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Identifying and Training Data for Appraoching AI by Construction of Entropy and PSO

I-HO Lee
Department of Information Engineering, I-Shou University, Taiwan
Chuan-Chun Wu
Department of Information Management, I-Shou University, Taiwan
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1.
Identifying and Training Data for Appraoching AI by Construction of Entropy and PSO. Journal of Research and Opinion [Internet]. 2020 Mar. 13 [cited 2024 Nov. 22];7(3):2649-5. Available from: https://researchopinion.in/index.php/jro/article/view/55
  • Articles
  • Submited: March 12, 2020
  • Published: March 13, 2020

Abstract

In the current field of AI, we use neural network and classification and clustering of data mining that those sciences train data for building model.  However, those training data method still need domain knowledge of humans to sort relative data.  So, we provide a construction to similar creature learning method. In physical space and in the dynamic environment the data seem chaos, but they do have regulars that we can find. Furthermore, our intelligence is dependent on our abilities of identifying the relation between outside environment and us, and we need to recognize the environmental data that this recognizing behavior or process is like learning system via  logic and sorting functions.  When each event  is happened that we need to identify what data is affected by them.  If we want to directly distinguish those relative data that we use entropy to analyse the dynamic data of environment with social function of particle swarm optimization(PSO) for achieving the learning method of creature.

References

[1]. Tianshi Chen ; Zidong Du ; Ninghui Sun ; Jia Wang ; Chengyong Wu ; Yunji Chen ; Olivier Temam INRIA, "A High-Throughput Neural Network Accelerator", IEEE Micro, vol. 35, no. 3, pp. 24-32, 2015.


[2]. Huan Liu ; Lei Yu; "Toward integrating feature selection algorithms for classification and clustering" IEEE Transactions on Knowledge and Data Engineering ,Vol. 17 , Issue: 4 ,pp. 491 - 502 , April 2005

[3]. Stuart Russell and Peter Norvig, " Artificial Intelligence: A Modern Approach ",Edition
3,Prentice Hall,2002

[4]. Greenough, Black and Wallance," Experience and Brain Development" ,
Child Development,Vol. 58, No. 3, pp. 539-559,Jun., 1987


[5] Kennedy, J.; Eberhart, R. (1995). "Particle Swarm Optimization". Proceedings of IEEE International Conference on Neural Networks. IV. pp.1942–1948.

[6] Ahmad Rabanimotlagh Bursa (2011) "An Efficient Ant Colony Optimization Algorithm for Multiobjective Flow Shop Scheduling Problem" World Academy of Science, Engineering and Technology 51 pp. 127-133.

[7] Ujjwal Maulik, Sanghamitra Bandyopadhyay (29 April 1999) " Genetic algorithm-based clustering technique " Pattern Recognition 33 No.1455,1465 pp. 1455-1465.

[8] Kirkpatrick, S.; Gelatt, C. D.; Vecchi, M. P. (1983). "Optimization by Simulated Annealing". Science 13 May 1983, Volume 220, No. 4598 pp.671-680.

[9] X.-S. Yang; S. Deb (December 2009). "Cuckoo search via Lévy flights". World Congress on Nature & Biologically Inspired Computing. IEEE Publications. Papercore summary pp.210–214.
http://papercore.org/Yang2009

[10] Yang, X. S. (2008). " Firefly Algorithm, Stochastic Test Functions and Design Optimisation" Papercore summary pp. 1-11. http://papercore.org/Yang2009


[11] X. S. Yang, (2010) " A New Metaheuristic Bat-Inspired Algorithm ", in: Nature Inspired Cooperative Strategies for Optimization, Studies in Computational Intelligence, Springer Berlin, 284, Springer, pp.65-74. http://arxiv.org/abs/1004.4170

[12] E. Zitzler and L. Thiele,( 1999), "Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach" IEEE Trans. Evol. Comput., vol. 3, pp. 257–271.


[14] Wikipedia(17 Feb 2020)
https://en.wikipedia.org/wiki/Entropy_(information_theory)

[15] ccjou(10 sept 2013)
https://ccjou.wordpress.com/2013/10/09/
How to Cite
1.
Identifying and Training Data for Appraoching AI by Construction of Entropy and PSO. Journal of Research and Opinion [Internet]. 2020 Mar. 13 [cited 2024 Nov. 22];7(3):2649-5. Available from: https://researchopinion.in/index.php/jro/article/view/55

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