Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Progress in Exploration Geophysics》 2007-02
Add to Favorite Get Latest Update

Review of support vector machine and its applications in petroleum exploration and development

Peng Tao,Zhang Xiang School of Geophysics and Oil Resources,Yangtze University,Jingzhou 434023,China  
Support vector machine(SVM)is one of machine learning technologies that emerged in the middle of 1990s.Being different from the traditional neural network that is based on structure risk minimum principle,SVM is based on empirical risk minimum principle.SVM manifests unique advantages in solving machine learning problem that is characterized by small quantity of samples,nonlinear and high dimension space.SVM has been successfully applied in function prediction,pattern recognition and classification.Application of SVM in petroleum exploration and development is an important research direction and has broad application prospect.
【Fund】: 湖北省教育厅科学技术研究重点项目(D200612002);; 湖北省自然科学基金项目(2004ABA043)
【CateGory Index】: P631.4
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
【References】
Chinese Journal Full-text Database 10 Hits
1 ZHENG Jun1,LIU Hongbo1,2,ZHOU Wen1,DENG Hucheng1(1.Energy College,Chengdu University of Technology,Chengdu,Sichuan 610059,China;2.Sichuan Water Conservancy Vocational College,Dujiangyan,Sichuan 600839,China);On Identification Methods for Reservoir Fractures in Daleel Oilfield in Oman Block-5[J];Well Logging Technology;2010-03
2 LI Chi(Department of Computer Science and Software Engineering of Jincheng College,Sichuan University,Chengdu 611731,China);Review of support vector machine and its applications in welding process[J];Electric Welding Machine;2011-10
3 LIU Guo-hui1,HOU Zheng1,2,WANG Tian-yi1,SONG Hong-wei3 (1.Shijiazhuang University of Economics,Shijiazhuang 050031,China;2.China University of Geosciences,Beijing,100083,China; 3.The Institute of Hydrogeology and Environmental Geology,CAGS,Shijiazhuang 050803,China);A new model to predict the water inflow of aquifer[J];Progress in Geophysics;2012-03
4 JIANG Xiao-feng1,XU Lun-hui1,ZHU Yue2(1.School of Civil and Transportation Engineering,South China University of Technology,GuangzhouGuangdong 510461,China;2.School of Bioscience and Bioengineering,South China University of Technology,Guangzhou Guangdong 510006,China);Short-term Traffic Flow Prediction Based on SVM[J];Journal of Guangxi Normal University(Natural Science Edition);2012-04
5 GUO Hai-feng,LI Hong-qi(Faculty of Natural Resource and Information Technology,China University of Petroleum,Beijing 102249,China;State Key Laboratory of Petroleum Resource and Prospecting(China University of Petroleum, Beijing),Beijing 102249,China) MENG Zhao-xu(Faculty of Natural Resource and Information Technology,China University of Petroleum,Beijing 102249,China;State Key Laboratory of Petroleum Resource and Prospecting (China University of Petroleum, Beijing),Beijing 102249,China;Research Institute of Petroleum Exploration and Development,Xinjiang Oilfield Company,PetroChina,Karamay 834000,Xinjiang,China)TAN Feng-qi(Faculty of Natural Resource and Information Technology,China University of Petroleum,Beijing 102249,China;State Key Laboratory of Petroleum Resource and Prospecting (China University of Petroleum, Beijing),Beijing 102249,China);Feature Selection,Genetic Algorithm and Support Vector Machine[J];Journal of Oil and Gas Technology;2008-06
6 ZHOU Ji-hong,YUAN Rui(First Author's Address: College of Geophysics and Oil Resources,Yangtze University;Key Laboratory of Exploration Technologies for Oil and Gas Resources(Yangtze University),Ministry of Education,Jingzhou 434023,Hubei,China);Identifying Complex Lithology of Clastic Rock Reservoir by Support Vector Machine[J];Journal of Oil and Gas Technology;2012-07
7 ZHOU Fan1,JIANG Hong-Fu2,WANG Li-Yan1,MENG Fan-Shun1(1.College of Marine Geo-Science,Ocean University of China,Qingdao 266100,China;2.College of Earth and Space Science,Peking University,Beijing 100871,China);Application of Array Induction Logging and Support Vector Machine to Fluid Identification[J];Periodical of Ocean University of China;2011-S1
8 YANG Lei1,WANG Hua-zeng2,CHEN Zi-ling3(1.School of Economics & Management in China University of Petroleum,Qingdao 266580,China; 2.Shengli Oilfield Dongsheng Group of SINOPEC,Dongying 257091,China; 3.Materials Company of PetroChina,Beijing 100029,China);Assessing value classification of oil and gas reserve based on support vector machine[J];Journal of China University of Petroleum(Edition of Natural Science);2012-03
9 Zhang Yinde Tong Kaijun Zheng Jun Wang Daochuan;Application of support vector machine method for identifying fluid in low-resistivity oil layers.[J];Geophysical Prospecting for Petroleum;2008-03
10 LI Hongqi1,2 GUO Haifeng1,2 GUO Haimin3 MENG Zhaoxu1,2,4 TAN Fengqi1,2 ZHANG Jun1,2(1.School of Resources and Information Technology,China University of Petroleum,Beijing 102249,China;2.State Key Laboratory of Petroleum Resource and Prospecting,China University of Petroleum,Beijing 102249,China;3.College of Geophysics and Oil Resources,Yangtze University,Jingzhou 434023,China;4.Research Institute of Petroleum Exploration and Development,PetroChina Xinjiang Oilfield Company,Karamay 834000,China);An approach of data mining for evaluation of complex formation using well logs[J];Acta Petrolei Sinica;2009-04
【Citations】
Chinese Journal Full-text Database 9 Hits
1 ZHANG Zuo-qing~1,HAN Ke-ning~1,YU Dai-guo~2,ZHANG Zhen-cheng_2(1.Logging Company of Huadong Petroleum Administration,Yangzhou,Jiangsu 225007,China;2.School of Geo-resources & Information,China University of Petroleum,Dongying,Shandong 257061,China);Using Support Vector Machine to Forecast Reservoir Sensitivity[J];Well Logging Technology;2005-04
2 YANG Bin~(1,2),KUANG Li-chun~3, SUN Zhong-chun~3,SHI Ze-jin~1(1.Chengdu University of Technology,Chengdu,Sichuan 610059,China;2.Postdoctorial Programme of Xinjiang Oilfield Company, Karamayi,Xinjiang 834000,China;3.Xinjiang Oilfield Company,PetroChina,Karamayi,Xinjiang 834000,China);On Support Vector Machines Method to Identify Oil & Gas Zone with Logging and Mudlog Information[J];Well Logging Technology;2005-06
3 LI Zhuo~1,LIU Bin~2,LIU Tie-nan~2(1.Goscience College,Daqing Petroleum Institute,Daqing,Heilongjiang 163318, China;2.Electronic and Information Engineering College,Daqing Petroleum Institute,Daqing,Heilongjiang 163318,China);Application of supportive vector machine to the prediction of production in oil fields[J];Journal of Daqing Petroleum Institute;2005-05
4 QI Hengnian (School of Information Engineering,Zhejiang Forestry College,Lin'an 311300);Support Vector Machines and Application Research Overview[J];Computer Engineering;2004-10
5 LI Pan-chi, XU Shao-hua(College of Computer Science and Engineering, Daqing Petroleum Institute, Daqing Heilongjiang 163318,China);Support vector machine and its application in complex water flooded layer recognition[J];Computer Applications;2004-09
6 Zhang Yanzhou, Liu Yeling, Xie Baoying. Department of Basic Course, Xi' an University of Science & Technology,Xi'an 710054, China;Application of SVM in prediction of reservoir thickness.[J];Progress in Exploration Geophysics;2005-06
7 XIONG Min(Shengli Oilfield Co. Ltd., SINOPEC, Linyi 251507, China);Support Vector Machine and Its Application in Enhanced Oil Recovery Potentiality Prediction[J];Mathematics In Practice and Theory;2004-05
8 Yao Kaifeng1,Lu Wenkai1,Ding Wenlong1,Zhang Shanwen2,Xiao Huanqin2 and Li Yanda1 (1.State Key Laboratory of Intelligent Technology and System,Department of Automation,Qinghua University;and 2.Shengli Oil Field Ltd,Sinopec).;HYDROCARBON PREDICTION METHOD BASED ON SVM FEATURE SELECTION[J];Natural Gas Industry;2004-07
9 Yue Youxi and Yuan Quanshe (Institute of Earth Resources and Information, China University of Petroleum).;APPLICATION OF SVM METHOD TO PREDICTING RESERVOIR PARAMETER[J];Natural Gas Industry;2005-12
【Co-citations】
Chinese Journal Full-text Database 10 Hits
1 XU Gao-cheng et al(College of Environment and Resource College,Southwest Science and Technology University,Mianyang,Sichuan 621010);Application of Supporting Vector Machine Technology in Extraction of Remote Sensing Image of Landslide[J];Journal of Anhui Agricultural Sciences;2009-06
2 GUAN Cui-ping (College of Life Science,Ningxia University,Yinchuan,Ningxia 750021);Recognition Prediction on G-Protein-Coupled-Receptors of Drug Target[J];Journal of Anhui Agricultural Sciences;2010-24
3 LIU Ting-ting(School of Software and Microelectronics,Beijing University,Beijing 100093);Research on Recognition of Rhizocotonia solani Based on Support Vector Machine[J];Journal of Anhui Agricultural Sciences;2011-28
4 GAO Chuang1,WANG Li-dong1,ZHOU Shi-yu2(1.School of Electronic and Information Engineering,University of Science and Technology Liaoning,Anshan 114051,China;2.AnGang Group New Hot-Rolled Co Ltd Hot-Rolled Strip Plaint,Anshan 114051,China);Classification of cervical cancer cell based on support vector machine and its application[J];Journal of University of Science and Technology Liaoning;2009-03
5 WANG Ting-hua,TIAN Sheng-feng,HUANG Hou-kuan,LIAO Nian-dong(School of Computer and Information Technology,Beijing Jiaotong University, Beijing 100044,China);Support Vector Machine Based on Weightiness of Sample Attribute[J];Journal of Beijing Jiaotong University;2007-05
6 SHANG Lei1,LIU Feng-jin2 (1. No. 17 Brigade of Graduate,Air Defense Forces Command Academy,Zhengzhou 450052,China;2. Command headquarter,Air Defense Artillery Brigade of Xinjiang Provincial Military Region,Urumchi 830017,China);Handwritten Number Recognition Based on Support Vector Machine[J];Ordnance Industry Automation;2007-03
7 Hu Shuyan Zheng Gangtie(School of Astronautics,Beijing University of Aeronautics and Astronautics,Beijing 100191,China);Driver fatigue prediction with eyelid related parameters by support vector machine[J];Journal of Beijing University of Aeronautics and Astronautics;2009-08
8 WANG ZiQiang DUAN AiLing ZHANG DeXian (School of Information Science and Engineering,Henan University of Technology,Zhengzhou Henan 450001,China);A support vector data description algorithm based on an adaptive kernel function[J];Journal of Beijing University of Chemical Technology(Natural Science Edition);2008-02
9 CHEN Zengzhao~(1,2)) YANG Yang~(1)) DONG Cailin~(2)) HE Xiuling~(1,2)) 1)Information Engineering School,University of Science and Technology Beijing,Beijing 100083,China 2)HE Xiuling The Center for Optimal Control & Discrete Mathematics,Central China Normal University,Wuhan 430079,China;A dynamical learning method with SVM and its application on bank slip recognition[J];Journal of University of Science and Technology Beijing;2006-02
10 GUO Hui,LIU Heping,WANG LingInformation Engineering School,University of Science and Technology Beijing,Beijing 100083,China;Kernel partial least squares based on least squares support vector machine primal-dual optimization problem[J];Journal of University of Science and Technology Beijing;2006-08
China Proceedings of conference Full-text Database 10 Hits
1 Xiukuan Zhao~(a,b,*),Min Li~b,Jinwu Xu~b,Gangbing Song~c ~aBeijing National Observatory of Space Environment,Institute of Geology and Geophysics,Chinese Academy of Sciences,Beijing 100029,China ~bSchool of Mechanical Engineering,University of Science and Technology Beijing,Beijing 100083,China ~cDepartment of Mechanical Engineering,University of Houston,Houston,TX 77204,USA;An effective procedure exploiting unlabeled data to build monitoring system[A];[C];2012
2 Wang Lianhong1,Zhang Guoyun 2,Zhang Jing1 1.College of Electrical and Information Engineering,Hunnan University,Changsha 410082,P.R.China2.Dept.of Physics and Electronics Information,Hunan Institute of Science and Technology,Yueyang,414006,P.R.China;A Novel Kernel PCA Support Vector Machine Algorithm with Feature Transition Function[A];[C];2007
3 Lv Peng1,Liu Yibing2,Ma Qiang2,Wei Yufan2 1.School of Mathematics and Physics,North China Electric Power University,Beijing 102206,P.R.China2.Department of automatics,North China Electric Power University,Beijing 102206,P.R.China;Gear Intelligent Fault Diagnosis Based on Support Vector Machines[A];[C];2007
4 Ma Wenxing1,Li Meng 1,2 1.Institute of Mechanical Science and Engineering,Jilin University,Changchun 130000,P.R.China 2.College of Mechanical Engineering,Changchun University,Changchun 130022,P.R.China;Fault Pattern Recognition of Rolling Bearings Based on Wavelet Packet and Support Vector Machine[A];[C];2008
5 Jiang Shaohua 1,2,Gui Weihua 1,Yang Chunhua 1,Tang Zhaohui1,Jiang Zhaohui1 1.School of Information Science and Engineering,Central South University,Changsha 410083,P.R.China 2.School of Information Science and Engineering,ShaoGuan University,ShaoGuan 512024,P.R.China;Method Based on Principal Component Analysis and Support Vector Machine and Its Application to Process Monitoring and Fault Diagnosis for Lead-Zinc Smelting Furnace[A];[C];2008
6 WANG Hai feng1,LI Zhuang1,REN Hong e2,ZHAO Peng21.School of Electronic and Information Engineering,Qiongzhou University,Sanya,Hainan 572022,P.R.China2.Information and Computer Engineering College,Northeast Forestry University,Harbin,150040,P.R.China;Texture Image Segmentation Algorithm Based on Nonsubsampled Contourlet Transform and SVM[A];[C];2010
7 ZHAO Baoyong~(1,2),QI Yingjian~3 1.School of Automation & Electrical Engineering,University of Science and Technology Beijing,Beijing 100083,P.R.China 2.Key Laboratory of Advanced Control of Iron and Steel Process,University of Science and Technology Beijing, Beijing 100083,P.R.China. 3.Science School,Communication University of China,Beijing 100024,P.R.China;Image Classification with Ant Colony Based Support Vector Machine[A];[C];2011
8 JIN Chaobu~1,HU Gangqiang~2,SHI Guangzhi~1,LI Yuyang~1 (1.Navy Submarine Academy Qingdao 266071,China; 2.92815 Army of PLA,Ningbo 315717,China);A underwater target recognition method using the support vector machines[A];[C];2011
9 Dai Mingyang~1,Yang Dali~1,Xu Mingxing~2 (1.School of Computer Science,Beijing Information Science & Technology University,Beijing 100101,China;2.Key Laboratory of Pervasive Computing,Ministry of Education Tsinghua National Laboratory for Information Science and Technology(TNList) Department of Computer Science and Technology,Tsinghua University,Beijing 100084,China);Research on the composition of UBM training set in speech emotion recognition[A];[C];2011
10 Dai Mingyang~1,Yang Dali~1,Xu Mingxing~2,Zhang Yongchao~2, Chen Sheng (1.School of Computer Science,Beijing Information Science & Technology University,Beijing 100101,China; 2.Key Laboratory of Pervasive Computing,Ministry of Education Tsinghua National Laboratory for Information Science and Technology(TNList) Department of Computer Science and Technology,Tsinghua University,Beijing 100084, China);Research on training speech selection for real emotion recognition[A];[C];2011
【Co-references】
Chinese Journal Full-text Database 10 Hits
1 FENG Jian-hui,YANG Yu-jing (Faculty of Land Resource Engineering of Kuming University of Science and Technology, Kuming,Yunnan,650093);Study of Texture Images Extraction Based on Gray Level Co-Occurence Matrix[J];Beijing Surveying and Mapping;2007-03
2 Liao Ningfang; Gao Zhiyun (Department of Optical Engineering,Beijing Institute of Technology,Beijing 100081);The Most Suitable Architecture of Hidden - Layer in BP Neural Networks for Function Approximation[J];Journal of Beijing Institute of Technology;1998-04
3 ZHANG Chen, DU Jun-ping (College of Information Engineering, Beijing Technology and Business University, Beijing 100037, China);STUDY ON THE PREDICTION METHOD USED IN HIGHWAY VEHICLE SYSTEM[J];Journal of Beijing Institute of Light Indusry;2001-04
4 FU Yang1,ZHANG Lei1,JIANG Yu-rong1,ZUO Guan-fang2(1.Shanghai University of Electric Power,Shanghai 200090,China;2.Changzhou Robotization Institute,Changzhou 213015,China);Power Transformer Fault Diagnosis Bosed on Data Reliability Analysis and Least Squares Support Vector Machine[J];Transformer;2010-09
5 Liu Rui-Lin1, Wu Yue-Qi2, Liu Jian-Hua2, Ma Yong2 1. College of Geophysics and Petroleum resource, Yangtze University, Jingzhou, Hubei 434023, China. 2. Institute of Engineering and Technology of Northwest Petroleum bureau, CNSPC, Urumqi 830011, China.;The Segmentation of FMI Image Based on 2-D Dyadic Wavelet Transform[J];应用地球物理(英文版);2005-02
6 NING Hui-yong,FAN Xiao-min,CHENG Hong-liang College of GeoExploration Science and Technology,Jilin University,Changchun 130026,China;Evaluating the Complex Lithology Reservoir Permeability with Stoneley Wave[J];Journal of Jilin University(Earth Science Edition);2007-S1
7 LIU Qing-kun, QUE Pei-wen, SONG Shou-peng (Inst of Automatic Detection,Shanghai Jiaotong University,Shanghai 200030,China);Study on method for flaw identification based on support vector machine[J];Journal of Transducer Technology;2005-03
8 Shao Weizhi, Lu Fu.;A New Method to Identify Fluid Property in Carbonate Reservoir.[J];Well Logging Technology;2002-01
9 Liang Qiaofeng, Shao Weizhi, Wang Zhike.;Application of high Definition Inductin Logging in Res-ervoir Evaluation.[J];Well Logging Technology;2003-03
10 Zhang Haina, Du Yushan, Wang Shanjiang,et al..;Carbonate Reservoir Features in Buried Hill of Ordovician System in Tahe Oilfield and Their Log Evaluation.[J];Well Logging Technology;2003-04
【Secondary References】
Chinese Journal Full-text Database 10 Hits
1 LI Hong-qi,LI Xiong-yan,TAN Feng-qi,GUO Hai-feng,YU Hong-yan(State Key Laboratory for Petroleum Resource and Prospecting,China University of Petroleum,Beijing 102249,China;Well Logging Research Center,China University of Petroleum,Beijing 102249,China);A Log Evaluation Method Based on the Data Mining Technique[J];Well Logging Technology;2009-01
2 ZHENG Jun1,LIU Hongbo1,2,ZHOU Wen1,DENG Hucheng1(1.Energy College,Chengdu University of Technology,Chengdu,Sichuan 610059,China;2.Sichuan Water Conservancy Vocational College,Dujiangyan,Sichuan 600839,China);On Identification Methods for Reservoir Fractures in Daleel Oilfield in Oman Block-5[J];Well Logging Technology;2010-03
3 WANG Rui1,ZHU Xiaomin1,2,WANG Lichang1(1.College of Geosciences,China University of Petroleum,Beijing 102249,China;2.Key Laboratory for Hydrocarbon Accumulation Mechanism,Ministry of Education,China University of Petroleum,Beijing 102249,China);Using Data Mining to Identify Carbonate Lithology[J];Well Logging Technology;2012-02
4 ZHU Li-ping1,LI Xiong-yan2,3,LI Hong-qi1,2,3(1.Department of Computer Science and Technology,China University of Petroleum(Beijing),Beijing 102249,China;2.State Key Laboratory of Petroleum Resource and Prospecting,China University of Petroleum(Beijing),Beijing 102249,China;3.Key Laboratory of Earth Prospecting and Information Technology,China University of Petroleum(Beijing),Beijing 102249,China);Identifying the low resistivity oil reservoir based on the model-driven data mining[J];Journal of Daqing Petroleum Institute;2010-04
5 ZHENG Song-qing, ZHANG Hong-fang, LIU Zhong-chun, MU Lei( Petroleum Exploration and Development Research Institute, Sinopec, Beijing 100083, China );Discrete fracture network model for fractured reservoirs[J];Journal of Daqing Petroleum Institute;2011-06
6 ZHANG Ying1,PAN Bao-zhi2,HE Sheng-lin2,ZHANG Pei-zhen1 (1.Lab of Ocean Remote Sensing and Information Technology GuangDong Ocean University,Zhanjiang 524088,China;2.College of Geoexploration Science and Technology,Jilin University,Changchun 130026,China;3.Zhanjiang Branch of China National Offshore Oil Corporation,Zhanjiang 524057,China.);Identification of the features of wavelet analysis based reservoir fluid[J];Progress in Geophysics;2012-06
7 HAN Xue-hui1,ZHI Le-fei2,LIU Rong3,YANG Ti-yuan4,LI Ya-ping4(1.Faculty of School of Geosciences,China University of Petroleum,Qingdao 266580,China; 2.Dongsheng Group CO.LTD,Shengli Oil Field,Dongying 25700,China; 3.China National Petroleum Offshore Engineering Co.Ltd.,Tianjin 300451,China; 4.Petroleum Exploration & Development Research Institude,PetroChina,Qinghai Oilfield Company,Duanhuang,736200,China);A lithologic identification method in Es4reservoir of Guangli oilfield with Least square support vector machine[J];Progress in Geophysics;2013-04
8 GUO Haopeng;SHI Yujiang;LI Gaoren;ZHANG Shaohua;SONG Chen;TANG Hongping;Exploration and Development Institute of Petrochina Changqing Oilfield Company;National Engineering Laboratory for Exploration and Development of Low-permeability Oil & Gas Fields;;On Well Logging Technology to Quickly Evaluate Productivity of the Ultra-low Permeability Reservoir[J];Well Logging Technology;2013-06
9 LIU Ying-ying;GAO Xiang-dong;School of Electromechanical Engineering,Guangdong University of Technology;;Analysis of molten pool infrared radiation characteristics based on support vector machine during laser welding[J];Electric Welding Machine;2014-03
10 SHANG Li-yuan;TAN Qing-mei;College of Economics and Management,Nanjing University of Aeronautics and Astronautics;;Emergency Classification Based on Support Vector Machine[J];Journal of Industrial Engineering and Engineering Management;2014-01
【Secondary Citations】
Chinese Journal Full-text Database 10 Hits
1 LI Kan, \ GAO Chun xiao, \ LIU Yu shu (Dept. of Computer Science and Engineering, Beijing Institute of Technology, Beijing100081, China);Support Vector Machine Based Hierarchical Clustering of Spatial Databases[J];Journal of Beijing Institute of Technology;2002-04
2 LIU Hui-chun, MA Shu-yuan, WU Ping-dong, YANG Feng, ZENG Xing-sheng, BI Lu-zheng (School of Mechanical Engineering and Automation, Beijing Institute of Technology, Beijing100081, China);Handwritten Digits Recognition for Automatic Analysis System of UK Psychology Test[J];Journal of Beijing Institute of Technology;2002-05
3 Fan Xunli, Dai Hang et al ..;Applications of Neural Network in Lithology Identification.[J];WELL LOGGING TECHNOLOGY;1999-01
4 LIU Tie-nan~1, LIU Bin~1, LIANG FU-gui~2 ( 1. Electricity and Information Engineering College, Daqing Petroleum Institute, Daqing, Heilongjiang 163318, China; 2. Oil Field Thermal Power Plant, Daqing Electricity Company, Daqing, Heilongjiang 163314, China );A genetic algorithm with local searching strategy and its application[J];Journal of Daqing Petroleum Institute;2005-02
5 LIU Bin~1, LI Zhuo~2, LIU Tie-nan~1, YU Sheng-yang~3, REN Zhen-zhen~4 ( 1. Electricity and Information Engineering College, Daqing Petroleum Institute, Daqing, Heilongjiang 163318, China; 2. Geoscience College, Daqing Petroleum Institute, Daqing, Heilongjiang 163318, China; 3. Personnel Department, Jilin Petroleum Group Co. Ltd., Songyuan, Jilin 138000, China; 4. Department of foreign languages, Daqing Petroleum Institute, Daqing, Heilongjiang 163318, China );A new Widrow adaptive filter based on supportive vector machine[J];Journal of Daqing Petroleum Institute;2005-04
6 ZHAO Hai-long,WANG Fang,HU Xiao-guang (Harbin Institute of Technology,Harbin 150001,Heilongjiang Province,China);APPLICATION OF WAVELET PACKET–ENERGY SPECTRUM IN MECHANICAL FAULT DIAGNOSIS OF HIGH VOLTAGE CIRCUIT BREAKERS[J];Power System Technology;2004-06
7 WANG Cheng-shan, WANG Ji-dong ( School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China );CLASSIFICATION METHOD OF POWER QUALITY DISTURBANCE BASED ON WAVELET PACKET DECOMPOSITION[J];Power System Technology;2004-15
8 ZHANG Lin1,2,LIU Xian-shan3,YIN He-jun1 (1.Institute of Electronics,ChineseAcademy of Sciences,Haidian District,Beijing 100080,China;2.Graduate School of the Chinese Academy of Science,Haidian District,Beijing 100080,China;3.State Key Laboratory of Hydropower Engineering Science,Wuhan University,Wuhan 430072,Hubei Province,China);APPLICATION OF SUPPORT VECTOR MACHINES BASED ON TIME SEQUENCE IN POWER SYSTEM LOAD FORECASTING[J];Power System Technology;2004-19
9 PAN Feng1,CHENG Hao-zhong1,YANG Jing-fei1,ZHANG Cheng2,PAN Zhen-dong2 (1.Dept. of Electrical Engineering,Shanghai Jiaotong University,Xuhui District,Shanghai 200030,China; 2.Changzhou Power Supply Company,Changzhou 213003,Jiangsu Province,China);POWER SYSTEM SHORT-TERM LOAD FORECASTING BASED ON SUPPORT VECTOR MACHINES[J];Power System Technology;2004-21
10 YUE You-xi, WANG Yong-gang, ZHANG Jun-hua;PREDICTION METHOD EVALUATION OF RESERVOIR PARAMETER'S PLANE DISTRIBUTION[J];Geology and Prospecting;2001-05
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved