Skip to main content

MOBI-CLASS: A Fuzzy Knowledge-Based System for Mobile Handset Classification

  • Conference paper
  • First Online:
Soft Computing for Problem Solving

Abstract

Fuzzy logic is a technique that provides a mathematical framework to deal with imprecise and uncertain information existing in the real-world decision-making systems. The objective is to integrate linguistic computation in decision making. Several rule-based systems are being developed using the subjective knowledge in the form of fuzzy if-then rules which are also known as ‘Fuzzy Knowledge Base Systems (FKBS)’. In this paper, a new FKBS titled MOBI-CLASS is proposed and implemented using open-access software Guaje. The interpretability and accuracy parameters are studied.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Zadeh, L.A.: Fuzzy Sets. Inf. Control 8, 338–353 (1965)

    Article  Google Scholar 

  2. Mendel, J.M.: Uncertain Rule Based Fuzzy Logic System: Introduction and New Directions. Prentice Hall (2001)

    Google Scholar 

  3. Klir, G.J., Yuan, B., Fuzzy Sets and Fuzzy Logic: Theory and Applications. Prentice Hall (1995)

    Google Scholar 

  4. Magdalena, L.: Fuzzy Rule Based Systems. Springer Handbook of Computational Intelligence, pp. 203–218 (2015)

    Chapter  Google Scholar 

  5. Chang, P.-C., Liu, C.-H.: ATSK fuzzy rule based system for stock price prediction. Expert Syst. Appl. 34(1), 135–144 (2008)

    Article  Google Scholar 

  6. Dange, P.S., Lad, R.K.: A fuzzy rule based system for an environmental acceptability of sewage treatment plant. KSCE J. Civil Eng. 21(7), 2590–2595 (2017)

    Article  Google Scholar 

  7. Shukla, P.K., Tripathi, S.P.: New approach for tuning interval type-2 fuzzy knowledge based using genetic algorithm. J. Uncertain. Anal. Appl. 2, 1–15 (2014)

    Article  Google Scholar 

  8. Nilashi, M., Ibrahim, O., Ahmadi, H., Shahmoradi, L.: A knowledge based system for breast cancer classification using fuzzy logic method. Telem. Inf. 34(4), 133–144 (2017)

    Article  Google Scholar 

  9. Mamdani, E.H., Assilian, S.: An experiment in linguistic synthesis with fuzzy logic controllers. Int. J. Men-Mach. Stud. 7(1), 1–13 (1975)

    Article  Google Scholar 

  10. Takagi, T., Sugeno, M.: Fuzzy identification of systems and its application to modeling and control. IEEE Trans. Syst. Man Cybern. 15(1), 116–132 (1985)

    Article  Google Scholar 

  11. Shukla, P.K., Tripathi, S.P.: A survey on interpretability-accuracy (I-A) trade-off in evolutionary fuzzy systems. In: IEEE International Conference on Genetic and Evolutionary Computation (ICGEC 2011), Japan, 29 August–01 September 2011

    Google Scholar 

  12. Shukla, P.K., Tripathi, S.P.: On the design of interpretable evolutionary fuzzy system (1-EFS) with improved accuracy. In: International Conference on Computing Science, L. P. University, India (2012)

    Google Scholar 

  13. Shukla, P.K., Tripathi, S.P.: Interpretability issues evolutionary multi objective fuzzy knowledge based system. In: 7th International Conference on Bio-Inspired Computing: Theories and Applications (BIC-7A2012), ABV-IIIT, Gwalior, India, 14–16 December 2012

    Google Scholar 

  14. Cassils, J., Cordon, O., Herrera F., Magdalena, L.: Accuracy Improvement in Linguistic Fuzzy Modeling. Springer, Newyork, NY, USA (2013)

    Google Scholar 

  15. Shukla, P.K., Tripathi, S.P.: A review on the interpretability-accuracy trade-off in evolutionary multi-objective fuzzy systems (EMOFS). Information 3, 256–277 (2012)

    Article  Google Scholar 

  16. Alonso, J.M., Magdalena, L., Generating understandable and accurate fuzzy rule based system in a Java environment. In: 9th International Workshop on Fuzzy Logic and Applications, pp. 212–219, Trani, Italy 29–31 August 2011

    Google Scholar 

  17. Alonso, J.M., Magdalena, L.: HILK++: an interpretability guided fuzzy modeling methodology for learning readable and comprehensible fuzzy rule base classifiers. Soft. Comput. 15(10), 1959–1980 (2011)

    Article  Google Scholar 

  18. Aarabi, R., Rezai, F., Aghakhani, Y.: A fuzzy rule based system for epileptic seizure detection in intra-cranial EEG. Clin. Neurophysiol. 120(9), 1648–1657 (2009)

    Article  Google Scholar 

  19. Bui, T.D., Heylen, D., Poel, M., Nijhot, A.: Generation of facial expression from emotions using a fuzzy rule based system. In: Australian Joint Conference on Artificial Intelligence. Lecture Notes in Computer Science (LNCS), vol. 2256, pp. 83–94 (2002)

    Chapter  Google Scholar 

  20. Shreshtha, B.P., Duckstein, L., Stakhiv, E.Z.: Fuzzy rule based modeling of reservoir operation. J. Water Resour. Plan. Manag. 122(4), 212–218 (1996)

    Google Scholar 

  21. Rashmi Devi, T.V., Eldho, T.I., Jana, R.: A GIS integrated fuzzy rule based inference system for land suitability evaluation in agriculture watersheds. Agric. Syst. 101(1–2), 101–109 (2009)

    Article  Google Scholar 

  22. Adrinoenssens, V., De Baets, B., Goethals, P.L.M., De Pauw, N.: Fuzzy rule based model for decision support in eco system management. Sci. Total Environ. 319(1–3), 1–12 (2004)

    Article  Google Scholar 

  23. Cordon, O., Herrera, F., Hoffmann, F., Magdalena, L.: Genetic Fuzz Systems: Evolutionary Tuning and Learning of Fuzzy Knowledge Based. World Scientific (2001)

    Google Scholar 

  24. Antonelli, M., Bernardo, D., Hagras, M., Marcelloni, F.: Multiobjective optimization of type-2 fuzzy rule based systems for financial data classification. IEEE Trans. Fuzzy Syst. 25(2), 249–264 (2017)

    Article  Google Scholar 

  25. Fernandez, A., del Rio, S., Bawakid, A., Herrera, F.: Fuzzy rule based classification systems for big data with MapReduce: granularity analysis. Adv. Data Anal. Classif. 11(4), 711–730 (2017)

    Article  MathSciNet  Google Scholar 

  26. Shukla, P.K., Tripathi, S.P.: Handling high dimensionality and interpretability accuracy trade-off issues in evolutionary multi-objective fuzzy classifies. Int. J. Sci. Eng. Res. 5(6), 665–671 (2014)

    Google Scholar 

  27. Shukla, P.K., Tripathi, S.P.: Interpretability and accuracy issues in evolutionary multi-objective fuzzy classifies. Int. J. Soft Comput. Netw. 1(1), 55–69 (2016)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Prabhash Chandra .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chandra, P., Agarwal, D., Shukla, P.K. (2019). MOBI-CLASS: A Fuzzy Knowledge-Based System for Mobile Handset Classification. In: Bansal, J., Das, K., Nagar, A., Deep, K., Ojha, A. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 817. Springer, Singapore. https://doi.org/10.1007/978-981-13-1595-4_77

Download citation

Publish with us

Policies and ethics