Title :
Aircraft Take-off and Landing Performance Intelligent Computation Model and Applications
Author :
Wei, Xunkai ; Wu, Lirong ; Hou, Shengli ; Li, Yinghong
Author_Institution :
Dept. of Aircraft & Power Eng., Air Force Eng. Univ., Xian
Abstract :
A novel aircraft take-off and landing performance intelligent computation model was proposed in this paper. First, main factors towards aircraft tableland take-off and landing performance were briefly analyzed. Then, general model for aircraft tableland take-off and landing performance computation was proposed. Finally, support vector machines (SVM) was applied in real taxing distance data of some type of aircraft. Meantime, so as to show superiority, high-precision etc. virtues of SVM, Bayesian regularized BP neural networks (BRBP), radical basis function neural networks (RBF), adaptive network based fuzzy inference systems (ANFIS) were also investigated. Results show that SVM is well suited for practical engineering use with satisfied generalized performance, as is better than other intelligent computation methods in the case studied in this paper. The proposed intelligent computation model is especially commendable for developing and enriching aircraft take-off and landing performance computation theory
Keywords :
adaptive systems; aerospace computing; aerospace engineering; backpropagation; belief networks; fuzzy reasoning; knowledge based systems; radial basis function networks; support vector machines; Bayesian regularized BP neural networks; adaptive network based fuzzy inference systems; aircraft landing performance intelligent computation; aircraft tableland landing performance; aircraft tableland take-off performance; aircraft take-off performance intelligent computation; radical basis function neural networks; support vector machines; Adaptive systems; Aircraft propulsion; Bayesian methods; Computational modeling; Computer applications; Fuzzy neural networks; Machine intelligence; Neural networks; Performance analysis; Support vector machines; Support Vector Machines (SVM); aircraft take-off and landing performance; intelligent computation model;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1714202
