Delamination identification of CFRP structure using discriminant analysis via the support vector machine
نویسندگان
چکیده
منابع مشابه
Identification areas with inundation potential for urban runoff harvesting using the support vector machine model
Rainfall-runoff from urban areas is one of the available water resources, which is wasted due to lack of attention and proper management. Besides, urban runoff excess of drains capacity causing many problems including inundation and urban environmental pollution. Therefore, harvesting this runoff can provide a part of the required water in urban areas, and also reduce flood and urban inund...
متن کاملInterval discriminant analysis using support vector machines
Imprecision, incompleteness, prior knowledge or improved learning speed can motivate interval–represented data. Most approaches for SVM learning of interval data use local kernels based on interval distances. We present here a novel approach, suitable for linear SVMs, which allows to deal with interval data without resorting to interval distances. The experimental results confirms the validity ...
متن کاملBlur Parameter Identification using Support Vector Machine
This paper presents a scheme to identify the blur parameters using support vector machine (SVM) Multiclass approach has been used to classify the length of motion blur and sigma parameter of atmospheric blur. Different models of SVM have been constructed to classify the parameters. Experimental results show the robustness of the proposed approach to classify blur parameters.
متن کاملUsing Wavelet Support Vector Machine for Fault Diagnosis of Gearboxes
Identifying fault categories, especially for compound faults, is a challenging task in mechanical fault diagnosis. For this task, this paper proposes a novel intelligent method based on wavelet packet transform (WPT) and multiple classifier fusion. An unexpected damage on the gearbox may break the whole transmission line down. It is therefore crucial for engineers and researchers to monitor the...
متن کاملCancer Related Gene Identification via p-norm Support Vector Machine∗
This paper focuses on the feature selection in classification via a new version of support vector machine (SVM) named p-norm support vector machine (0 < p < 1). Different from the 2-norm in the standard linear SVM, the p-norm of the normal vector of the decision plane is used which leads to more sparse solution. By using the successive linear algorithm, we can get an approximate local optimal s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Transactions of the JSME (in Japanese)
سال: 2014
ISSN: 2187-9761
DOI: 10.1299/transjsme.2014smm0020