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博文

目前显示的是标签为“Support Vector Machine”的博文

Hilbert Huang Transform for Predicting Proteins Subcellular Location

Read  full  paper  at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=17#.VNMxHizQrzE Author(s)   Feng SHI , Qiujian CHEN , Nana LI   Affiliation(s) School of Science, Huazhong Agricultural University, Wuhan, Hubei, China . School of Science, Huazhong Agricultural University, Wuhan, Hubei, China . School of Science, Huazhong Agricultural University, Wuhan, Hubei, China . ABSTRACT Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for the understanding the mechanism of programmed cell death, and their function is related to their types. The apoptosis proteins are categorized into the following four types: (1) Cytoplasmic protein; (2) Plasma membrane-bound protein; (3) Mitochondrial inner and outer proteins; (4) Other proteins. A novel method, the Hilbert-Huang transform, is applied for predicting the type of a given apoptosis protein with support...

The Prediction Model of Financial Crisis Based on the Combination of Principle Component Analysis and Support Vector Machine

Read full paper at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=49185#.VJJuo8nQrzE Author(s)   Guicheng Shen * , Weiying Jia Affiliation(s) School of Information, Beijing Wuzi University, Beijing, China . ABSTRACT This paper studies financial crisis of listed companies in China Manufacture Industry, and selects 181 companies with financial crisis and 181 normal companies as its research samples, and its research is based on financial indexes three years before the financial crisis happens. Firstly the method of principle component analysis is used to abstract useful information from the training data. Secondly a prediction model of financial crisis is constructed with the method of Support V...

An Integrated Intrusion Detection System by Combining SVM with AdaBoost

Read full paper at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=51617#.VHKFKGfHRK0 Author(s) Yu Ren Affiliation(s) College of Computer, Communication University of China, Beijing, China . ABSTRACT In the Internet, computers and network equipments are threatened by malicious intrusion, which seriously affects the security of the network. Intrusion behavior has the characteristics of fast upgrade, strong concealment and randomness, so that traditional methods of intrusion detection   system (IDS) are difficult to prevent the attacks effectively. In this paper, an integrated network   intrusion detection algorithm by combining support vector machine (SVM) with AdaBoost was   presented. T...