A survey on intelligence approaches that may be useful for information and communication technology research

doi:1005-8885 (2008) 01-0001-05

Acta Metallurgica Sinica(English letters) ›› 2008, Vol. 15 ›› Issue (1): 1-5.doi: 1005-8885 (2008) 01-0001-05

• Wireless • Next Articles

A survey on intelligence approaches that may be useful for information and communication technology research

ZHONG Yi-xin

School of Information Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2008-01-05 Revised:1900-01-01 Online:2008-03-31
Contact: ZHONG Yi-xin

Abstract

CLC Number:

TP919

ZHONG Yi-xin. A survey on intelligence approaches that may be useful for information and communication technology research[J]. Acta Metallurgica Sinica(English letters), 2008, 15(1): 1-5.

References

1. Zhong Yi-xin. Principles of Information Science. Third Edition. Beijing: BUPT Press, 2002 (in Chinese)

2. Russell S J, Norvig P. Artificial Intelligence: A Modern Approach. Second Edition. Beijing: Pearson Education Asia Limited and Tsinghua University Press, 2006

3. Cowan J D, Sharp D H. Neural Nets. Quarterly Reviews of Biophysics, 1988, 21: 365-427

4. Cowan J D, Sharp D H. Neural nets and artificial intelligence. Daedalus, 1988, 117: 85-121

5. McCulloch W S, Pitts W H. A logical calculus of the ideas imminent in nervous activity. Bull Math Biophy. 1943, 5: 115-135

6. Rosenblatt F. The perceptron: a probabilistic model for information storage and organization in the brain. Psych Rev, 1958, 65: 386-408

7. Hinton G E, Anderson J A. Parallel Models of Associative Memory. Lawrence Erlbaum Associates, Potomac, Maryland. 1981

8. Hopfield J J. Neural networks and physical systems with emergent collective computational abilities. Proceedings of Nat Acad of Sci, 1982, 79: 2554-2558

9. Rumelhart D E, McClelland J L. Parallel Distributed Processing. MIT Press, Cambridge, Massachusetts. 1986 (Eds.)

10. Newell A, Simon H A. Human problem solving. Englewood Cliffs, NJ: Prentice-Hall, 1972

11. Simon H A. The Sciences of Artificial. Cambridge, MA: The MIT Press, 1969

12. Webber B L, Nilsson N J. Readings in Artificial Intelligence. Morgan Kaufmann, San Mateo, California. 1981 (Eds.)

13. Cohen P R. Empirical Methods for Artificial Intelligence. MIT Press, Cambridge, Massachusetts. 1995

14. Nilsson N J. Principles of Artificial Intelligence. Springer-Verlag, Berlin, 1982

15. Feigenbaum E A, Feldman J. Computers and thought. McGraw-Hill, 1963 (Eds.)

16. Brooks R. Intelligence without representation. Artificial Intelligence, 1991, 47: 139-159

17. Brooks R. Intelligence without Reasoning, in Proceedings of IJCAI’91 Sydney, 1991

18. Zhong Yi-xin. Principles of Cognetics in Machine: A Unified Theory of Information-Knowledge-Intelligence Transform. Beijing: Science Press. 2007 (in Chinese)

19. Zhong Yi-xin. Cognitive approach to artificial and natural intel- ligence. International Journal on Cognitive Informatics and Natural Intelligence. 2007, 2(1): 1-16

20. Nilsson N. Artificial Intelligence: A New Synthesis, Morgan Kaufmann Publisher, 1998

21. Jennings N R. Agent-based computing promise and perils. IJCAI-99, 1999, 1429-1436

22. Chaib-draa B, et al. Trends in distributed artificial intelligence. Artificial Intelligence Review, 1992, 6: 35-66

Copyright © 2020 The Journal of China Universities of Posts and Telecommunications
　 Adress: P.O. Box 231,Beijing University of Posts and Telecommunications,10 Xi Tucheng Road,Beijing 100876,P.R.China　Post Code: 100081
Tel：86-010-62282493　Fax： 86-010-62283461　E-mail: jchupt@bupt.edu.cn
Support by: Beijing Magtech Co.Ltd

[1]	Hong PENG yaozong liu. Joint global constraint and Fisher discrimination based multi-layer dictionary learning for image classification [J]. The Journal of China Universities of Posts and Telecommunications, 2023, 30(5): 1-10.
[2]	Cheng Jie, Zhang Ru, Wei Jiahui, Lu Chen, LvZhishuai, Lin Bingjie, Xia Ang. Heuristic multistep attack scenarios construction based on kill chain [J]. The Journal of China Universities of Posts and Telecommunications, 2023, 30(5): 61-71.
[3]	Zhang Xijun, Zhang Guannan, Zhang Xianli, Zhang Hong, Zhang Minghu. Medium and long-term traffic flow prediction based on ACNN-Trans model [J]. The Journal of China Universities of Posts and Telecommunications, 2023, 30(4): 21-32.
[4]	Zheng Zhidong, Yu Yanming, Liu Ning, Yuan Honggang, Lou Ning. Low-complexity detection based on maximum cumulative measure and Laurent decomposition for multi-h CPM signal [J]. The Journal of China Universities of Posts and Telecommunications, 2022, 29(6): 64-72.
[5]	Huang Junfu, Wang Yawen, Gong Yunzhan, Jin Dahai. Cross-project software defect prediction based on multi-source data sets [J]. The Journal of China Universities of Posts and Telecommunications, 2021, 28(4): 75-87.
[6]	. Human motion prediction using optimized sliding window polynomial fitting and recursive least squares [J]. The Journal of China Universities of Posts and Telecommunications, 2021, 28(3): 76-85.
[7]	. TCL: a taxi trajectory prediction model combining time and space features [J]. The Journal of China Universities of Posts and Telecommunications, 2021, 28(3): 63-75.
[8]	. Partition sampling strategy for robot motion planning under uncertainty [J]. The Journal of China Universities of Posts and Telecommunications, 2021, 28(3): 49-62.
[9]	Duan Shengyu, Zhai Dongyao, Lu Yue. Statistical static timing analysis for circuit aging prediction [J]. The Journal of China Universities of Posts and Telecommunications, 2021, 28(2): 14-23.
[10]	Han Fengquan, Han Yinghua , Lu Jing, Zhao Qiang. Wind speed prediction based on nested shared weight long short-term memory network [J]. The Journal of China Universities of Posts and Telecommunications, 2021, 28(1): 41-51.
[11]	Zhao Guosheng, Liu Dongmei, Wang Jian. Cloud security situation prediction method based on grey wolf optimization and BP neural network [J]. The Journal of China Universities of Posts and Telecommunications, 2020, 27(6): 30-41.
[12]	Liu Kun, Wang Hui , Shen Zihao. Prediction of network attack profit path based on NAPG model [J]. The Journal of China Universities of Posts and Telecommunications, 2020, 27(5): 91-102.
[13]	Chen Faquan, Fan Jun. Real-time prediction of the motion tendency of human lower limbs during gait [J]. The Journal of China Universities of Posts and Telecommunications, 2020, 27(4): 1-7.
[14]	Zhou You, Duan Ruifeng, Jiang Bofeng. Reduced-state noncoherent MLSD method for CPM in aeronautical telemetry [J]. The Journal of China Universities of Posts and Telecommunications, 2020, 27(4): 43-53.
[15]	Wang Huan, Liu Ting, Cao Yuning, Wu Aixiang. Underflow concentration prediction model of deep-cone thickener based on data-driven [J]. The Journal of China Universities of Posts and Telecommunications, 2019, 26(6): 63-72.

A survey on intelligence approaches that may be useful for information and communication technology research

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments