2022

  • Doğru, F. Z., & Arslan, O. (2022). Multivariate skew Laplace normal distribution for modeling skewness and heavy-tailedness in multivariate data sets. Statistics and Its Interface, 15(4), 475-485.
  • Bas, E. 2022,  Robust fuzzy regression functions approaches, Information Sciences, 613, pp. 419–434.
  • Bas, E., Egrioglu, E., Karahasan, O. 2022, A Pi-Sigma artificial neural network based on sine cosine optimization algorithm, Granular Computing, 2022, 7(4), pp. 813–820.
  • Bas, E., Egrioglu, E., Kolemen, E. 2022, A novel intuitionistic fuzzy time series method based on bootstrapped combined pi-sigma artificial neural network, Engineering Applications of Artificial Intelligence, 114, 105030.
  • Egrioglu, E., Baş, E., Chen, M.-Y., 2022, Recurrent dendritic neuron model artificial neural network for time series forecasting, Information Sciences, 2022, 607, pp. 572–584.
  • Bas, E., Egrioglu, E. 2022, A fuzzy regression functions approach based on Gustafson-Kessel clustering algorithm, Information Sciences, 2022, 592, pp. 206–214.
  • Yılmaz, O., Bas, E., Egrioglu, E., 2022, The Training of Pi-Sigma Artificial Neural Networks with Differential Evolution Algorithm for Forecasting, Computational Economics, 59(4), pp. 1699–1711.
  • Chen, M.-Y., Sangaiah, A.K., Chen, T.-H., Lughofer, E.D., Egrioglu, E. 2022Deep Learning for Financial Engineering, Computational Economics, 2022, 59(4), pp. 1277–1281.
  • Bas, E., Egrioglu, E., Kolemen, E. 2022, Training simple recurrent deep artificial neural network for forecasting using particle swarm optimization, Granular Computing, 2022, 7(2), pp. 411–420.
  • Eğrioğlu, E., Fildes, R. 2022, A New Bootstrapped Hybrid Artificial Neural Network Approach for Time Series Forecasting, Computational Economics, 59(4), pp. 1355–1383.
  • Chen, M.-Y., Liao, C.-H., Lughofer, E.D., Egrioglu, E. 2022, Editorial, Library Hi Tech, 2022, 40(1), pp. 1–2.
  • Yolcu, O.C., Egrioglu, E., Bas, E., Yolcu, U. 2022, Multivariate intuitionistic fuzzy inference system for stock market prediction: The cases of Istanbul and Taiwan, Applied Soft Computing, 116, 108363.
  • Egrioglu, E., Bas, E., A new automatic forecasting method based on a new input significancy test of a single multiplicative neuron model artificial neural network, Network: Computation in Neural Systems, 33(1-2), pp. 1–16.
  • Chen, M.-Y., Lughofer, E.D., Egrioglu, E., 2022, Deep learning and intelligent system towards smart manufacturing, Enterprise Information Systems, 2022, 16(2), pp. 189–192.
  • Egrioglu, E., Fildes, R., Baş, E. 2022, Recurrent fuzzy time series functions approaches for forecasting, Granular Computing, 7(1), pp. 163–170.