Wastewater Treatment Systems from Case-Based Reasoning
Abstract
Case-Based Reasoning (CBR) is one of the emerging paradigms for designing intelligent systems. Preliminary studies indicate that the area is ripe for theoretical advances and innovative applications. Heuristic search is one of the most widely used techniques for obtaining optimal solutions to many real-world problems. We formulated the design of wastewater treatment systems as a heuristic search problem. In this article we identify some necessary properties of the heuristic search problems to be solved in the CBR paradigm. We designed a CBR system based on these observations and performed several experiments with the wastewater treatment problem. We compare the performance of the CBR system with the A* search algorithm.
Cite
Text
Krovvidy and Wee. "Wastewater Treatment Systems from Case-Based Reasoning." Machine Learning, 1993. doi:10.1023/A:1022643228269Markdown
[Krovvidy and Wee. "Wastewater Treatment Systems from Case-Based Reasoning." Machine Learning, 1993.](https://mlanthology.org/mlj/1993/krovvidy1993mlj-wastewater/) doi:10.1023/A:1022643228269BibTeX
@article{krovvidy1993mlj-wastewater,
title = {{Wastewater Treatment Systems from Case-Based Reasoning}},
author = {Krovvidy, Srinivas and Wee, William G.},
journal = {Machine Learning},
year = {1993},
pages = {341-363},
doi = {10.1023/A:1022643228269},
volume = {10},
url = {https://mlanthology.org/mlj/1993/krovvidy1993mlj-wastewater/}
}