Temperature prediction based on fuzzy clustering and fuzzy rules interpolation techniques

@article{Chen2009TemperaturePB,
  title={Temperature prediction based on fuzzy clustering and fuzzy rules interpolation techniques},
  author={Shyi-Ming Chen and Yu-Chuan Chang and Ching-Hsue Cheng and Sue-Fen Huang},
  journal={2009 IEEE International Conference on Systems, Man and Cybernetics},
  year={2009},
  pages={3444-3449}
}
In this paper, we present a new method to deal with temperature prediction based on fuzzy clustering and fuzzy rules interpolation techniques. First, the proposed method constructs fuzzy rules from training samples based on the fuzzy C-Means clustering algorithm, where each fuzzy rule corresponds to a cluster and the linguistic terms appearing in the fuzzy rules are represented by triangular fuzzy sets. Then, it performs fuzzy inference based on the multiple fuzzy rules interpolation scheme… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.

References

Publications referenced by this paper.
Showing 1-10 of 17 references

Pattern Recognition with Fuzzy Objective Function Algorithms

Advanced Applications in Pattern Recognition • 1981
View 10 Excerpts
Highly Influenced

Fuzzy Interpolation and Extrapolation: A Practical Approach

IEEE Transactions on Fuzzy Systems • 2008
View 1 Excerpt

Similar Papers

Loading similar papers…