Application of Artificial Neural Network (ANN): Development of Central-based ANN (CebaANN)

被引:0
作者
Jeong, Su Yeon [1 ]
Yoon, Tae Seon [2 ]
Jeong, Chae Yoon [1 ]
机构
[1] Hankuk Acad Foreign Studies, Gyeonggi Do Yongin 17035, South Korea
[2] Hankuk Acad Foreign Studies, Sci & Informat Dept, Gyeonggi Do Yongin 17035, South Korea
来源
2016 8TH INTERNATIONAL CONFERENCE ON COMPUTER AND AUTOMATION ENGINEERING (ICCAE 2016) | 2016年 / 56卷
关键词
D O I
10.1051/matecconf/20165604001
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Nowaday, the number of known protein structures is significantly less than the number of known amino acid sequences. It is because the regularity of amino acid depend on structure is not clear and the number of thermodynamic conditions are too many. There are some cases that discovering protein structure by experiment. However, It needs much time and cost for increasing the number of amino acid sequences, thus, there is less efficiency. So the empirical method which predict theoretically the structure of protein has been developed. We suggest Central-Based Artificial Neural Network as prediction method of protein structure. CebaANN can analyze similarity more detail by making part of center that affect outcome bigger. In experiment we got 85% of prediction probability at E structure, but we got 34% of probability at total.
引用
收藏
页数:5
相关论文
共 50 条
[1]   Application of artificial neural network (ANN) for prediction of fabrics' extensibility [J].
Rolich, Tomislav ;
Sajatovic, Anica Hursa ;
Pavlinic, Daniela Zavec .
FIBERS AND POLYMERS, 2010, 11 (06) :917-923
[2]   Application of artificial neural network (ANN) for prediction of fabrics’ extensibility [J].
Tomislav Rolich ;
Anica Hursa Šajatović ;
Daniela Zavec Pavlinić .
Fibers and Polymers, 2010, 11 :917-923
[3]   Application of Artificial Neural Network (ANN) for Prediction of Maritime Safety [J].
Xu Jian-Hao .
INFORMATION AND MANAGEMENT ENGINEERING, PT VI, 2011, 236 :34-38
[4]   Application of Artificial Neural Network (ANN) for Prediction of Power Load [J].
Xia, Fei ;
Fan, Li .
SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING: THEORY AND PRACTICE, VOL 2, 2012, 115 :673-+
[5]   Application of an artificial neural network (ANN) for the identification of grapevine genotypes [J].
Mancuso, S ;
Pisani, PL ;
Bandinelli, R ;
Rinaldelli, E .
VITIS, 1998, 37 (01) :27-32
[6]   Development of an artificial neural network (ANN) for retinal image analysis [J].
Basu, A ;
Lowell, J ;
Kennedy, RI ;
Hunter, A ;
Ryder, RE .
DIABETES, 2001, 50 :A430-A430
[7]   Artificial Neural Network (ANN) Based Implementation of Duval Pentagon [J].
Farooque, Md Umar ;
Wani, Shufali A. ;
Khan, Shakeb A. .
2015 INTERNATIONAL CONFERENCE ON CONDITION ASSESSMENT TECHNIQUES IN ELECTRICAL SYSTEMS (CATCON), 2015, :46-50
[8]   Artificial Neural Network (ANN) Based Empirical Interpolation of Precipitation [J].
Joshi, Rajesh .
INTERNATIONAL JOURNAL OF MATHEMATICAL ENGINEERING AND MANAGEMENT SCIENCES, 2016, 1 (03) :93-106
[9]   Application of the artificial neural network (ANN) in flood forecasting on a karstic catchment [J].
Xiong, LH ;
O'Connor, KM ;
Goswami, M .
FORECASTING AND MITIGATION OF WATER-RELATED DISASTERS, THEME C, PROCEEDINGS: 21ST CENTURY: THE NEW ERA FOR HYDRAULIC RESEARCH AND ITS APPLICATIONS, 2001, :29-35
[10]   Application of Artificial Neural Network (ANN) to improve forecasting of sea level [J].
Filippo, Alessandro ;
Torres, Audalio Rebelo, Jr. ;
Kjerfve, Bjorn ;
Monat, Andre .
OCEAN & COASTAL MANAGEMENT, 2012, 55 :101-110