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Balraj, E.
- Rule Based Interaction Technique with Ant Colony Optimization Algorithm
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Authors
Affiliations
1 Computer Science and Engineering, M. Kumarasamy College of Engineering, Karur, IN
1 Computer Science and Engineering, M. Kumarasamy College of Engineering, Karur, IN
Source
International Journal of Emerging Trends in Science & Technology, Vol 1, No 2 (2015), Pagination: 27-34Abstract
Ant Colony Optimization (ACO) algorithms have been successfully applied to discover a list of classification rules. In general, these algorithms follow a sequential covering strategy, where a single rule is discovered at each iteration of the algorithm in order to build a list of rules. The problem in this case is not coping with the problem of rule interaction, i.e., the result of a rule affects the rules that can be discovered subsequently since the search space is modified due to the removal of examples covered by previous rules. Here, a new sequential covering strategy cAnt-MinerPB for ACO classification algorithm is proposed to mitigate the problem of rule interaction, where the order of the rules is implicitly encoded as pheromone values and the search is guided by the quality of a candidate list of rules. cAnt-MinerPB algorithm, which is the extended version of the Ant-Miner algorithm that handles continuous attributes on-the-fly during the rule construction process. The experiments are conducted using 18 publicly available data sets and results shows that the predictive accuracy obtained by a new ACO classification algorithm implementing the cAnt- MinerPB, statistically significantly higher than the predictive accuracy of state-of-the-art rule induction classification algorithms.Keywords
Datamining, Ant Colony Optimization, Classification, Rule Induction, Sequential Covering.- A Prototype based Multibiometric Authentication System for Smart House Door System using Arduino
Abstract Views :219 |
PDF Views:0
Authors
E. Balraj
1,
T. Abirami
2
Affiliations
1 Assistant Professor, Department of Information Technology, M.Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
2 Associate Professor, Department of Information Technology, Kongu Engineering College, Perundurai, Tamil Nadu, IN
1 Assistant Professor, Department of Information Technology, M.Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
2 Associate Professor, Department of Information Technology, Kongu Engineering College, Perundurai, Tamil Nadu, IN
Source
International Journal of Emerging Trends in Science & Technology, Vol 7, No 2 (2021), Pagination: 27-31Abstract
In recent days, Biometrics becomes essential part of our life. Because it provides more security than other properties. People can apply biometric authentication in any field such as online exam, door access control, banking, identifying people, intelligent agent. The intelligent house becomes standard for the past few years. It will give a security and cozy to the house owner. However, the protection is incredibly necessary, it should be determining the house owner accurately and forestall the system to create an error for identification. Our proposed frameworks use finger print, facial recognition to make a system just like the security to create a identity and observation the protection of buildingKeywords
Finger Print, Face Recognition, Smart Home Door, Multi Biometric, Intelligent HouseReferences
- . Ishengoma, Fredrick. (2014). AUTHENTICATION system for smart homes based on ARM7TDMI-S and IRIS-Fingerprint Recognition Technologies. CIIT International Journal of Programmable Device Circuits and Systems. 6. 162 – 167. 10.5815/IJIEEB.2014.06.08.
- . D. Bregman, “Smart Home intelligence – The eHome that Learns”, International Journal of Smart Home, Vol.4, No.4, 2010.
- . Vijay Srinivasan, John Stankovic, Kamin Whitehouse, “Using Height Sensors for Biometric Identification in Multi-Resident Homes”, Pervasive Computing, 8th International Conference, Pervasive 2010, pp. 337-354, Helsinki, Finland, 2010.
- . Rishi, Kamer & Yildirim Yayilgan, Sule. (2013). “Multimodal Biometric Authentication Using Fingerprint and Iris Recognition in Identity Management”. 334-341. 10.1109/IIH-MSP.2013.91.
- . M. M. Monwar and M. L. Gavrilova, ``Multimodal biometric system using rank-level fusion approach, ''IEEE Trans. Syst., Man, Cybern. B, Cybern., vol. 39, no. 4, pp. 867878, Aug. 2009.
- . P. Paul, M. L. Gavrilova, and R. Alhajj, “Decision fusion for multimodal biometrics using social network analysis,'' IEEE Trans. Syst., Man, Cybern., Syst., vol. 44, no. 11, pp. 15221533, Nov. 2014.
- . Funsho Tosin Enahoro, Sudhasini Raman Kutty,” Biometrics Based Security System Using Arduino” International Journal of Information System and Engineering,Vol. 8 (No 1.), April, 2020. pp30-51.
- . Magdin, Martin & Koprda, Stefan & Ľubor, Ferenczy. (2018). Biometrics Authentication of Fingerprint with Using Fingerprint Reader and Microcontroller Arduino. Telkomnika (Telecommunication Computing Electronics and Control). 16. 755-765. 10.12928/TELKOMNIKA.v16i2.7572.
- . Meenakshi, N & Monish, M & Dikshit, K & Bharath, S. (2019). Arduino Based Smart Fingerprint Authentication System. 1-7. 10.1109/ICIICT1.2019.8741459.
- . Mahesh Bhanushali,, Manish Bhanushali,, Darpan Bhanushali, Archana Chaugule,Manish Bhelande, ” Biometric Authentication System using Arduino” Journal of Advancement in Parallel Computing Volume 3 Issue 3,PP1-5.
- . E.Balraj, T.Dinesh, S.Deepan, N.Nattudurai, “CNN Based Multimodel Biometric Authentication System Using Face And Fingerprint”, International Journal of Future Generation Communication and Networking, Volume 13,Issue 02,PP 1536 – 1539.
- . Dr.T.Abirami E.Balraj, “A Multibiometric Authentication System Using Fusion Level Techniques” , International Journal Of Scientific & Technology, Volume 09,Issue 01, PP - 3332-3335.