Title :
Risk assessment in power plants based on AIA improved support vector machines
Author :
Sun, Wei ; Zhang, Jie
Author_Institution :
Sch. of Bus. Adm., North China Electr. Power Univ., Baoding
Abstract :
According to the practical situation of risk assessment in power plants, a set of index system is established. The index system includes financial indexes and non-financial indexes. Then support vector machines (SVM) algorithm is used for assessment in this research. In this paper the step of improve SVM by artificial immune algorithm is given to show how to get the best effectiveness in SVM. In this paper we give an example coming from power plants data and the results show that the method can classify the data effectively, and the model has high correct classification accuracy.
Keywords :
artificial immune systems; power plants; risk management; support vector machines; AIA improved support vector machines; artificial immune algorithm; classification accuracy; nonfinancial indexes; power plants; risk assessment; Automation; Logistics; Power generation; Power system modeling; Quadratic programming; Risk management; Statistical learning; Sun; Support vector machine classification; Support vector machines; AIA; Classification; Power plants; Risk assessment; Support vector machines;
Conference_Titel :
Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-2502-0
Electronic_ISBN :
978-1-4244-2503-7
DOI :
10.1109/ICAL.2008.4636200