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[10] ´÷Ⱥ A novel ensemble pruning algorithm based on randomized greedy selective strategy and ballot£¬Neurocomputing, 2013, 122(25)£¬ 258?265£¨SCIÊÕ¼£©¡£
[9] ´÷Ⱥ Back-propagation with diversive curiosity: An automatic conversion from search stagnation to exploration£¬Applied Soft Computing,13(1), 2013, 483?495£¨SCIÊÕ¼£©¡£
[8] ´÷Ⱥ A competitive ensemble pruning approach based on cross-validation technique£¬Knowledge-Based Systems,37, 2013, Pages 394?414£¨SCIÊÕ¼£©¡£
[7] ´÷Ⱥ*£¬ÁõÄþÖÓ Alleviating the problem of local minima in Backpropagation through competitive learning £¬Neurocomputing, 2012, 94(1)£¬ 152?158£¨SCIÊÕ¼£©
[6] ´÷Ⱥ*£¬ÁõÄþÖÓ The build of n-Bits Binary Coding ICBP Ensemble System£¬Neurocomputing, 2011, 74(17)£¬3509-3519£¨SCIÊÕ¼£©¡£
[5] ´÷Ⱥ£¬The Build of a Dynamic Classifier Selection ICBP System And its Application to Pattern Recognition£¬Neural Computing and Applications£¬2010£¬19(1)£¬123-137£¨SCIÊÕ¼£©¡£
[4] ´÷Ⱥ£¬³ÂËɲÓ*£¬Íõ?´£?CBP-SOM: A Hybrid Neural Network Architecture Based on SOM£¬Èí¼þѧ±¨£¬2009£¬05ÆÚ£¬1329-1336£¨EIÊÕ¼£©¡£
[3] ´÷Ⱥ£¬³ÂËɲÓ*£¬Integrating the improved CBP model with kernel SOM£¬Neurocomputing, 2006, 69(16-18)£¬2208-2216£¨SCIÊÕ¼£©¡£
[2] ´÷Ⱥ£¬³ÂËɲÓ*£¬Chained DLS-ICBP Neural Networks with Multiple Steps Time Series Prediction£¬Neural Processing Letters£¬2005, 21(2)£¬1370-4621£¨SCIÊÕ¼£©¡£
[1] ´÷Ⱥ£¬³ÂËɲÓ*£¬Improved CBP neural network model with applications in time series prediction£¬Neural Processing Letters, 2003£¬18(6), 197-211¡££¨SCIÊÕ¼£©¡£
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[9] Ò¶Èñ(2016˶),´÷Ⱥ*£¬A Novel Greedy Randomized Dynamic Ensemble Selection Algorithm,Neural Processing Letters,2017,DOI:10.1007/s11063-017-9670-y (SCIÔ´¿¯)
[8] Ëθգ¨2015˶),´÷Ⱥ*£¬A novel double deep ELMs ensemble system for time series forecasting,Knowledge-Based Systems,134: 31-49 (2017).(SCIÊÕ¼)
[7] ÀîÃÀÁë(2014˶),´÷Ⱥ*£¬A Novel Knowledge-Leverage-Based Transfer Learning Algorithm£¬Applied Intelligence£¬2017,doi:10.1007/s10489-017-1084-z(SCIÔ´¿¯£©
[6] º«ÏþÃÍ(2014˶),´÷Ⱥ*£¬Batch-normalized Mlpconv-wise Supervised Pre-training Network In Network£¬Applied Intelligence£¬2017,doi:10.1007/s10489-017-0968-2(SCIÔ´¿¯£©
[5] ÕÅæÃ(2013˶),´÷Ⱥ*£¬Hybrid ensemble selection algorithm incorporating GRASP with path relinking£¬Applied Intelligence£¬2016,44(3),704-724(SCIÊÕ¼£©
[4] ÕÅæÃ(2013˶),´÷Ⱥ*£¬ÂíÖÒ³¼ Extreme learning machines' ensemble selection with GRASP£¬Applied Intelligence£¬2015,43(2),439-459 (SCIÊÕ¼£©
[3] ÂíÖÒ³¼(2012˶),´÷Ⱥ*£¬Selected an Stacking ELMs for Time Series Prediction£¬Neural Processing Letters, 2016,44(3): 831-856. SCIÊÕ¼
[2] ÂíÖÒ³¼(2012˶),´÷Ⱥ*£¬ÁõÄþÖÓ Several novel evaluation measures for rank-based ensemble pruning with applications to time series prediction£¬Expert Systems with Applications,Volume 42, Issue 1, January 2015, Pages 280?292£¨SCIÊÕ¼£©
[1] Áõת(2011˶),´÷Ⱥ*£¬ÁõÄþÖÓ Ensemble selection by GRASP£¬Applied Intelligence£¬2014,41(1),128-144 (SCIÊÕ¼£©
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