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ECoS Literature

Algoroithms Applications Comparisons
This part of the site lists all of the ECoS-related literature that I am aware of. It is organised into three sections: Algorithms, which are papers that primarily deal with ECoS algorithms; Applications, which are papers that primarily deal with applying ECoS algorithms to solve problems; and Comparisons, which are papers that compare the performance ECoS algorithms with other algorithms. Links to online versions of papers are being included on an on-going basis, as are new ECoS-related publications.  If you are aware of any publications or links that you think I should include please let me know at the following address: papersATecos.watts.net.nz.

BibTeX source files for each of these pages are available: Algorithms.bib, Applications.bib, Comparisons.bib. They are also available in RIS format: Algorithms.ris, Applications.ris, Comparisons.ris.

Overview Publications

Kasabov, N.K. “Evolving Connectionist Systems: Methods and Applications in Bioinformatics, Brain Study and Intelligent Machines”.Springer, 2003.

Watts, M.J. A decade of Kasabov’s Evolving Connectionist Systems: A Review. IEEE Transactions on Systems, Man and Cybernetics Part C - Applications and Reviews (2009)  39(3) 253-269 (PDF reprint).

Recent Publications

Al-Khowarizmi, A.-K.; Nasution, I. R.; Lubis, M. & Lubis, A. R. The effect of a SECoS in crude palm oil forecasting to improve business intelligence. Bulletin of Electrical Engineering and Informatics, 2020, 9.

Malcangi, M. & Malcangi, M. Bioinspired Early Prediction of Earthquakes Inferred by an Evolving Fuzzy Neural Network Paradigm. International Conference on Engineering Applications of Neural Networks, 2019, 361-367.

Noori, A.; Amphawan, A.; Ghazi, A. & Ghazi, S. A. Dynamic evolving neural fuzzy inference system equalization scheme in mode division multiplexer for optical fiber transmission. Bulletin of Electrical Engineering and Informatics, 2019, 8, 127-135.

Jiang, H.; Kwong, C.; Kremer, G. O. & Park, W.-Y. Dynamic modelling of customer preferences for product design using DENFIS and opinion mining''. Advanced Engineering Informatics, Elsevier, 2019, 42, 100969 .
Maintained by Dr Michael J. Watts