & Chang, F. J. (2001). Intelligent control for modelling of real?time reservoir operation. Hydrological Processes, 15(9), 1621-1634.
Djukanovic, M. B., Calovic, M. S., Vesovic, B. V., & Sobajic, D. J. (1997). Neuro-fuzzy controller of low head hydropower plants using adaptive-network based fuzzy inference system. Energy Conversion, IEEE Transactions on,12(4), 375-381.
Gallo, A. E. (1992). Record number of new products in 1991. Food Review,15(3), 19-21.
Ham, F. M., & Kostanic, I. (2000). Principles of neurocomputing for science and engineering. McGraw-Hill Higher Education.
Jang, J. S. (1993). ANFIS: adaptive-network-based fuzzy inference system.Systems, Man and Cybernetics, IEEE Transactions on, 23(3), 665-685.
Liao, H. P., Su, J. P., & Wu, H. M. (2001). An Application of ANFIS to Modeling of a Forecasting System for the Demand of Teacher Human Resources (Article written in Chinese). Journal of Education and Psychology,24(1), 1-17.
Li, R. P., Mukaidono, M., & Turksen, I. B. (2002). A fuzzy neural network for pattern classification and feature selection. Fuzzy Sets and Systems, 130(1), 101-108.
Madhani, P. M. (2011). Restructuring fixed and variable pay in sales organizations: a product life cycle approach. Compensation & Benefits Review,43(4), 245-258.
Oonsivilai, A., & El-Hawary, M. E. (1999, May). Power system dynamic load modeling using adaptive-network-based fuzzy inference system. In Electrical and Computer Engineering, 1999 IEEE Canadian Conference on (Vol. 3, pp. 1217-1222). IEEE.
Ryan, C., & Riggs, W. E. (1996). Redefining the product life cycle: the five-element product wave. Business Horizons, 39(5), 33-40.
Rink, D. R., Roden, D. M., & Fox, H. W. (1999). Financial management and planning with the product life cycle concept. Business Horizons, 42(5), 65-72.
Sfetsos, A. (2000). A comparison of various forecasting techniques applied to mean hourly wind speed time series. Renewable energy, 21(1), 23-35.
Turksen, I. B. (1991). Measurement of membership functions and their acquisition. Fuzzy sets and systems, 40(1), 5-38.
Takagi, T., & Sugeno, M. (1985). Fuzzy identification of systems and its applications to modeling and control. Systems, Man and Cybernetics, IEEE Transactions on, (1), 116-132.
Watanabe, S. (1985). Pattern recognition: human and mechanical. John Wiley & Sons, Inc.
Zadeh, L.A. (1965). Fuzzy Sets. Information and Control, 8, 338–353.