TY - GEN
T1 - Fuzzy case-based reasoning
T2 - 1st International Conference on Machine Learning and Cybernetics, ICMLC 2002
AU - Li, Kan
AU - Liu, Yu Shu
PY - 2002
Y1 - 2002
N2 - Classical K-nn algorithm in CBR has been used widely. But in the actual situation, cases often have kinds of features, and classical K-nn algorithm cannot tackle it well. Other fuzzy K-nn algorithm may apply well to these perspective systems, but they do not adapt to weather prediction. In the paper, we propose our novel fuzzy K-nn algorithm. Because weather is continuous, dynamic, and chaotic, in our algorithm, the time function as the adjustive factors is introduced to similarity-measuring function. Fuzzy logic is used in the retrieval of cases. Then fuzzy K-nn algorithm is proposed. Finally, Experimental results are given and we get better effect.
AB - Classical K-nn algorithm in CBR has been used widely. But in the actual situation, cases often have kinds of features, and classical K-nn algorithm cannot tackle it well. Other fuzzy K-nn algorithm may apply well to these perspective systems, but they do not adapt to weather prediction. In the paper, we propose our novel fuzzy K-nn algorithm. Because weather is continuous, dynamic, and chaotic, in our algorithm, the time function as the adjustive factors is introduced to similarity-measuring function. Fuzzy logic is used in the retrieval of cases. Then fuzzy K-nn algorithm is proposed. Finally, Experimental results are given and we get better effect.
KW - Case-based reasoning
KW - Fuzzy logic
KW - K-nearest neighbor
KW - Similarity-measuring function
UR - https://www.scopus.com/pages/publications/0036928064
M3 - Conference contribution
AN - SCOPUS:0036928064
SN - 0780375084
SN - 9780780375086
T3 - Proceedings of 2002 International Conference on Machine Learning and Cybernetics
SP - 107
EP - 110
BT - 2002 International Conference on Machine Learning and Cybernetics, ICMLC 2002
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 4 November 2002 through 5 November 2002
ER -