Genetic Programming Bibliography entries for Yuanxiang Li

up to index Created by W.Langdon from gp-bibliography.bib Revision:1.3838

GP coauthors/coeditors: Fuchuan Ni, Xiaoyan Yang, Jinhai Xiang, Feng Wang, Li Li, Kangshun Li, Zhiyi Lin, Weiwu Wang, Shengwu Xiong, Bojin Zheng, Jixiang Zhu, Wei Zhang, Xuewen Xia, Xing Xu,

Genetic Programming Articles by Yuanxiang Li

Genetic Programming conference papers by Yuanxiang Li

  1. Fuchuan Ni and Yuanxiang Li and Xiaoyan Yang and Jinhai Xiang. An Orthogonal Cartesian Genetic Programming Algorithm for Evolvable Hardware. In 2014 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI), pages 220-224, 2014. details

  2. Jixiang Zhu and Yuanxiang Li and Wei Zhang and Xuewen Xia and Xing Xu. Adaptive Combinational Logic Circuits Based on Intrinsic Evolvable Hardware. In Andy Tyrrell editor, 2009 IEEE Congress on Evolutionary Computation, pages 3010-3017, Trondheim, Norway, 2009. IEEE Press. details

  3. Feng Wang and Yuanxiang Li and Kangshun Li and Zhiyi Lin. A New Circuit Representation Method for Analog Circuit Design Automation. In Jun Wang editor, 2008 IEEE World Congress on Computational Intelligence, pages 1976-1980, Hong Kong, 2008. IEEE Press. details

  4. Feng Wang and Yuan-Xiang Li. Analog Circuit Design Automation Using Neural Network-Based Two-Level Genetic Programming. In 2006 International Conference on Machine Learning and Cybernetics, pages 2087-2092, Dalian, 2006. IEEE. details

  5. Weiwu Wang and Yuanxiang Li and Shengwu Xiong and Bojin Zheng. Identify Discontinuous Parameter of Parabolic System via Point-Tree Structured Genetic Programming. In Hai Zhuge and Toru Ishida editors, Proceedings of The 2nd International Conference on Semantics, Knowledge and Grid (SKG2006), page 43, Guilin, Guangxi, China, 2006. IEEE Computer Society. details

  6. Feng Wang and Yuanxiang Li. Multi-objective Adaptive Scheme for Analog Circuit Design Based on Two-layer Genetic Programming. In ICNN\&B'05. International Conference on Neural Networks and Brain, volume 1, pages 274-278, 2005. IEEE. details