Breaking the Stereotypical Dogma of Artificial Neural Networks with Cartesian Genetic Programming

1. Ali, J., Khan, G.M., Mahmud, S.A.: Enhancing growth curve approach using CGPANN for predicting the sustainability of new food products. In: IFIP International Conference on Artificial Intelligence Applications and Innovations, pp. 286–297. Springer (2014)

   Google Scholar 

2. Arbab, M.A., Khan, G.M., Sahibzada, A.M.: Cardiac arrhythmia classification using cartesian genetic programming evolved artificial neural network. Exp. Clin. Cardiol. 20(9) (2014)

   Google Scholar 

3. Bidlo, M.: Evolutionary design of generic combinational multipliers using development. In: International Conference on Evolvable Systems, pp. 77–88. Springer (2007)

   Google Scholar 

4. Carpenter, G.A., Grossberg, S.: The art of adaptive pattern recognition by a self-organizing neural network. Computer 21(3), 77–88 (1988)

   Article  Google Scholar 

5. Fekiač, J., Zelinka, I., Burguillo, J.C.: A review of methods for encoding neural network topologies in evolutionary computation. In: Proceedings of 25th European Conference on Modeling and Simulation ECMS 2011, pp. 410–416 (2011)

   Google Scholar 

6. Gomez, F., Schmidhuber, J., Miikkulainen, R.: Accelerated neural evolution through cooperatively coevolved synapses. J. Mach. Learn. Res. 9(May), 937–965 (2008)

   MATH  MathSciNet  Google Scholar 

7. Gomez, F.J., Miikkulainen, R.: Solving non-markovian control tasks with neuroevolution. IJCAI 99, 1356–1361 (1999)

   Google Scholar 

8. Guo, H., Nandi, A.K.: Breast cancer diagnosis using genetic programming generated feature. Pattern Recognit. 39(5), 980–987 (2006)

   Article  Google Scholar 

9. Haider, A., Hanif, M.N.: Inflation forecasting in Pakistan using artificial neural networks. Pak. Econ. Soc. Rev. 123–138 (2009)

   Google Scholar 

10. Iranpour, M., Almassi, S., Analoui, M.: Breast cancer detection from fna using svm and rbf classifier. In: 1st Joint Congress on Fuzzy and Intelligent Systems (2007)

    Google Scholar 

11. Jordan, M.I.: Attractor dynamics and parallellism in a connectionist sequential machine. In: Proceedings of the 8th Confererence of the Cognitive Science Society, pp. 531–546. Lawrence Erlbaum Associates (1986)

    Google Scholar 

12. Kamruzzaman, J., Sarker, R.A.: Forecasting of currency exchange rates using ANN: a case study. In: Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on, vol. 1, pp. 793–797. IEEE (2003, December)

    Google Scholar 

13. Khan, G.M., Ali, J., Mahmud, S.A.: Wind power forecastingan application of machine learning in renewable energy. In: 2014 International Joint Conference on Neural Networks (IJCNN), pp. 1130–1137. IEEE (2014)

    Google Scholar 

14. Khan, G.M., Khattak, A.R., Zafari, F., Mahmud, S.A.: Electrical load forecasting using fast learning recurrent neural networks. In: The 2013 International Joint Conference on Neural Networks (IJCNN), pp. 1–6. IEEE (2013)

    Google Scholar 

15. Khan, G.M., Nayab, D., Mahmud, S.A., Zafar, H.: Evolving dynamic forecasting model for foreign currency exchange rates using plastic neural networks. In: 2013 12th International Conference on Machine Learning and Applications (ICMLA), vol. 2, pp. 15–20. IEEE (2013)

    Google Scholar 

16. Khan, G.M., Ullah, F., Mahmud, S.A.: MPEG-4 internet traffic estimation using recurrent CGPANN. In: International Conference on Engineering Applications of Neural Networks, pp. 22–31. Springer (2013)

    Google Scholar 

17. Khan, G.M., Zafari, F.: Dynamic feedback neuro-evolutionary networks for forecasting the highly fluctuating electrical loads. Genet. Program. Evolvable Mach. 17(4), 391–408 (2016)

    Article  Google Scholar 

18. Khan, G.M., Zafari, F., Mahmud, S.A.: Very short term load forecasting using cartesian genetic programming evolved recurrent neural networks (CGPRNN). In: 2013 12th International Conference on Machine Learning and Applications (ICMLA), vol. 2, pp. 152–155. IEEE (2013)

    Google Scholar 

19. Khan, M.M., Ahmad, A.M., Khan, G.M., Miller, J.F.: Fast learning neural networks using cartesian genetic programming. Neurocomputing 121, 274–289 (2013)

    Article  Google Scholar 

20. Khan, M.M., Khan, G.M., Miller, J.F.: Developmental plasticity in cartesian genetic programming artificial neural networks. In: Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2011), pp. 449–458. SciTePress (2011)

    Google Scholar 

21. Kryuchin, O.V., Arzamastsev, A.A., Troitzsch, K.G.: The prediction of currency exchange rates using artificial neural networks. Exch. Organ. Behav. Teach. J. 4 (2007)

    Google Scholar 

22. Liu, K., Subbarayan, S., Shoults, R., Manry, M., Kwan, C., Lewis, F., Naccarino, J.: Comparison of very short-term load forecasting techniques. IEEE Trans. Power Syst. 11(2), 877–882 (1996)

    Article  Google Scholar 

23. Moriarty, D.E.: Symbiotic evolution of neural networks in sequential decision tasks. Ph.D. thesis, University of Texas at Austin USA (1997)

    Google Scholar 

24. Nayab, D., Khan, G.M., Mahmud, S.A.: Prediction of foreign currency exchange rates using cgpann. In: International Conference on Engineering Applications of Neural Networks, pp. 91–101. Springer (2013)

    Google Scholar 

25. Pan, Z., Nie, L.: Evolving both the topology and weights of neural networks. Parallel Algorithms Appl. 9(3–4), 299–307 (1996)

    Article  MATH  Google Scholar 

26. Papadrakakis, M., Papadopoulos, V., Lagaros, N.D.: Structural reliability analyis of elastic-plastic structures using neural networks and monte carlo simulation. Comput. Methods Appl. Mech. Eng. 136(1–2), 145–163 (1996)

    Article  MATH  Google Scholar 

27. Philip, A.A., Taofiki, A.A., Bidemi, A.A.: Artificial neural network model for forecasting foreign exchange rate. World Comput. Sci. Inf. Technol. J. (WCSIT) 1 (3) 110–118 (2011)

    Google Scholar 

28. Pujol, J.C.F., Poli, R.: Evolving the topology and the weights of neural networks using a dual representation. Appl. Intell. 8(1), 73–84 (1998)

    Article  Google Scholar 

29. Refenes, A.N., Azema-Barac, M., Chen, L., Karoussos, S.: Currency exchange rate prediction and neural network design strategies. Neural Comput. Appl. 1(1), 46–58 (1993)

    Article  Google Scholar 

30. Rehman, M., Ali, J., Khan, G.M., Mahmud, S.A.: Extracting trends ensembles in solar irradiance for green energy generation using neuro-evolution. In: IFIP International Conference on Artificial Intelligence Applications and Innovations, pp. 456–465. Springer (2014)

    Google Scholar 

31. Rehman, M., Khan, G.M., Mahmud, S.A.: Foreign currency exchange rates prediction using cgp and recurrent neural network. IERI Procedia 10, 239–244 (2014)

    Article  Google Scholar 

32. Sadeghi, B.: A bp-neural network predictor model for plastic injection molding process. J. Mater. Process. Technol. 103(3), 411–416 (2000)

    Article  MathSciNet  Google Scholar 

33. Sarangi, P.P., Sahu, A., Panda, M.: A hybrid differential evolution and back-propagation algorithm for feedforward neural network training. Int. J. Comput. Appl. 84(14) (2013)

    Google Scholar 

34. Singh, D., Singh, S.: A self-selecting neural network for short-term load forecasting. Electr. Power Compon. Syst. 29(2), 117–130 (2001)

    Article  Google Scholar 

35. Stanley, K.O., Miikkulainen, R.: Efficient reinforcement learning through evolving neural network topologies. In: Proceedings of the 4th Annual Conference on Genetic and Evolutionary Computation, pp. 569–577. Morgan Kaufmann Publishers Inc. (2002)

    Google Scholar 

36. Wieland, A.P.: Evolving neural network controllers for unstable systems. In: IJCNN-91-Seattle International Joint Conference on Neural Networks, 1991, vol. 2, pp. 667–673. IEEE (1991)

    Google Scholar 

Download references