Title :
A Real Estate Evaluation Risk Early-Warning Model Based on Immune Algorithm
Author :
Wu, Ze-Jun ; Han, Yong ; Liang, Yi-wen
Author_Institution :
Wuhan Univ., Wuhan
Abstract :
For the reason that there are lots of uncertain factors existing in the real estate evaluation market, the traditional and static evaluation methods, such as organization ranking or yearly interrogating, are not efficient for following and monitoring the risk exactly. A novel intelligent alerting model, designed in this paper, can sense abnormity and identify risk exactly, based on the knowledge of artificial immunology and r-contiguous matching function with weight values. The factors that influence the evaluation market will be quantitated and coded. So the model can detect the abnormal factors by the self-adaptive learning and alert the risk of real estate evaluation market exactly and timely.
Keywords :
alarm systems; real estate data processing; risk analysis; unsupervised learning; immune algorithm; intelligent alerting model; r-contiguous matching function; real estate evaluation risk early-warning model; self-adaptive learning; uncertain factors; weight values; Companies; Condition monitoring; Cybernetics; Educational institutions; Electronic mail; Government; Immune system; Machine learning; Machine learning algorithms; Organisms; Artificial immunology; Real estate evaluation market; Risk early-warning;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370161