A neuro-fuzzy approach for sensor network data cleaning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4694 LNAI, Issue PART 3, 2007, Pages 140-147

  Petrosino, Alfredo ^a   Staiano, Antonino ^a  

^a UNIVERSITY OF NAPLES PARTHENOPE   (Italy)

Author keywords

Data cleaning; Neuro fuzzy; Regression; Sensor networs

Indexed keywords

DATA ACQUISITION; SENSOR NETWORKS;

DATA CLEANING; NEURO-FUZZY REGRESSION; SENSOR DATA;

FUZZY NEURAL NETWORKS;

EID: 38149034383     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74829-8_18     Document Type: Conference Paper

References (13)

1. Bishop, C.M.: Pattern Recognition and Machine Learning. Springer, Heidelberg (2006)
2. Bychkovskiy, V., Megerian, S., Estrin, D., Potkonjak, M.A.: A Collaborative Approach to in-place Sensor Calibration. In: Zhao, F., Guibas, L.J. (eds.) IPSN 2003. LNCS, vol. 2634, Springer, Heidelberg (2003)
3. Elnahwary, E., Nath, B.: Cleaning and Querying Noisy Sensors. IN WSNA'03. In: Proceedings of the 2nd ACM International Conference on Wireless Sensors and Applications, pp. 78-87. ACM Press, New York (2003)
4. Hand, D.J., Mannila, H., Smyth, P.: Principles of Data Mining. MIT Press, Cambridge (2001)
5. Nauck, D., Kruse, R.: Neuro-Fuzzy Models in Fuzzy Rule Generation. In: Bezdek, J.C., Dubois, D., Prade, H. (eds.) Fuzzy Sets in Approximate Reasoning and Information Systems, Kluwer, Dordrecht (1999)
6. Shawe-Taylor, J., Cristianini, N.: Kernel Methods for Pattern Analysis. Cambridge University Press, Cambridge (2004)
7. Tan, Y.L., Sehgal, V., Shahri, H.H.: SensoClean: Handling Noisy and Incomplete Data in Sensor Networks using Modeling. Technical Report, University of Maryland (2005)
8. Intel Berkeley Laboratory Data, http://berkeley.intel-research.net/ labdata/
9. Pedrycz, W., Kandel, A., Zhang, Y.Q.: Neurofuzzy Systems. In: Nguyen, H.T., Sugeno, M. (eds.) Fuzzy Systems Modeling and Control. The Handbook on Fuzzy Sets, Kluwer Academic Publishers, Dordrecht (1998)
10. Spanos, D.P., Olfati-Saber, R., Murray, R.M.: Approximate Distributed Kalman Filtering in Sensor Networks with Quantifiable Performance. In: Fourth International Symposium on Information Processing in Sensor Networks, pp. 133-139 (2005)
11. Galhardas, H., et al.: Declarative data cleaning: Language, model, and algorithms. In: VLDB, pp. 371-380 (2001)
12. Raman, V., Hellerstein, J.M.: Potter's Wheel: An Interactive Data Cleaning System. The VLDB Journal, 381-390 (2001)
13. Jang, R., ANFIS,: Adaptive-Network-based Fuzzy Inference Systems. IEEE Trans. on Systems, Man, and Cybernetics 23, 665-685 (1993)