Research and Development of Granular Neural Networks

Granular neural networks(GNNs) as a new calculation system structure based on Granular Computing(GrC) and artificial neural network can be able to deal with all kinds of granular information of the real world. This article has made the summary on the development and the present situation of GNNs. Firstly, it introduces the basic model of GrC: word calculation model based on fuzzy sets theory, rough sets model, granular computing model based on quotient space theory and so on, summarizes the research progress of fuzzy neural networks(FNNs) and rough neural networks(RNNs), then analyses the ensemble-based methods of GNNs, researches their meeting point of three main GrC methods, and finally points out the research and development direction of GNNs.

[1]  Guochu Chen,et al.  Cultural Particle Swarm Optimization Neural Network and Its Application in Soft-Sensing Modeling , 2009, 2009 Fifth International Conference on Natural Computation.

[2]  Yi Zhao,et al.  The Study of the Gas Emission Prediction Model Based on Fuzzy-rough Set Neural Network , 2010, 2010 Second International Conference on Machine Learning and Computing.

[3]  Chen Dan.  A New Neuron Model Based on Weak T-Norm Cluster , 2001 .

[4]  Francis K. H. Quek,et al.  Attribute bagging: improving accuracy of classifier ensembles by using random feature subsets , 2003, Pattern Recognit..

[5]  Hong Zhu,et al.  Optimizing radial basis function neural network based on rough sets and affinity propagation clustering algorithm , 2012, Journal of Zhejiang University SCIENCE C.

[6]  Zhang Bo,et al.  Theory of Fuzzy Quotient Space (Methods of Fuzzy Granular Computing) , 2003 .

[7]  Haitao He,et al.  The Research on CMAC Network Model Based on Rough Sets for Flatness Control , 2009, 2009 Fourth International Conference on Innovative Computing, Information and Control (ICICIC).

[8]  Lotfi A. Zadeh,et al.  Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic , 1997, Fuzzy Sets Syst..

[9]  Yu Jiang-min.  Study of Fault Diagnosis Based on New Rough Set-Neural Networks , 2006 .

[10]  Yiyu Yao,et al.  Granular Computing: basic issues and possible solutions , 2007 .

[11]  Jeffrey James,et al.  An emerging paradigm , 2004 .

[12]  P. Lingras.  Rough Neural Networks , 1996 .

[13]  Andrzej Bargiela,et al.  General fuzzy min-max neural network for clustering and classification , 2000, IEEE Trans. Neural Networks Learn. Syst..

[14]  Ahmad Fadzil M. Hani,et al.  Missing Attribute Value Prediction Based on Artificial Neural Network and Rough Set Theory , 2008, 2008 International Conference on BioMedical Engineering and Informatics.

[15]  Abraham Kandel,et al.  Granular neural networks for numerical-linguistic data fusion and knowledge discovery , 2000, IEEE Trans. Neural Networks Learn. Syst..

[16]  Gao Xieping.  The Researching Development of Evolutionary Neural Networks , 2001 .

[17]  W. Pedrycz,et al.  OR/AND neuron in modeling fuzzy set connectives , 1994, IEEE Trans. Fuzzy Syst..

[18]  Xiangpeng Li,et al.  A Rough CP Neural Network Model Based on Rough Set , 2007, Third International Conference on Natural Computation (ICNC 2007).

[19]  Hu Li-hua.  Research Progress of Attribute Reduction Based on Rough Sets , 2010 .

[20]  Yao Wang.  The Researching Overview of Evolutionary Neural Networks , 2004 .

[21]  Jian Wang,et al.  A New Pattern Recognition Model based on Heuristic SOM Network and Rough Set Theory , 2006, 2006 IEEE International Conference on Vehicular Electronics and Safety.

[22]  Yu Dao-yuan,et al.  Particle Swarm Optimization Based Algorithm for Neural Network Learning , 2004 .

[23]  Bin Xie,et al.  The Evaluation and Application Research about Regional Innovation Capability Based on Rough Set and BP Neural Network , 2009, 2009 Second International Conference on Information and Computing Science.

[24]  Ye San,et al.  Rough set theory and its application in the intelligent systems , 2008, 2008 7th World Congress on Intelligent Control and Automation.

[25]  Yin Jia-wa.  Faults Diagnosis of Diesels Based on Rough Set Genetic Neural Networks , 2009 .

[26]  Zhang Ming-yuan.  A Model for Assessment of Earthquake Damages and Losses Based on Rough Genetic BP Networks , 2010 .

[27]  Witold Pedrycz,et al.  Granular Computing - The Emerging Paradigm , 2007 .

[28]  Hardwari Lal Mandoria,et al.  A Combined Classifier to Detect Landmines Using Rough Set Theory and Hebb Net Learning & Fuzzy Filter as Neural Networks , 2009, 2009 International Conference on Signal Processing Systems.

[29]  Saeed Gholizadeh,et al.  Optimum design of structures by an improved genetic algorithm using neural networks , 2005, Adv. Eng. Softw..

[30]  Jianying Li,et al.  Rough Neural Networks: A Review , 2011 .

[31]  Jing He,et al.  Decision Analysis of Combat Effectiveness Based on Rough Set Neural Network , 2008, 2008 Fourth International Conference on Natural Computation.

[32]  K. Thangavel,et al.  Dimensionality reduction based on rough set theory: A review , 2009, Appl. Soft Comput..

[33]  Vijay K. Rohatgi,et al.  Advances in Fuzzy Set Theory and Applications , 1980 .

[34]  Feng Xue,et al.  Five-Category Evaluation of Commercial Bank's Loan by the Integration of Rough Sets and Neural Network , 2008 .

[35]  Y. Yao.  Granular Computing : basic issues and possible solutions , 2000 .

[36]  Hu Qing,et al.  Efficient Symbolic and Numerical Attribute Reduction with Neighborhood Rough Sets , 2008 .

[37]  Wang Yaonan,et al.  Filtering image impulse noise based on fuzzy rough neural network , 2005 .

[38]  Krzysztof Krawiec,et al.  ROUGH SET REDUCTION OF ATTRIBUTES AND THEIR DOMAINS FOR NEURAL NETWORKS , 1995, Comput. Intell..

[39]  Lotfi A. Zadeh,et al.  Fuzzy sets and information granularity , 1996 .

[40]  Hu Qing,et al.  Numerical Attribute Reduction Based on Neighborhood Granulation and Rough Approximation , 2008 .

[41]  Wei Wang,et al.  The application of rough neural network in RMF model , 2010, 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010).

[42]  Lotfi A. Zadeh,et al.  Fuzzy logic = computing with words , 1996, IEEE Trans. Fuzzy Syst..

[43]  Prabir Kumar Biswas,et al.  A Granular Reflex Fuzzy Min–Max Neural Network for Classification , 2009, IEEE Transactions on Neural Networks.

[44]  Yanqing Zhang,et al.  Granular Neural Networks With Evolutionary Interval Learning , 2008, IEEE Transactions on Fuzzy Systems.

[45]  Jung-Hsien Chiang,et al.  A Combination of Rough-Based Feature Selection and RBF Neural Network for Classification Using Gene Expression Data , 2008, IEEE Transactions on NanoBioscience.

[46]  P.-Y. Glorennec.  Neuro-fuzzy logic , 1996, Proceedings of IEEE 5th International Fuzzy Systems.

[47]  Ling Jin-jiang.  Feature Selection Based Neural Network Ensemble Method , 2004 .

[48]  Soo Young Moon,et al.  Fuzzy Based Filtering Nodes Assigning Method for Sensor Networks , 2012 .

[49]  Yang Liu,et al.  Principle of Universal Logics , 2013 .

[50]  Chen Shi-fu,et al.  An Approach for Reduction of Continuous-Valued Attributes , 2005 .

[51]  Wang Yaonan,et al.  Fuzzy-rough Neural Network and Its Application to Vowel Recognition , 2006 .

[52]  Liu Xiao-ping.  Research and application of integration of RS and FNN in defect recognition of welding , 2009 .

[53]  Wei Gong.  Application of Rough Set and Fuzzy Neural Network in Information Handling , 2009, 2009 International Conference on Networking and Digital Society.

[54]  M Syeda,et al.  Parallel granular neural networks for fast credit card fraud detection , 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

[55]  Hong Zhu,et al.  Research and Development of Granularity Clustering , 2011 .

[56]  Chen You.  Dynamic evaluation method study of enterprise supply chain performance based on FCM , 2011 .

[57]  F. Zhang,et al.  Application of Quantum Neural Network Based on Rough Set in Transformer Fault Diagnosis , 2010, 2010 Asia-Pacific Power and Energy Engineering Conference.

[58]  Nan Jiang,et al.  A Study of Data Fusion Based on Combining Rough Set with BP Neural Network , 2009, 2009 Ninth International Conference on Hybrid Intelligent Systems.

[59]  Li Yi.  Application of fuzzy artmap for tone recognition of Chinese trisyllabic word , 2004 .

[60]  Huang Qinghua,et al.  Numerical Attribute Reduction Based on Neighborhood Granulation and Rough Approximation , 2008 .

[61]  Witold Pedrycz,et al.  Granular neural networks , 2001, Neurocomputing.

[62]  Guo Xian-sheng.  Design of Neural Network Controller Based on Rule Encoded by Rough Sets , 2006 .

[63]  Hu Jun.  An overview of granular computing , 2007 .

[64]  Wang Yaonan,et al.  Rough neural network and its application to intelligent (information) procession , 2005 .