丁世飛，男，出生在山東青島，是一名研究員，現(xiàn)任職于中國礦業(yè)大學(xué)。

中文名

丁世飛

性別

男

籍貫

山東青島

民族

漢族

國籍

中國

出生地

山東省青島市

信仰

無

畢業(yè)院校

中國科學(xué)院計算技術(shù)研究所

職業(yè)

教師

任職機構(gòu)

中國礦業(yè)大學(xué)

代表作品

孿生支持向量機：算法與拓展

職稱

教授

學(xué)位

中國科學(xué)院計算所博士后

主要成就

全國智能信息處理學(xué)術(shù)會議（NCIIP）程序委員會主席

人物簡介

中國科學(xué)院計算技術(shù)研究所客座研究員、博士生導(dǎo)師

中國礦業(yè)大學(xué)教授、博士生導(dǎo)師

中國礦業(yè)大學(xué)計算機應(yīng)用技術(shù)博士點學(xué)科帶頭人

中國礦業(yè)大學(xué)計算機科學(xué)與技術(shù)學(xué)院教授委員會主任

中國礦業(yè)大學(xué)-中國科學(xué)院智能信息處理聯(lián)合實驗室負(fù)責(zé)人

學(xué)術(shù)兼職

擔(dān)任下列專家委員會委員：

（1）中國計算機學(xué)會杰出會員、資深會員

（2）中國計算機學(xué)會理事

（3）中國人工智能學(xué)會理事

（4）中國計算機學(xué)會人工智能與模式識別專委會委員

（5）中國計算機學(xué)會多值邏輯與模糊邏輯專委會常委委員

（6）中國人工智能學(xué)會知識工程與分布式智能專業(yè)委員會委員

（7）中國人工智能學(xué)會機器學(xué)學(xué)習(xí)專業(yè)委員會委員

（8）中國人工智能學(xué)會粒計算與知識發(fā)現(xiàn)專業(yè)委員會常委委員

（9）江蘇省計算機學(xué)會人工智能專業(yè)委員會常委委員

（10）江蘇省計算機學(xué)會大數(shù)據(jù)專家委員會委員

（11）江蘇省人工智能學(xué)會理事

（12）江蘇省人工智能學(xué)會機器學(xué)習(xí)專委會副主任委員

擔(dān)任下列國際期刊編委：

（1）《IJCI: International Journal of Collaborative Intelligence》主編

（2）《JDCTA: Journal of Digital Contents Technology and Application》副主編

（3）《JCIT: Journal of Convergence Information Technology》編委

（4）《AISS: Advances in Information Sciences and Service Sciences》編委

（5）《IJACT: International Journal of Advancements in Computing Technology》編委

（6）《JCP: Journal of Computers》編委

（7）《JSW: Journal of Software》編委

（8）《IPL:CInformation Processing Letters》編委

（9）《AMIS: Applied Mathematics & Information Sciences》編委

擔(dān)任下列國際期刊特約編輯：

（1）《Applied Mathematics & Information Sciences》特約編輯(Guest Editor)

（2）《INFORMATION》的特約編輯(Guest Editor)

（3）《Neurocpmputing》特約編輯(Guest Editor)

（4）《The Scientific World Journal》的特約編輯(Guest Editor)

（5）《Mathematical Problems in Engineering》的特約編輯(Guest Editor)

（6）《Journal of Computers (JCP)》特約編輯(Guest Editor)

（7）《Journal of Software (JSW)》特約編輯(Guest Editor)

（8）《Journal of Networks (JNW)》的特約編輯(Guest Editor)

擔(dān)任下列國際SCI源刊特約審稿專家：

（1）《Journal of Information Science》

（2）《Applied Soft Computing》

（3）《Information Sciences》

（4）《Computational Statistics and Data Analysis》

（5）《IEEE Transactions on Fuzzy Systems》

（6）《International Journal of Pattern Recognition and Artificial Intelligence》

（7）《Neurocpmputing》

（8）《Soft Computing》

（9）《Pattern Recognition》

（10）《Pattern Recognition Letters》

擔(dān)任下列國內(nèi)核心期刊審稿專家：

（1）《計算機學(xué)報》

（2）《軟件學(xué)報》

（3）《計算機研究與發(fā)展》

（4）《中國科學(xué)》（中英文版）

（5）《電子學(xué)報》（中英文版）

（6）《模式識別與人工智能》

（7）《計算機科學(xué)》

（8）《小型微型計算機系統(tǒng)》

（9）《計算機應(yīng)用研究》

（10）《計算機工程與科學(xué)》

（11）《計算機工程與應(yīng)用》

（12）《計算機科學(xué)與探索》

（13）《微電子學(xué)與計算機》

擔(dān)任下列國內(nèi)外會議PC Chair or Member：

（1）全國智能信息處理學(xué)術(shù)會議（NCIIP）程序委員會主席

（2）江蘇省人工智能學(xué)術(shù)會議程序委員會主席

（3）2012?3?4年信息、智能與計算國際研討會主席

（4）粒度計算國際會議程序委員會委員

（5）智能信息處理國際會議程序委員會委員

（6）中國機器學(xué)習(xí)會議程序委員會委員

（7）中國粗糙集與軟計算、中國粒計算、中國Web智能聯(lián)合會議程序委員會委員等

擔(dān)任下列項目評審專家：

（1）國家863、973項目評審專家

（2）國家自然科學(xué)獎、國家科技進(jìn)步獎、國家科技發(fā)明獎（三大獎）評審專家

（3）國家自然科學(xué)基金重點項目、面上項目、青年項目評審專家

研究方向

模式識別與人工智能

機器學(xué)習(xí)與數(shù)據(jù)挖掘

粒度計算與知識發(fā)現(xiàn)

感知與認(rèn)知計算

大數(shù)據(jù)智能分析

神經(jīng)網(wǎng)絡(luò)與深度學(xué)習(xí)

支持向量機與孿生支持向量機

科研項目

已經(jīng)完成的項目

1. 2001-2003參加并完成國家自然科學(xué)基金項目“信息模式識別理論及其在地學(xué)中的應(yīng)用”的研究（項目編號: 40074001）

2. 1999-2001主持完成省教育廳項目“信息模式識別理論及其在害蟲預(yù)測預(yù)報中的應(yīng)用研究”

3. 1998-2000主持完成省教育廳項目“農(nóng)作物病蟲害現(xiàn)代生物數(shù)學(xué)預(yù)報技術(shù)研究”

4. 2005-2006主持中國博士后科學(xué)基金項目“視感知學(xué)習(xí)理論及其應(yīng)用研究”（No.2005037439）

5. 2004-2006主持山東省作物生物學(xué)國家重點實驗室開放基金項目“山東省玉米病蟲害數(shù)字模式分類的研究”（No.20040010）

6. 2006-2008參加國家自然科學(xué)基金項目“多元數(shù)據(jù)的信息模式研究與地學(xué)數(shù)據(jù)分析”（No.40574001）

7. 2006-2009參加國家863高技術(shù)項目“基于感知機理的智能信息處理技術(shù)”(No. 2006AA01Z128)

8. 2007-2010主持中國科學(xué)院智能信息處理重點實驗室開放基金項目“基于認(rèn)知的模式特征分析理論與算法研究”(No.IIP2006-2)

9. 2010-2012主持江蘇省基礎(chǔ)研究計劃（自然科學(xué)基金）項目“面向高維復(fù)雜數(shù)據(jù)的粒度知識發(fā)現(xiàn)研究”(No.BK2009093)

10.2011-2012主持北京郵電大學(xué)智能通信軟件與多媒體北京市重點實驗室開放課題“粒度SVM方法與應(yīng)用研究”

11. 2010-2012參加國家自然科學(xué)基金項目“分布式計算環(huán)境下的并行數(shù)據(jù)挖掘算法與理論研究”(No.60975039)

12. 2011-2013主持中國科學(xué)院智能信息處理重點實驗室開放基金項目“高維復(fù)雜數(shù)據(jù)的粒度支持向量機理論與算法研究”(No.IIP2010-1)

正在進(jìn)行的項目

1. 2013.1-2017.12主持國家重點基礎(chǔ)研究發(fā)展計劃（973計劃）課題“腦機協(xié)同的認(rèn)知計算模型”(No.2013CB329502)[1]

2. 2014.1-2017.12主持國家自然科學(xué)基金項目“面向大規(guī)模復(fù)雜數(shù)據(jù)的多粒度知識發(fā)現(xiàn)關(guān)鍵理論與技術(shù)研究” (No. 61379101)[2]

3. 2017.1-2020.12，主持中央高?；緲I(yè)務(wù)費學(xué)科重點項目“基于大數(shù)據(jù)?；亩嗔６鄬由窠?jīng)網(wǎng)絡(luò)及其優(yōu)化方法研究”(No.2017XKZD03)[3]

論文著作

已出版著作

1.

丁世飛

,靳奉祥，趙相偉著. 現(xiàn)代數(shù)據(jù)分析與信息模式識別. 北京:

科學(xué)出版社

,2012

2.

丁世飛

編著. 人工智能. 北京:

清華大學(xué)出版社

, 2010

3.

丁世飛

編著。人工智能（第2版）. 北京:

清華大學(xué)出版社

, 2015

4.

丁世飛

編著. 高級人工智能. 徐州:

中國礦業(yè)大學(xué)出版社

, 2015

5.

丁世飛

著. 孿生支持向量機：理論與拓展. 北京:

科學(xué)出版社

, 2017[4]

已發(fā)表論文

2017年

國內(nèi)期刊

曾凱,

丁世飛

. 圖像超分辨率重建的研究進(jìn)展.

計算機工程與應(yīng)用

, 2017, 53(16):29-35.

丁世飛

,張楠，史忠植. 拉普拉斯極速學(xué)習(xí)機.

軟件學(xué)報

,2017,28(10):2599-2610.

丁世飛

,黃華娟。最小二乘孿生參數(shù)化不敏感支持向量回歸機.

軟件學(xué)報

, 2017, 28(12):3146?3155.

國際SCI期刊

Jian Zhang,

Shifei Ding

, Yu Xue. Weight Uncertainty in Boltzmann Machine.

Cognitive Computation

, 2016, 8(6): 1064-1073

Xiekai Zhang,

Shifei Ding

, Yu Xue. An improved multiple birth support vector machine for pattern classification.

Neurocomputing

, 2017, 225:119-128

Shifei Ding

, Yuexuan An, Xiekai Zhang, Yu Xue. Wavelet Twin Support Vector Machines based on Glowworm Swarm Optimization.

Neurocomputing

, 2017, 225:157-163

Nan Zhang,

Shifei Ding

, Jian Zhang, Yu Xue. Research on Point-wise Gated Deep Networks,

Applied Soft Computing,

2017,52:1210–1221

Shifei Ding

, Xiekai Zhang, Yuexuan An, Yu Xue. Weighted linear loss multiple birth support vector machine based on information granulation for multi-class classification.

Pattern Recognition

, 2017,67:32-46

Weixin Bian,

Shifei Ding

,Yu Xue.Combining weighted linear project analysis with orientation diffusion for fingerprint orientation field reconstruction.

Information Sciences

,2017,396:55-71

Shifei Ding

, Lingheng Meng, Youzhen Han, Yu Xue. A Review on Feature Binding Theory and Its Functions Observed in Perceptual Process.

Cognitive Computation

,2017,9(2):194-206

Nan Zhang,

Shifei Ding

. Unsupervised and semi-supervised extreme learning machine with wavelet kernel for high dimensional data.

Memetic Computing

, 2017,8(2)

Shifei Ding

, Nan Zhang, Jian Zhang, Xinzheng Xu, Zhongzhi Shi. Unsupervised extreme learning machine with representational features.

International Journal of

Machine Learning

and Cybernetics

, 2017, 8(2):587-595

Shifei Ding

, Zhibin Zhu, Xiekai Zhang. An overview on semi-supervised support vector machine.

Neural Computing and Applications

, 2017, 28(5): 969-978

Shifei Ding

, Lili Guo, Yalu Hou. Extreme learning machine with kernel model based on deep learning.

Neural Computing and Applications

, 2017, 28(8):1975-1984

Mingjing Du,

Shifei Ding

, Yu Xue. A novel density peaks clustering algorithm for mixed data.

Pattern Recognition Letters

, 2017, 97:46-53

Shifei Ding

, Mingjing Du, Tongfeng Sun, Xiao Xu, Yue Xue. An entropy-based density peaks clustering algorithm for mixed type data employing fuzzy neighborhood.

Knowledge-Based Systems

, 2017, 133:294-313

Shifei Ding

, Weixin Bian, Tongfeng Sun, Yu Xue. Fingerprint enhancement rooted in the spectra diffusion by the aid of the 2D adaptive Chebyshev band-pass filter with orientation-selective.

Information Sciences

, 2017, 415-416:233-246

Lingheng Meng,

Shifei Ding

, Yu Xue. Research on denoising sparse autoencoder. I

nternational Journal of Machine Learning and Cybernetics

, 2017, 8(5):1719-1729

Weixin Bian,

Shifei Ding

, Yu Xue. Fingerprint image super resolution using sparse representation with ridge pattern prior by classification coupled dictionaries.

IET Biometrics

, 2017, 6(5):342-350

Hongjie Jia,

Shifei Ding

, Mingjing Du. A Nystr?m Spectral Clustering Algorithm Based on Probability Incremental Sampling.

Soft Computing

,2017,21(19):5815–5827

Shifei Ding

, Nan Zhang, Xiekai Zhang, Fulin Wu. Twin support vector machine: theory, algorithm and applications.

Neural Computing and Applications

, 2017, 28(11):3119-3130

Shifei Ding

, Weixin Bian, Hongmei Liao, Tongfeng Sun, Yu Xue. Combining Gabor filtering and classification dictionaries learning for fingerprint enhancement.

IET Biometrics

, 2017,6(6):438-447[5]

2016年

國內(nèi)期刊

張謝鍇,

丁世飛

. 基于馬氏距離的孿生支持向量.

計算機科學(xué)

, 2016, 43(3):49-53

樊淑炎,

丁世飛

. 基于多尺度的改進(jìn)Graph cut算法.

山東大學(xué)學(xué)報(工學(xué)版)

, 2016, 46 (1): 28-33

孟令恒,

丁世飛

. 基于單靜態(tài)圖像的深度感知模型研究.

山東大學(xué)學(xué)報(工學(xué)版)

, 2016, 46(3):37-43

朱強波,

丁世飛

. 基于GA優(yōu)化自適應(yīng)NSCT-PCNN圖像融合.

小型微型計算機系統(tǒng)

, 2016

37 (7): 1583-1587.

馬恒,

丁世飛

. 一種基于混合數(shù)據(jù)的相似性度量的譜聚類算法.

小型微型計算機系統(tǒng)

, 2016, 37 (8): 1751-1754.

王婷婷,

丁世飛

. 基于資格跡的RBF非線性強化學(xué)習(xí)研究.

小型微型計算機系統(tǒng)

, 2016, 37 (7): 1508-1512

國際SCI期刊

Shifei Ding

, Mingjing Du, Hong Zhu. Survey on Granularity Clustering.

Cognitive Neurodynamics

. 2015, 9(6):561-572

Nan Zhang,

Shifei Ding

, Zhongzhi Shi. Denoising Laplacian multi-layer extreme learning machine.

Neurocomputing

, 2016, 171: 1066-1074

Jian Zhang,

Shifei Ding

, Nan Zhang, Zhongzhi Shi. An Incremental Extreme Learning Machine Based on Deep Feature Embedded.

International Journal of MachineLearning and Cybernetics

, 2016, 7(1):111-120

Shifei Ding

, Jian Zhang, Hongjie Jia, Jun Qian. An Adaptive Density Data Stream Clustering Algorithm.

Cognitive Computation

, 2016, 8(1):30-38

Shifei Ding

, Xiekai Zhang, Junzhao Yu. Twin support vector machines based on fruit fly optimization algorithm.

Journal International Journal of Machine Learning and Cybernetics

, 7(2):193-203

Xiekai Zhang,

Shifei Ding

, Tongfeng Sun. Multi-class LSTMSVM based on optimal directed acyclic graph and shuffled frog leaping algorithm.

International Journal of MachineLearning and Cybernetics

, 2016, 7(2): 241-251

Nan Zhang,

Shifei Ding

. Multi Layer ELM-RBF for Multi-Label Learning.

Applied Soft Computing

, 2016, 43:535-545

Mingjing Du,

Shifei Ding

, Hongjie Jia. Study on Density Peaks Clustering Based on k-Nearest Neighbors and Principal Component Analysis.

Knowledge-Based Systems

, 2016, 99:135-145

Shifei Ding

, Jian Zhang, Xinzheng Xu, Yanan Zhang. A Wavelet Extreme Learning Machine.

Neural Computing and Applications

, 2016, 27(4):1033-1040

Li Xu,

Shifei Ding

, Xinzheng Xu, Nan Zhang. Self-adaptive Extreme Learning Machine Optimized by Rough Set Theory and Affinity Propagation Clustering.

Cognitive Computation

, 8(4):720-728

Hongmei Liao,

Shifei Ding

, Miaomiao Wang, Gang Ma. An Overview on Rough Neural networks.

Neural Computing and Applications

, 2016, 27(7): 1805–1816

Hongjie Jia,

Shifei Ding

, Mingjing Du, Yu Xue. Approximate normalized cuts without Eigen-decomposition.

Information Sciences

, 2016, 374:135-150

Shifei Ding

, Zhongzhi Shi, Dacheng Tao, Bo An. Recent Advances in Support Vector Machines.

Neurocomputing

, 2016, 211:1-3

Hui Li, Xuesong Wang,

Shifei Ding

. Research of multi-sided multi-granular neural network ensemble optimization method.

Neurocomputing

, 2016, 197:78-85

Guanying Wang, Xinzheng Xu, Xiangying Jiang,

Shifei Ding

. Medical image registration based on self-adapting pulse-coupled neural networks and mutual information.

Neural Computing and Applications

, 2016, 27(7): 1917-1926

Tongfeng Sun,

Shifei Ding

, Wei Chen, Xinzheng Xu. No-reference image quality assessment based on gradient histogram response.

Computers & Electrical Engineering

, 2016, 54:330-344[5]

2015年

國內(nèi)期刊

鮑麗娜,

丁世飛

, 許新征, 孫統(tǒng)風(fēng)?；卩徲虼植诩臉O速學(xué)習(xí)計算法.濟南大學(xué)學(xué)報.

自然科學(xué)版

, 2015, 29(5):367-371

花小朋,

丁世飛

. 基于魯棒局部嵌入的孿生支持向量機.

中南大學(xué)學(xué)報(自然科學(xué)版)

, 2015, 46(1):149-156

黃華娟,

丁世飛

, 史忠植. 光滑CHKS孿生支持向量回歸機.

計算機研究與發(fā)展

, 2015, 52(3): 569-578

郭麗麗,

丁世飛

. 深度學(xué)習(xí)研究進(jìn)展.

計算機科學(xué)

, 2015, 42(5):28-33. [2015.5]

賈洪杰,

丁世飛

, 史忠植. 求解大規(guī)模譜聚類的近似加權(quán)核k-means算法.

軟件學(xué)報

, 2015, 26(11):2836?2846

國際SCI期刊

Shifei Ding

, Zhongzhi Shi, Ke Chen, Ahmad T. Azar. Mathematical Modeling and Analysis of Soft Computing.

Mathematical Problems in Engineering

, vol.2015, Article ID 578321, 2 pages, 2015. doi:10.1155/2015/578321

Shifei Ding

, Han Zhao, Yanan Zhang, Xinzheng Xu, Ru Nie. Extreme Learning Machine algorithm Theory and Applications.

Artificial Intelligence Review

, 2015, 44(1): 103-115

Shifei Ding

,Nan Zhang,Xinzheng Xu, Lili Guo,and Jian Zhang. Deep Extreme Learning Machine and Its Application in EEG Classification.

Mathematical Problems in Engineering

Volume 2015 (2015), Article ID 129021, 11 pages (http://dx.doi.org/10.1155/2015/129021)

Hongjie Jia,

Shifei Ding

, Mingjing Du. Self-Tuning p-Spectral Clustering Based on Shared Nearest Neighbors.

Cognitive Computation

, 2015,7(5):622-632

Shifei Ding

, Mingjing Du, Hong Zhu. Survey on Granularity Clustering.

Cognitive Neurodynamics

. 2015, 9(6):561-572

Wang Guanying,

Ding Shifei

, Jiang, Xiangying, Zhao, Zuopeng. A new method for constructing granular neural networks based on rule extraction and extreme learning machine.

Pattern Recognition Letters

, 2015,67:138-144

Weikuan JIa, Dean Zhao, Tian Shen,

Shifei Ding

, Yuyan Zhao, Chanli Hu. An optimized classification algorithm by BP neural network based on PLS and HCA.

Applied Intelligence

, 2015, 43(1):176-191

Liao Hongmei,

Ding Shifei

. Mixed and Continuous strategy Monitor-Forward Game based Selective Forwarding Solution in WSN.

International Journal of Distributed Sensor Networks

, 2015 (10.1155/2015/359780)

Shifei Ding

, Hui Li. Twice clustering based individual neural network generation method.

Neurocomputing

, 2015, 157, 264-272

Xiaopeng Hua,

Shifei Ding

. Weighted least squares projection twin support vector machines with local information.

Neurocomputing

, 2015, 160:228-237

Shifei Ding

, Huanjuan Huang, Junzhao Yu, Han Zhao. Research on the hybrid models of granular computing and support vector machine.

Artificial Intelligence Review

, 2015,43(4):565-577

Shifei Ding

, Fulin Wu, Jun Qian, Hongjie Jia, Fengxiang Jin. Research on data stream clustering algorithm.

Artificial Intelligence Review

, 2015, 43(4): 593-600

2014年

Shifei Ding

, Hongjie Jia, Liwen Zhang, Fengxiang Jin. Research of semi-supervised spectral clustering algorithm based on pairwise constraints.

Neural Computing and Applications

, 2014,24(1):211-219.

(SCI, EI)

Shifei Ding

, Hongjie Jia, Jinrong Chen, Fengxiang Jin. Granular Neural Networks.

Artificial Intelligence Review

, 2014,41(3): 373-384.

(SCI, EI)

Shifei Ding

, Huajuan Huang, Xinzheng Xu, Jian Wang. Polynomial Smooth Twin Support Vector Machines.

Applied Mathematics & Information Sciences

, 2014, 8(4)

(SCI,EI)

Shifei Ding

, Zhongzhi Shi. Track on Intelligent Computing and Applications.

Neurocomputing

, 2014, vol.130, 1-2.

(SCI, EI)

Shifei Ding

, Xiaopeng Hua. Recursive least squares projection twin support vector machines.

Neurocomputing

, 2014, vol.130, 3-9.

(SCI, EI)

花小朋,

丁世飛.

局部保持對支持向量機.

計算機研究與發(fā)展

,

2014, 51(3)

(EI)

2013年

Xinzheng Xu,

Shifei Ding

, Weikuan Jia, Gang Ma, Fengxiang Jin. Research of assembling optimized classification algorithm by neural network based on Ordinary Least Squares (OLS).

Neural Computing and Applications

, 2013,22(1):187-193.

(SCI, EI)

Shifei Ding

, Hui Li, Chunyang Su, Junzhao Yu, Fengxiang Jin. Evolutionary artificial neural networks: a review.

Artificial Intelligence Review

, 2013, 39(3):251-260.

(SCI, EI)

Li Hui,

Ding Shifei

. Research of Individual Neural Network Generation and Ensemble Algorithm Based on Quotient Space Granularity Clustering.

Applied Mathematics & Information Sciences

, 2013, 7(2):701-708.

(SCI, EI)

Hui Li,

Shifei Ding

. Research and Development of Granular Neural Networks.

Applied Mathematics & Information Sciences

, 2013, 7(3):1251-1261.

(SCI, EI)

Shifei Ding

, Bingjuan Qi, Hongjie Jia, Hong Zhu. Research of Semi-supervised Spectral Clustering Based on Constraints Expansion.

Neural Computing and Applications

, 2013, 22 (Suppl 1):405-410.

(SCI, EI)

Shifei Ding

, Yanan Zhang, Jinrong Chen, Weikuan Jia. Research on Using Genetic Algorithms to Optimize Elman Neural Networks.

Neural Computing and Applications

, 2013, 23(2):293-297.

(SCI, EI)

Hua-juan Huang,

Shi-fei Ding

, Zhong-zhi Shi. Primal least squares twin support vector regression.

Journal of Zhejiang University SCIENCE C

, 2013, 14(9):722-732.

(SCI, EI)

Shifei Ding,

Youzhen Han, Junzhao Yu, Yaxiang Gu. A fast fuzzy support vector machine based on information granulation.

Neural Computing and Applications

, 2013, 23(suppl 1):S139-S144

(SCI, EI)

黃華娟,

丁世飛

.多項式光滑孿生支持向量回歸機.

微電子學(xué)與計算機

, 2013, 30(10):5-8.

丁世飛

,黃華娟. 加權(quán)光滑CHKS孿生支持向量機.

軟件學(xué)報

, 2013, 24(11):2548-2557.

賈洪杰,

丁世飛

.基于鄰域粗糙集約減的譜聚類算法.

南京大學(xué)學(xué)報。自然科學(xué)版

,2013, 49(5):619-627.

Hong Zhu,

Shifei Ding

, Xinzheng Xu, Li Xu. A parallel attribute reduction algorithm based on Affinity Propagation clustering.

Journal of Computers

, 2013, 8(4):990-997.

(EI)

Hong Zhu,

Shifei Ding

, Han Zhao, Lina Bao. Attribute granulation based on attribute discernibility and AP algorithm.

Journal of Software

, 8(4):834-841.

(EI)

Yanan Zhang,

Shifei Ding

, Xinzheng Xu, Han Zhao, Wanqiu Xing. An Algorithm Research for Prediction of Extreme Learning Machines Based on Rough Sets.

Journal of Computers

, 2013, 8(5): 1335-1342.

(EI)

Hui Li,

Shifei Ding

. A Novel Neural Network Classification Model based on Covering and Affinity Propagation Clustering Algorithm.

Journal of Computational Information Systems

, 2013, 9(7):2565-2573.

(EI)

Shifei Ding

, Junzhao Yu, Huajuan Huang, Han Zhao. Twin Support Vector Machines Based on Particle Swarm Optimization.

Journal of Computers

, 2013, 8(9): 2296-2303.

(EI)

Huajuan Huang,

Shifei Ding

, Fulin Wu. Invasive Weed Optimization Algorithm for Optimizating the Parameters of Mixed Kernel Twin Support Vecotr Machines.

Journal of Computers

, 2013, 8(8): 2077-2084.

(EI)

Hongjie Jia,

Shifei Ding

, Hong Zhu, Fulin Wu, Lina Bao. A Feature Weighted Spectral Clustering Algorithm Based on Knowledge Entropy.

Journal of Software

, 2013, 8(5): 1101-1108.

(EI)

Tongfeng Sun,

Shifei Ding

, Zihui Ren Novel Image Recognition Based on Subspace and SIFT.

Journal of Software

, 2013, 8(5): 1109-1116.

(EI)

Shifei Ding

, Fulin Wu, Ru Nie, Junzhao Yu, Huajuan Huang. Twin Support Vector Machines Based on Quantum Particle Swarm Optimization.

Journal of Software

, 2013, 8(7): 1743-1750.

(EI)

Ding Shifei

, Zhang Yanan, Xu Xinzheng, Bao Lina. A novel extreme learning machine based on hybrid kernel function.

Journal of Computers

,2013, 8(8):2110-2117.

(EI)

Shifei Ding

, Huajuan Huang, Ru Nie. Forecasting Method of Stock Price Based on Polynomial Smooth Twin Support Vector Regression

.

Lecture Notes in Computer Science

, 2013, Volume 7995, 2013, pp 96-105.

(EI)

2012年

Shifei Ding

, Hong Zhu,Weikuan Jia,Chunyang Su. A survey on feature extraction for pattern recognition.

Artificial Intelligence Review

,2012, 37(3):169-180.

(SCI, EI)

Shifei Ding

,Li Xu,Chunyang Su,Fengxiang Jin. An optimizing method of RBF neural network based on genetic algorithm.

Neural Computing and Applications

, 2012, 21(2):333-336.

(SCI, EI)

Shifei Ding

,Bingjuan Qi. Research Of granular support vector machine.

Artificial Intelligence Review

, 2012, 38(1):1-7.

(SCI, EI)

Xin-zheng XU,

Shi-fei DING

, Zhong-zhi SHI, Hong ZHU. Optimizing radial basis function neural network based on rough sets and affinity propagation clustering algorithm.

Journal of Zhejiang University-SCIENCE C

(Computers & Electronics), 2012,13(2):131-138.

(SCI, EI)

Bingjuan Qi,

Shifei Ding

, Huajuan Huang, Junzhao Yu. A Support Vector Extraction Method based on Clustering Membership.

International Journal of Digital Content Technology and its Applications

, 2012, 6(13):1-10.

(EI)

Chang Tong,

Shi-fei Ding

, Hong Zhu, Hongjie Jia. A Granularity Attribute Reduction Algorithm Based on Binary Discernibility Matrix.

International Journal of Advancements in Computing Technology

, 2012, 4(12):213-221.

(EI)

Xiaopeng Hua,

Shifei Ding

. Matrix Pattern Based Projection Twin Support Vector Machines.

International Journal of Digital Content Technology and its Applications

, 2012, 6(20):172-181.

(EI)

Junzhao Yu,

Shifei Ding

, Huajuan Huang. Twin Support Vector Machines Based on Rough Sets.

International Journal of Digital Content Technology and its Applications

, 2012, 6(20):493-500.

(EI)

Huajuan Huang,

Shifei Ding

. A Novel Granular Support Vector Machine Based on Mixed Kernel Function.

International Journal of Digital Content Technology and its Applications

, 2012, 6(20):484-492.

(EI)

Shifei Ding

(Guest editorial). Special Issue: Advances in Information and Computers,

Journal of Computers

, 2012, 7(10):2351-2353.

(EI)

Shifei Ding

(Guest editorial). Special Issue: Advances in Information and Networks.

Journal of Networks

, 2012, 7(7):1007-1008.

(EI)

(被EI收錄, 收錄號:

20123415368412)

Shifei Ding

(Guest editorial). Special Issue: Advances in Information and Networks.

Journal of Software

, 7(9):1923-1924.

(EI)

Shifei Ding

, Zhentao Yu (Guest editorial). Special Issue: Advances in Computers and Electronics Engineering.

Journal of Computers

, 2012, 7(12):2851-2852.

(EI)

丁世飛

, 朱紅, 許新征, 史忠植. 基于熵的模糊信息測度研究.

計算機學(xué)報

, 2012.35(4):796-801

(EI).

朱紅,

丁世飛

, 許新征. 基于改進(jìn)屬性約簡的細(xì)粒度并行AP聚類算法.

計算機研究與發(fā)展

, 2012, 49(12):2638-2644

(EI)

許新征,

丁世飛

,史忠植，趙作鵬，朱紅。一種基于QPSO的脈沖耦合神經(jīng)網(wǎng)絡(luò)參數(shù)的自適應(yīng)確定方法.

模式識別與人工智能

, 2012,25(6): 909-915

(EI

)

馬剛,

丁世飛

, 史忠植. 基于極速學(xué)習(xí)的粗糙RBF神經(jīng)網(wǎng)絡(luò).

微電子學(xué)與計算機

,

2012, 29(8):9-14.

2011年

Shifei Ding

, Weikuan Jia, Chunyang Su, et al. Research of Neural Network Algorithm Based on Factor Analysis and Cluster Analysis.

Neural Computing and Applications

, 2011, 20(2): 297-302

(SCI,EI).

Shifei Ding

, Chunyang Su, Junzhao Yu. An Optimizing BP Neural Network Algorithm Based on Genetic Algorithm.Artificial Intelligence Review, 2011, 36Algorithm.

Artificial Intelligence Review

, 2011, 36(2): 153-162

(SCI, EI).

Ding Shifei

, Qian Jun, Xu Li, Zhao Xiangwei, Jin Fengxiang. A Clustering Algorithm Based on Information Visualization.

International Journal of Digital Content Technology and its Applic

ations

, 2011, 5(1): 26-31

(EI).

Shifei Ding

, Yu Zhang, Li Xu, Jun Qian. A Feature Selection Algorithm Based on Tolerant Granule.

Journal of Convergence Information Technology,

2011, 6(1): 191-195

(EI).

Ding Shifei

, Li Jianying, Xu Li, Qian Jun. Research Progress of Granular Computing (GrC).

International Journal of Digital Content Technology and its Applications

, 2011, 5(1): 162-172

(EI).

Shifei DING

, Jinrong CHEN, Xinzheng XU, Jianying LI. Rough Neural Networks: A review.

Journal of Computational Information Systems

, 2011, 7(7): 2338-2346

(EI).

Shifei Ding

, Xinzheng Xu, Hong Zhu. Studies on Optimization Algorithms for Some Artificial Neural Networks Based on Genetic Algorithm (GA).

Journal of Computers

, 2011, 6 (5):939-946

(EI).

Shifei DING

, Yaxiang GU. A Fuzzy Support Vector Machine Algorithm with Dual Membership Based on Hypersphere.

Journal of Computational Information Systems

, 2011, 7(6): 2028-2034

(EI).

丁世飛

, 齊丙娟, 譚紅艷. 支持向量機理論與算法研究綜述.

電子科技大學(xué)學(xué)報

,2011, 40(1): 2-10

(EI).

賈偉寬,

丁世飛,

許新征, 蘇春陽, 史忠植. 基于Shannon熵的因子特征提取算法研究.

模式識別與人工智能

, 2011, 24(3): 327-331

(EI).

2010年以前

Shifei Ding

, Weikuian Jia, Xinzheng Xu, et al. Neural Networks Algorithm Based on Factor Analysis.

Lecture Notes in Computer Science

, Vol.6063/2010, pp.319-324

(EI).

Shifei Ding

, Weikuan Jia, Chunyang Su, et al. An improved BP Neural Netwok Algorithm Based on Factor Analysis.

Journal of Convergence Information Technology

, 2010, 5(4): 103-108

(EI).

Shifei Ding

, Li Xu, Hong Zhu, Liwen Zhang. Research and Progress of Cluster Algorithms based on Granular Computing.

International Journal of Digital Content Technology and its Applications

, 2010, 4(5): 96-104

(EI).

Shifei Ding

, Li Xu, Chunyang Su, Hong Zhu. Using Genetic Algorithms to Optimize Artificial Neural Networks,

Journal of Convergence Information Technology

, 2010, 5(8): 54-62

(EI).

Shifei Ding

, Yongping Zhang, Xiaofeng Lei et al. Research on a principal components decision algorithm based on information entropy.

Journal of Information Science

, 2009, 35(1):120-127

(SCI, EI).

Shifei Ding

, Chunyang Su, Weikuan Jia, Fengxiang Jin, Zhongzhi Shi. Several Progress of Semi-Supervised Learning.

Journal of Information & Computational Science

, 2009, 6(1): 211-217

(EI).

Shi-Fei Ding

, Shi-Xiong Xia, Feng-Xiang Jin, Zhong-Zhi Shi. Novel Fuzzy Information Proximity Measures.

Journal of Information Science

, 2007, 33 (6):678-685

(SCI, EI).

Ding Shifei,

Shi Zhongzhi. Supervised Feature Extraction Algorithm Based on Improved Polynomial Entropy.

Journal of Information Science

, 32(4): 309-315,2006.8

(SCI, EI)

Ding Shifei

, Shi Zhongzhi. Studies on Incidence Pattern Recognition Based on Information Entropy.

Journal of Information Science

, 31(6):497-502,2005.12

(SCI, EI).

Ding Shifei

, Jin Fengxiang. Information characteristics of discrete K-L transform based on information entropy.

Transactions Nonferrous Metals Society of China

, 2003.6

(SCI ,EI).

Shifei Ding

, Zhongzhi Shi, Xiaoying Wang. Symmetric Cross Entropy and Information Feature Compression Algorithm.

Journal of Computational Information Systems

, 1(2): 247-252 , 2005.6

(EI).

Ding Shifei

, Shi Zhongzhi. Studies on Information Clustering Algorithm Based on MID.

Chinese Journal of Electronics

, Vol.15 No.4A, pp.918-920, 2006

(SCI, EI).

Ding Shifei

, Shi Zhongzhi. Divergence-based Supervised Information Feature Compression Algorithm.

Lecture Notes in Computer Science

, Vol. 3971/2006, pp. 1421-1426

(SCI, EI).

Shifei Ding

, Zhongzhi Shi. A Novel Supervised Information Feature Compression Algorithm.

Lecture Notes in Computer Science

, Vol. 3991/2006, pp. 777-780

(SCI, EI).

Shifei Ding

, Zhongzhi Shi, Yuncheng Wang,and Fengxiang Jin. Optimization Feature Compression and FNN Realization.

Lecture Notes in Control and Information Science

, Vol. 344/2006, pp. 951-956

(SCI, EI).

Shifei Ding

, Zhongzhi Shi, and Fengxiang Jin. Supervised Feature Extraction Algorithm Based on Continuous Divergence Criterion.

Lecture Notes in Artificial Inteligence

, Vol. 4114/2006, pp.268-277

(SCI, EI).

丁世飛

, 賈偉寬, 許新征, 蘇春陽. 基于PLS的Elman神經(jīng)網(wǎng)絡(luò)算法研究.

電子學(xué)報

, 2010, 38(2A): 71-75

(EI).

許新征,

丁世飛

, 史忠植, 賈偉寬. 圖像分割的新理論何新方法.

電子學(xué)報

, 2010, 38(2A): 76-82

(EI).

丁世飛

,靳奉祥. Fuzzy-Grey信息集成模式識別算法的研究.計算機輔助設(shè)計與圖形學(xué)學(xué)報, 2004, 16(3):275-278

(EI).

丁世飛

,靳奉祥，史忠植. 基于PLS的信息特征壓縮算法.

計算機輔助設(shè)計與圖形學(xué)學(xué)報

, 2005, 17(2):368-371

(EI).

丁世飛

,史忠植. 基于廣義距離的直接聚類算法研究.

計算機研究與發(fā)展

，2007, 44(4): 674-679

(EI).

丁世飛

,黃華娟. 加權(quán)光滑CHKS孿生支持向量機. 軟件學(xué)報, 2013, 24(11):2548-2557

(EI)

.

獲獎情況

1. 2007年獲全國優(yōu)秀博士學(xué)位論文提名獎；

2. 2006年獲山東省優(yōu)秀博士學(xué)位論文獎；

3. 2007年獲山東高等學(xué)校優(yōu)秀科研成果二等獎，第1位；

4. 2006年獲中國科學(xué)院計算技術(shù)研究所優(yōu)秀博士后出站報告；

4. 2004年獲山東高等學(xué)校優(yōu)秀科研成果二等獎，第1位；

5. 2001年獲山東省省級教學(xué)成果三等獎，第4位；

6. 2016年獲江蘇省高等學(xué)校自然科學(xué)二等獎，第1位。