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Fuzzy Logic Modeling for Prediction of the Nuclear Tracks

Year 2018, Volume: 1 Issue: 1, 33 - 40, 01.08.2018

Abstract

In this paper, we have applied Fuzzy Logic Modeling (FLM) on nuclear track detector (CR-39) data. These data were obtained practically to find a number of effects tracks of alpha in nuclear track detector (CR-39) for different temperatures and different concentrations at different etchant times. We applied Fuzzy Logic Modeling on this physical data to make it continuous and that shows there is a match between original data and fuzzy and  then we found optimal triple  (temperature, concentration, etchant time) to get a clearer picture of the number of this tracks.

References

  • [1] R.L. Fleischer, P.B. Price and R.M. Walker, Nuclear Tracks in Solids 1975.[2] R.K. Jain, A. Kumar, R.N. Chakraborty and B.K. Nayak, Irradiation Etect of 60Co Gamma Rays onBulk Etch Rate, Track Etch Rate and Activation Energy of CR-39 Solid State Nuclear Track Detector,Proceedings of the DAE Symposium on Nuclear Physics. 59 (2014), 432-433.[3] A.F. Hafez and G. Somogyi, Determination of Radon and Thoron Permeability through Some Plastics byTrack Technique, International Journal of Radiation Applications and Instrumentation. 12 (1986), 697{700.[4] F. Leonardi, M. Caresana, R. Mishra, S. Tonnarini, R. Trevisi and M. Veschetti, An Extended Study of theEtching Characteristics of CR-39 Detectors, Radiation Measurements. 44 (2009), 787-790.[5] V. Chavan, P.C. Kalsi and A. Mhatre The Etching, Optical and Thermal Response of a Newly DevelopedNuclear Track Detector Called NADAC-ADC Copolymer to Gamma-Irradiation, Journal of Radioanalyticaland Nuclear Chemistry. 87 (2011), 273-276.[6] S. B. Al-deen and A. A. Ibrahem nding of optimum Etching conditions for CR-39 nuclear track detector,Kirkuk journal F06 pus science. 3 (2015).[7] L. A. Zadeh, Fuzzy sets, Information and Control. 8 (1965), 338{353.[8] A. Homaifar and E. Cormick, Simultaneous design of membership functions and rule sets for fuzzy con-trollers using genetic algorithms, IEEE Trans. Fuzzy Systems. 3 (1995), 129-139.[9] J. M. Mendel, Fuzzy logic systems for engineering, A tutorial In Proceedings of the IEEE. 83 (1995),345-377.[10] Y. Y. Yao, Two views of the theory of rough sets in nite universes., International Journal of ApproximationReasoning. 15 ( 1996), 291-317.[11] Y. Y. Yao, A comparative study of fuzzy sets and rough sets, Information Sciences. 109 (1998), 227-242.[12] G. Hayward and V. Davidson, Fuzzy logic applications, Analyst. 128 (2003), 1304-1306.[13] W. Wang and S. M. Bridges, Genetic algorithm optimization of membership functions for mining fuzzyassociation rules, Fuzzy Theory and Technology Conference (2000).FUZZY LOGIC MODELING FOR PREDICTION OF THE NUCLEAR TRACKS 9[14] A. Abraham, Adaptation of fuzzy inference system using neural learning. Fuzzy System Engineering, Theoryand Practice N. Nedjah. 3 (2005), 53-83.[15] M. Z. Sha q, M. Farooq and S. A. Khayam, Neural Networks and Adaptive Neuro Fuzzy Inference Systemsfor Portscan Detection, EvoWorkshops, LNCS. 4974 (2008), 52-61.[16] F. Zhiyi, A fuzzy inference system for synthetic evaluation of compost maturity and stability, Masters ofEngineering thesis, University of Regina, Saskatchewan (2004).[17] S. Kumar, N. Bhatia and N. Kapoor, Fuzzy logic based tool for loan risk prediction, In Proceedings ofInternational Conference on Communication and Computing Technologies. (2011), 180-183.[18] S. Kumar, N. Bhatia and N. Kapoor, Software risk analysis using fuzzy logic, International Journal ofComputer Information Systems. 2 (2011), 7-12.[19] S. Gursharan, N. Bhatia and S. Sawtantar, Fuzzy logic based cricket player performance evaluator, IJCASpecial Issue on "Arti cial Intelligence Techniques - Novel Approaches and Practical Applications" AIT.(2011).[20] M. J. Smithson, G. Oden, Fuzzy set theory and application in psychology, International Handbook of FuzzySets and Possibility Theory. 5 (1999) 557-585.[21] J. Russell and M. Bullock, Fuzzy Concepts and the perception of emotion in facial expression, Social-Cognition. 4 (1986), 309-341.[22] V. Dimitrov, Use of Fuzzy Logic when dealing with Social Complexity, Complexity International. 04 (1997)1-10.[23] T. Yahashita, On a support system for human decision making by the combination of fuzzy reasoning andfuzzy structural modeling, Fuzzy Set and System. 8 (1998), 257-263.[24] T. Luis, A Fuzzy based advisor for election and creation of political communities, Information SystemResearch Group. 3 (2011) 180-185.
Year 2018, Volume: 1 Issue: 1, 33 - 40, 01.08.2018

Abstract

References

  • [1] R.L. Fleischer, P.B. Price and R.M. Walker, Nuclear Tracks in Solids 1975.[2] R.K. Jain, A. Kumar, R.N. Chakraborty and B.K. Nayak, Irradiation Etect of 60Co Gamma Rays onBulk Etch Rate, Track Etch Rate and Activation Energy of CR-39 Solid State Nuclear Track Detector,Proceedings of the DAE Symposium on Nuclear Physics. 59 (2014), 432-433.[3] A.F. Hafez and G. Somogyi, Determination of Radon and Thoron Permeability through Some Plastics byTrack Technique, International Journal of Radiation Applications and Instrumentation. 12 (1986), 697{700.[4] F. Leonardi, M. Caresana, R. Mishra, S. Tonnarini, R. Trevisi and M. Veschetti, An Extended Study of theEtching Characteristics of CR-39 Detectors, Radiation Measurements. 44 (2009), 787-790.[5] V. Chavan, P.C. Kalsi and A. Mhatre The Etching, Optical and Thermal Response of a Newly DevelopedNuclear Track Detector Called NADAC-ADC Copolymer to Gamma-Irradiation, Journal of Radioanalyticaland Nuclear Chemistry. 87 (2011), 273-276.[6] S. B. Al-deen and A. A. Ibrahem nding of optimum Etching conditions for CR-39 nuclear track detector,Kirkuk journal F06 pus science. 3 (2015).[7] L. A. Zadeh, Fuzzy sets, Information and Control. 8 (1965), 338{353.[8] A. Homaifar and E. Cormick, Simultaneous design of membership functions and rule sets for fuzzy con-trollers using genetic algorithms, IEEE Trans. Fuzzy Systems. 3 (1995), 129-139.[9] J. M. Mendel, Fuzzy logic systems for engineering, A tutorial In Proceedings of the IEEE. 83 (1995),345-377.[10] Y. Y. Yao, Two views of the theory of rough sets in nite universes., International Journal of ApproximationReasoning. 15 ( 1996), 291-317.[11] Y. Y. Yao, A comparative study of fuzzy sets and rough sets, Information Sciences. 109 (1998), 227-242.[12] G. Hayward and V. Davidson, Fuzzy logic applications, Analyst. 128 (2003), 1304-1306.[13] W. Wang and S. M. Bridges, Genetic algorithm optimization of membership functions for mining fuzzyassociation rules, Fuzzy Theory and Technology Conference (2000).FUZZY LOGIC MODELING FOR PREDICTION OF THE NUCLEAR TRACKS 9[14] A. Abraham, Adaptation of fuzzy inference system using neural learning. Fuzzy System Engineering, Theoryand Practice N. Nedjah. 3 (2005), 53-83.[15] M. Z. Sha q, M. Farooq and S. A. Khayam, Neural Networks and Adaptive Neuro Fuzzy Inference Systemsfor Portscan Detection, EvoWorkshops, LNCS. 4974 (2008), 52-61.[16] F. Zhiyi, A fuzzy inference system for synthetic evaluation of compost maturity and stability, Masters ofEngineering thesis, University of Regina, Saskatchewan (2004).[17] S. Kumar, N. Bhatia and N. Kapoor, Fuzzy logic based tool for loan risk prediction, In Proceedings ofInternational Conference on Communication and Computing Technologies. (2011), 180-183.[18] S. Kumar, N. Bhatia and N. Kapoor, Software risk analysis using fuzzy logic, International Journal ofComputer Information Systems. 2 (2011), 7-12.[19] S. Gursharan, N. Bhatia and S. Sawtantar, Fuzzy logic based cricket player performance evaluator, IJCASpecial Issue on "Arti cial Intelligence Techniques - Novel Approaches and Practical Applications" AIT.(2011).[20] M. J. Smithson, G. Oden, Fuzzy set theory and application in psychology, International Handbook of FuzzySets and Possibility Theory. 5 (1999) 557-585.[21] J. Russell and M. Bullock, Fuzzy Concepts and the perception of emotion in facial expression, Social-Cognition. 4 (1986), 309-341.[22] V. Dimitrov, Use of Fuzzy Logic when dealing with Social Complexity, Complexity International. 04 (1997)1-10.[23] T. Yahashita, On a support system for human decision making by the combination of fuzzy reasoning andfuzzy structural modeling, Fuzzy Set and System. 8 (1998), 257-263.[24] T. Luis, A Fuzzy based advisor for election and creation of political communities, Information SystemResearch Group. 3 (2011) 180-185.
There are 1 citations in total.

Details

Primary Language English
Subjects Mathematical Sciences
Journal Section Articles
Authors

Shehab A. Ibrahem

Ahmet Sahıner

Ahmed A. Ibrahım

Publication Date August 1, 2018
Published in Issue Year 2018 Volume: 1 Issue: 1

Cite

APA Ibrahem, S. A., Sahıner, A., & Ibrahım, A. A. (2018). Fuzzy Logic Modeling for Prediction of the Nuclear Tracks. Journal of Multidisciplinary Modeling and Optimization, 1(1), 33-40.
AMA Ibrahem SA, Sahıner A, Ibrahım AA. Fuzzy Logic Modeling for Prediction of the Nuclear Tracks. jmmo. August 2018;1(1):33-40.
Chicago Ibrahem, Shehab A., Ahmet Sahıner, and Ahmed A. Ibrahım. “Fuzzy Logic Modeling for Prediction of the Nuclear Tracks”. Journal of Multidisciplinary Modeling and Optimization 1, no. 1 (August 2018): 33-40.
EndNote Ibrahem SA, Sahıner A, Ibrahım AA (August 1, 2018) Fuzzy Logic Modeling for Prediction of the Nuclear Tracks. Journal of Multidisciplinary Modeling and Optimization 1 1 33–40.
IEEE S. A. Ibrahem, A. Sahıner, and A. A. Ibrahım, “Fuzzy Logic Modeling for Prediction of the Nuclear Tracks”, jmmo, vol. 1, no. 1, pp. 33–40, 2018.
ISNAD Ibrahem, Shehab A. et al. “Fuzzy Logic Modeling for Prediction of the Nuclear Tracks”. Journal of Multidisciplinary Modeling and Optimization 1/1 (August 2018), 33-40.
JAMA Ibrahem SA, Sahıner A, Ibrahım AA. Fuzzy Logic Modeling for Prediction of the Nuclear Tracks. jmmo. 2018;1:33–40.
MLA Ibrahem, Shehab A. et al. “Fuzzy Logic Modeling for Prediction of the Nuclear Tracks”. Journal of Multidisciplinary Modeling and Optimization, vol. 1, no. 1, 2018, pp. 33-40.
Vancouver Ibrahem SA, Sahıner A, Ibrahım AA. Fuzzy Logic Modeling for Prediction of the Nuclear Tracks. jmmo. 2018;1(1):33-40.