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基于DFS的协调机器学习模型 被引量:1

Research on A Kind of Coordination Machine Learning Model Based on The DFS
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摘要 机器学习是人工智能的核心课题之一,机器学习的研究得到众多学者的广泛关注。基于动态模糊集等基本理论,提出了一种协调学习模型,并讨论了CMLM的学习算法,该种学习方法适合复杂的学习系统。通过研究这种学习方法,进一步丰富了机器学习的基本内容。 Machine learning is a key problem for artificial intelligence, which research is a widespread and profound influence in many scholar. Based on dynamic fuzzy sets theory, in this paper, a kind of coordination machine learning model (CMLM) is proposed and learning algorithm of CMLM is discussed. This learning method is fit for complicated learning system. By the research of this learning method, this paper has abundanted the content of machine learning.
作者 李凡长
出处 《计算机工程》 CAS CSCD 北大核心 2001年第3期106-109,144,共5页 Computer Engineering
基金 国家自然科学基金 苏州大学科研处基金
关键词 动态模糊集 人工智能 协调机器学习 DFS 人工智能 Dynamic fuzzy sets Artifical intelligence Machine coordination learning
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  • 1孙吉贵,刘叙华.NC线性对称调解[J].计算机学报,1993,16(8):561-567. 被引量:2
  • 2李凡长,徐金辉,蔡庆生.一种基于类比空间的类比推理的定义及数学模型[J].计算机科学,1994,21(5):35-37. 被引量:2
  • 3李凡长,刘贵全,蔡庆生.基于动态模糊逻辑的一种学习模型[J].计算机科学,1996,23(3):73-74. 被引量:6
  • 41,Allen J. Maintaining knowledge about temporal intervals. Communication of the ACM, 1983,26(11):832~843 被引量:1
  • 52, Vilain M, Kautz H. Constraint propagation algorithms for temporal reasoning. In: Kehler T, Rosenschein S et al eds. Proceedings of the 5th National Conference on Artificial Intelligence. San Mateo, CA: Morgan Kaufmann Publishers, Inc., 1986. 377~382 被引量:1
  • 63, Dechter R, Meiri I, Pearl J. Temporal constraint networks. Artificial Intelligence, 1991,49(1):61~95 被引量:1
  • 74, Meiri I. Combining qualitative and quantitative constraints in temporal reasoning. Artificial Intelligence, 1996,87(2):343~385 被引量:1
  • 85, Navarrete I, Marin R. Qualitative temporal reasoning with points and durations. In: Pollack M E ed. Proceedings of the 14th International Joint Conference on Artificial Intelligence. San Mateo, CA: Morgan Kaufmann Publishers, Inc., 1997. 1454~1459 被引量:1
  • 96,Wetprasit R, Sattar A. Temporal reasonning with qualitative and quantitative information about points and durations. In: Mostow J, Rich C eds. Proceedings of the 15th National Conference on Artificial Intelligence. Cambridge, MA: AAAI Press, 1998. 656~663 被引量:1
  • 107, Schwlb E, Dechter R. Processing disjunctions in temporal constraint networks. Artificial Intelligence, 1997,93(1):29~61 被引量:1

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