Inexact Inference for Rule-Based Damage Assessment of Existing Structures
Proceedings of the Seventh International Joint Conference on Artificial Intelligence. Expert Systems. Pages 837-841.
Abstract
he knowledge organization of a rule-based damage assessment system of existing structures subjected to earthquake excitation is outlined in this paper. A principle of inexact inference to obtain a rational solution is presented. The fuzzy set theory and the production system with certainty factor are employed jointly in the inexact inference to deal with the continuous nature of the damage state and to attain the modularity of uncertain knowledge, respectively.
Mitsuru Ishizuka, King-sun Fu, and James T. P. Yao. 1981. Inexact Inference for Rule-Based Damage Assessment of Existing Structures. In Proceedings of the Seventh International Joint Conference on Artificial Intelligence, IJCAI-81. IJCAI, 837–841. https://ijcai.org/proceedings/1981/159
Ishizuka, M., Fu, K., & Yao, J. T. P. (1981). Inexact Inference for Rule-Based Damage Assessment of Existing Structures. In Proceedings of the Seventh International Joint Conference on Artificial Intelligence, IJCAI-81 (pp. 837–841). IJCAI. https://ijcai.org/proceedings/1981/159
@inproceedings{ijcai1981p159,
title = {Inexact Inference for Rule-Based Damage Assessment of Existing Structures},
author = {Ishizuka, Mitsuru and Fu, King-sun and Yao, James T. P.},
booktitle = {Proceedings of the Seventh International Joint Conference on
Artificial Intelligence, {IJCAI-81}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Roger C. Schank},
pages = {837--841},
year = {1981},
month = {8},
note = {Expert Systems},
url = {https://ijcai.org/proceedings/1981/159},
}
TY - CPAPER TI - Inexact Inference for Rule-Based Damage Assessment of Existing Structures AU - Ishizuka, Mitsuru AU - Fu, King-sun AU - Yao, James T. P. T2 - Proceedings of the Seventh International Joint Conference on Artificial Intelligence, IJCAI-81 PB - International Joint Conferences on Artificial Intelligence PY - 1981 SP - 837 EP - 841 UR - https://ijcai.org/proceedings/1981/159 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
