Orbanic, P., and Fajdiga, M., 1999, “R&D Process Located at Automotive Industry Suppliers,” M.Fajdiga, T.Jurejevcic, and F.Trenc, eds., "*Proceedings of 4th Conference and Exhibition Innovative Automotive Technology – IAT’99*", Nova Gorica, Slovenia, April 8–9, pp. 233–240.

Nagode, M., and Fajdiga, M., 1998, “On a New Method for Prediction of the Scatter of Loading Spectra,” Int. J. Fatigue, 20 (4), pp. 271–277.

[CrossRef]Nagode, M., Klemenc, J., and Fajdiga, M., 2001, “Parametric Modelling and Scatter Prediction of Rainflow Matrices,” Int. J. Fatigue, 23 (6), pp. 525–532.

[CrossRef]Shen, H., Lin, J., and Mu, E., 2000, “Probabilistic Model on Stochastic Fatigue Damage,” Int. J. Fatigue, 22 (7), pp. 569–572.

[CrossRef]Tovo, R., 2001, “On the Fatigue Reliability Evaluation of Structural Components Under Service Loading,” Int. J. Fatigue, 23 (7), pp. 587–598.

[CrossRef]Zhao, Y. X., Yang, B., and Zhai, Z. Y., 2008, “The Framework for a Strain-Based Fatigue Reliability Analysis,” Int. J. Fatigue, 30 (3), pp. 493–501.

[CrossRef]Spoormaker, J. L., 1996, “The Role of Polymer Engineering in Designing for Reliability of Plastic Products,” Mater. Sci., 32 (4), pp. 396–402.

[CrossRef]Bernasconi, A., Davoli, P., Basile, A., and Filippi, A., 2007, “Effect of Fibre Orientation on the Fatigue Behaviour of a Short Glass Fibre Reinforced Polyamide-6,” Int. J. Fatigue, 29 , pp. 199–208.

[CrossRef]McCrum, N. G., Buckley, C. P., and Bucknall, C. B., 1988, "*Principles of Polymer Engineering*", 2nd ed., Oxford Science Publications, New York.

Tsang, K. Y., DuQuesnay, D. L., and Bates, P. J., 2008, “Fatigue Properties of Vibration-Welded Nylon 6 and Nylon 66 Reinforced With Glass Fibres,” Composites, Part B, 39 , pp. 396–404.

[CrossRef]Zupancic, B., Nikonov, A. V., Florjancic, U., and Emri, I., 2007, “Time-Dependent Behaviour of Drive Belts Under Periodic Mechanical Loading: Analysis of the Location of a Single Line Spectrum,” J. Mech. Eng., 53 (10), pp. 696–705.

Zupancic, B., and Emri, I., 2009, “Time-Dependent Constitutive Modelling of Drive Belts – II. The Effect of the Shape of Material Retardation Spectrum on the Strain Accumulation Process,” Mech. Time-Depend. Mater., 13 , pp. 375–400.

[CrossRef]Wyzgoski, M. G., Krohn, J. A., and Novak, G. E., 2004, “Fatigue of Fiber-Reinforced Injection Molded Plastics I: Stress-Lifetime Data,” Polym. Compos., 25 (5), pp. 489–498.

[CrossRef]Crawford, R. J., 1998, "*Plastic Engineering*", 3rd ed., Butterworth-Heinemann, Oxford.

Moet, A., and Aglan, H.1988, "*Fatigue Failure, Engineered Materials Handbook*", Vol.2 , Engineering Plastics, ASM International.

Ward, I. M., and Hadley, D. W., 1997, "*An Introduction to the Mechanical Properties of Solid*", John Willey & Sons, New York.

DuPont Engineering Polymers: DuPont Minlon and Zytel naylon resins: "*Design information—Module II*". DuPont Company, 2002.

Wyzgoski, M. G., Krohn, J. A., and Novak, G. E., 2004, “Fatigue of Fibre-Reinforced Injection Molded Plastics II: Tensile Versus Flexural Loading,” Polym. Compos., 25 (6), pp. 569–576.

[CrossRef]Crawford, R. J., and Benhem, P. P., 1975, “Some Fatigue Characteristics of Thermoplastics,” Polymer, 16 , pp. 908–914.

[CrossRef]Lee, J. A., Almond, D. P., and Harris, B., 1999, “The Use of Neural Networks for the Prediction of Fatigue Lives of Composite Materials,” Composites, Part A, 30 , pp. 1159–1169.

[CrossRef]Vassilopoulos, A., Georgopoulos, E., and Keller, T., 2008, “Comparison of Genetic Programming With Conventional Methods for Fatigue Life Modelling of FRP Composite Materials,” Int. J. Fatigue, 30 (9), pp. 1634–1645.

[CrossRef]Freire, S. J., Carlos, R., Neto, D., De Aquino, A. D., and Freire, E. M., 2009, Comparative Study Between ANN Models and Equations in the Conventional Analysis of Fatigue Failure of GFRP,” Int. J. Fatigue, 31 (5), pp. 831–839.

[CrossRef]Al-Assadi, M., El Kadi, H., and Deiab, I. M., 2010, “Predicting the Fatigue Life of Different Composite Materials Using Artificial Neural Networks,” Appl. Compos. Mater., 17 , pp. 1–14.

[CrossRef]Agarwal, M., 1997, “Combining Neural and Conventional Paradigms for Modelling, Prediction and Control,” Int. J. Syst. Sci., 28 (1), pp. 65–81.

[CrossRef]Klemenc, J., and Fajdiga, M., 2002, “A Neural Network Approach to the Simulation of Load Histories by Considering the Influence of a Sequence of Rainflow Load Cycles,” Int. J. Fatigue, 24 (11), pp. 1109–1125.

[CrossRef]Klemenc, J., and Fajdiga, M., 2004, “An Improvement to the Methods for Estimating the Statistical Dependencies of the Parameters of Random Load States,” Int. J. Fatigue, 26 (2), pp. 141–154.

[CrossRef]Bucar, T., Nagode, M., and Fajdiga, M., 2006, “A Neural Network Approach to Describing the Scatter of S-N Curves,” Int. J. Fatigue, 28 (4), pp. 311–323.

[CrossRef]Bucar, T., Nagode, M., and Fajdiga, M., 2007, “An Improved Neural Computing Method for Describing the Scatter of S-N Curves,” Int. J. Fatigue, 29 (12), pp. 2125–2137.

[CrossRef]Janezic, M., Klemenc, J., and Fajdiga, M., 2010, “A Neural-Network Approach to Describe the Scatter of Cyclic Stress-Strain Curves,” Mater. Des., 31 (1), pp. 438–448.

[CrossRef]"*Fatigue and Tribological Properties of Plastics and Elastomers*", Plastics Design Library; Norwich, 1995.

Buxbaum, O., 1992, "*Betriebsfestigkeit: sichere und wirtschafliche Bemessung schwingbruchgefaehredeter Bauteile*", Strahleisen, Duesseldorf.

Haibach, E., 1989, "*Betriebsfestigkeit: Verfahren und Daten zur Bauteilerechnung*", VDI Verlag, Duesseldorf.

Dowling, N. E., 1999, "*Mechanical Behaviour of Materials: Engineering Methods for Deformation, Fracture, and Fatigue*", Prentice-Hall, Upper Saddle River, NY.

Adkis, D. W., and Kander, R. G., 1988, “Fatigue Performance of Glass Reinforced Thermoplastics,” "*Proceedings of the 4th Annual Conference on Advanced Composites*", Vol. 4 , pp. 437–445.

Coffin, L. F., 1954, “A Study of the Effects of Cyclic Thermal Stresses on a Ductile Material,” Trans. ASME, 76 (6), pp. 931–950.

Manson, S. S., 1965, “Fatigue: A Complex Subject—Some Simple Approximations,” Exp. Mech., 5 (7), pp. 193–226.

[CrossRef]Haykin, S., 1994, "*Neural Networks, a Comprehensive Foundation*", Macmillan College, New York.

Press, W. H., 1988, "*Numerical Recipes in C*", Cambridge University, Cambridge.

Bishop, C. M., 1995"*Neural Networks for Pattern Recognition*", Clarendon, Oxford.

Akaike, H., 1974, “A New Look at the Statistical Model Identification,” IEEE Trans. Autom. Control, 19 (6), pp. 716–723.

[CrossRef]Burnham, K. P., and Anderson, D. R., "*Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach*", 2nd ed., Springer-Verlag, Berlin, 2002.

McQuarrie, A. D. R., and Tsai, C. L., 1998, "*Regression and Time Series Model Selection World Scientific*".

Hastie, T., Tibshirani, R., Friedman, J., 2001, "*The Elements of Statistical Learning: Data Mining, Inference and Prediction*", Springer-Verlag, New York.

Cochran, W. G., 1977, "*Sampling Techniques*", 3rd ed., John Wiley & Sons, New York.

Cohen, A. C., 1965, “Maximum Likelihood Estimation in the Weibull Distribution Based on Complete and on Censored Samples,” Technometrics, 7 (4), pp. 579–588.

[CrossRef]Todorovski, L., Ljubic, P., and Dzeroski, S., 2004, “Inducing Polynomial Equations for Regression,” "*Proceedings of the 15th European Conference on Machine Learning ECML 2004*" (Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, Vol. 3201 ). Berlin, pp. 441–452.