### Novel Hybrid Rule Network Based on TS Fuzzy Rules

#### Abstract

#### Keywords

#### Full Text:

PDF#### References

ANGELOV P.P., ZHOU X. Evolving Fuzzy-Rule-Based Classifiers From Data

Streams. IEEE Transactions on Fuzzy Systems. 2008, 16(6), pp. 1462-1475, doi: 10.1109/TFUZZ.2008.925904.

AZEEM M.F., HANMANDLU M., AHMAD N. Structure identification of generalized adaptive neuro-fuzzy inference systems. IEEE Transactions on Fuzzy Systems. 2003, 11(5), pp. 666-681, doi: 10.1109/TFUZZ.2003.817857.

BUCKLEY J.J. Sugeno type controllers are universal controllers. Fuzzy Sets and Systems. 1993, 53, pp. 299-303, doi: 10.1016/0165-0114(93)90401-3.

CARUANA R.A., DAVID SCHAFFER J., ESHELMAN L.J. Using multiple representations to improve inductive bias: gray and binary coding for genetic algorithms. In: A.M. SEGRE, ed. Proceedings of the Sixth International Workshop on Machine Learning, San Francisco, USA. CA: Morgan Kaufmann, 1989, pp. 375-378, doi: 10.1016/B978-1-55860-036-2.50095-3.

CHIU S.L. Fuzzy model identification based on cluster estimation. Intelligent and Fuzzy Systems. 1994, 2, pp. 267-278, doi: 10.3233/IFS-1994-2306.

CHOI J.-N., OH S.-K., PEDRYCZ W. Identification of fuzzy models using a successive tuning method with a variant identification ratio. Fuzzy Sets and Systems. 2008, 159(21), pp. 2873-2889, doi: 10.1016/j.fss.2007.12.031.

DORIGO M., BIRATTARI M., STUTZLE T. Ant colony optimization. IEEE Computational Intelligence Magazine. 2006,1(4), pp. 28-39, doi: 10.1109/MCI.2006.329691.

DUAN J.-C., CHUNG F.-L. Multilevel fuzzy relational systems: structure and identification. Soft Computing. 2002, 6, pp. 71-86, doi: 10.1007/s005000100144.

EBERHART R.C., SHI Y. Evolutionary computation implementations. In: R.C. EBERHART AND Y. SHI, eds. Computational Intelligence. Burlington: Morgan Kaufmann, 2007, pp. 95-143, doi: 10.1016/B978-155860759-0/50004-4.

GAO Y., ER M.J. NARMAX time series model prediction: feedforward and recurrent fuzzy neural network approaches. Fuzzy Sets and Systems. 2005, 150(2), pp. 331-350, doi: 10.1016/j.fss.2004.09.015.

GOU B., HUANG X. The methods of multiclass classifiers based on SVM. Journal of Data Acquisition & Processing. 2006, 21(3), pp. 334-339.

HOLLAND J.H. Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence. Oxford, England: U Michigan Press, 1975.

JANG J.-S.R. ANFIS: adaptive-network-based fuzzy inference system. IEEE Transactions on Systems, Man, and Cybernetics. 1993, 23(3), pp. 665-685, doi: 10.1109/21.256541.

JI R., YANG Y., ZHANG W. Incremental smooth support vector regression

for Takagi-Sugeno fuzzy modeling. Neurocomputing. 2014, 123, pp. 281-291, doi: 10.1016/j.neucom.2013.07.017.

JUANG C.-F., LIN C.-T. An online self-constructing neural fuzzy inference network and its applications. IEEE Transactions on Fuzzy Systems. 1998, 6(1), pp. 12-32, doi: 10.1109/91.660805.

KALHOR A., ARAABI B.N., LUCAS C. A new systematic design for Habitually Linear Evolving TS Fuzzy Model. Expert Systems with Applications. 2012, 39(2), pp. 1725-1736, doi: 10.1016/j.eswa.2011.08.085.

KENNEDY J., EBERHART R.C., SHI Y. The Particle Swarm. In: J. KENNEDY AND R.C.E. SHI, eds. Swarm Intelligence. San Francisco: Morgan Kaufmann, 2001, pp. 287-325, doi: 10.1016/B978-155860595-4/50007-3.

LI J., ZHENG Y., SHEN S. A classification rule acquisition and reasoning algorithm based on the fuzzy regional distribution. Chinese J. Computers. 2008, 31(6), pp. 934-941.

LIN L., DING G. A Multiple Classification Method Based on the Cloud Model. Neural Network World. 2010, 20(5), pp. 651-666.

MAGUIRE L.P., et al. Predicting a chaotic time series using a fuzzy neural network. Information Sciences. 1998, 112, pp. 125-136, doi: 10.1016/S0020-0255(98)10026-9.

MAMDANI E.H., ASSILIAN S. An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies. 1975, 7(1), pp. 1-15, doi: 10.1016/S0020-7373(75)80002-2.

RAMANAN A., SUPPHARANGSAN S., NIRANJAN M. Unbalanced Decision Trees for Multi-class Classification. Second International Conference on Industrial and Information Systems (ICIIS 2007), Penadeniya, Sri Lanka, Ceylon. IEEE, 2007, pp. 291-294, doi: 10.1109/ICIINFS.2007.4579190.

SETNES M., ROUBOS H. GA-fuzzy modeling and classification: Complexity and Performance. IEEE Transactions on Fuzzy Systems. 2000, 8(5), pp. 509-522, doi: 10.1109/91.873575.

TAKAGI T., SUGENO M. Fuzzy Identification of Systems and Its Applications to Modeling and Control. IEEE Transactions on Systems, Man, and Cybernetics. 1985, 15, pp. 116-132, doi: 10.1109/TSMC.1985.6313399.

WANG L., LANGARI R. Complex systems modeling via fuzzy logic. IEEE Transactions on Systems, Man, and Cybernetics, part B-cybernetics. 1996, 26(1), pp. 100-106, doi: 10.1109/3477.484441.

WANG L.X. Adaptive Fuzzy Systems and Control: Design Stability Analysis. Upper Saddle River, NJ, USA: Prentice Hall Professional Technical Reference, 1994.

WANG N., YANG Y. A fuzzy modeling method via Enhanced Objective Cluster Analysis for designing TSK model. Expert Systems with Applications. 2009, 36(10), pp. 12375-12382, doi: 10.1016/j.eswa.2009.04.048.

ZHONG S., LEI D., DING G. Convolution Sum Discrete Process Neural Network and Its Application in Aeroengine Exhausted Gas Temperature Prediction. Acta Aeronautica et Astronautica Sinica. 2012, 33(3), pp. 438-445.

ZHU B., et al. A GMDH-based fuzzy modeling approach for constructing TS model. Fuzzy Sets and Systems. 2012, 189(1), pp. 19-29, doi: 10.1016/j.fss.2011.08.004.

DOI: http://dx.doi.org/10.14311/NNW.2015.25.005

### Refbacks

- There are currently no refbacks.

Should you encounter an error (non-functional link, missing or misleading information, application crash), please let us know at nnw.ojs@fd.cvut.cz. **Please, do not use the above address for non-OJS-related queries (manuscript status, etc.).** For your convenience we maintain a list of frequently asked questions here. General queries to items not covered by this FAQ shall be directed to the journal editoral office at nnw@fd.cvut.cz.