暂无分享,去创建一个
[1] H. Karimi,et al. Quantized ℋ∞ Filtering for Continuous‐Time Markovian Jump Systems with Deficient Mode Information , 2015 .
[2] Randall K. McRee,et al. Symbolic regression using nearest neighbor indexing , 2010, GECCO '10.
[3] J. Anderson,et al. Hypersonic and High-Temperature Gas Dynamics , 2019 .
[4] Søren Nymand Lophaven,et al. DACE - A Matlab Kriging Toolbox , 2002 .
[5] Daniel Raymer,et al. Aircraft Design: A Conceptual Approach, Sixth Edition , 2012 .
[6] Chang-an Yuan,et al. An improved Gene Expression Programming approach for symbolic regression problems , 2014, Neurocomputing.
[7] Conor Ryan,et al. Grammatical evolution , 2001, IEEE Trans. Evol. Comput..
[8] Hector M. Romero Ugalde,et al. Computational cost improvement of neural network models in black box nonlinear system identification , 2015, Neurocomputing.
[9] Shaoliang Zhang,et al. Adaptive space transformation: An invariant based method for predicting aerodynamic coefficients of hypersonic vehicles , 2015, Eng. Appl. Artif. Intell..
[10] Jianbin Qiu,et al. H∞ filtering for two-dimensional continuous-time Markovian jump systems with deficient transition descriptions , 2015, Neurocomputing.
[11] Hossein Kaydani,et al. Permeability estimation in heterogeneous oil reservoirs by multi-gene genetic programming algorithm , 2014 .
[12] Shaoliang Zhang,et al. Parse-matrix evolution for symbolic regression , 2012, Eng. Appl. Artif. Intell..
[13] Chen Chen,et al. Elite bases regression: A real-time algorithm for symbolic regression , 2017, 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD).
[14] Pengfei Yan,et al. Data-driven controller design for general MIMO nonlinear systems via virtual reference feedback tuning and neural networks , 2016, Neurocomputing.
[15] Ankit Garg,et al. An integrated SRM-multi-gene genetic programming approach for prediction of factor of safety of 3-D soil nailed slopes , 2014, Eng. Appl. Artif. Intell..
[16] Dominic P. Searson,et al. GPTIPS: An Open Source Genetic Programming Toolbox For Multigene Symbolic Regression , 2010 .
[17] Mark Johnston,et al. How online simplification affects building blocks in genetic programming , 2009, GECCO.
[18] J. Anderson,et al. Fundamentals of Aerodynamics , 1984 .
[19] Daniel P. Raymer,et al. Aircraft Design: A Conceptual Approach , 1989 .
[20] Amir Hossein Alavi,et al. A new approach for modeling of flow number of asphalt mixtures , 2017 .
[21] Tommy W. S. Chow,et al. Clone selection programming and its application to symbolic regression , 2009, Expert Syst. Appl..
[22] Samira Abbasgholizadeh Rahimi,et al. Medical diagnosis of Rheumatoid Arthritis using data driven PSO-FCM with scarce datasets , 2017, Neurocomputing.
[23] Josh C. Bongard,et al. Improving genetic programming based symbolic regression using deterministic machine learning , 2013, 2013 IEEE Congress on Evolutionary Computation.
[24] Godfrey A. Walters,et al. Symbolic and numerical regression: experiments and applications , 2003, Inf. Sci..
[25] Chen Chen,et al. A divide and conquer method for symbolic regression , 2017, ArXiv.
[26] Trent McConaghy,et al. FFX: Fast, Scalable, Deterministic Symbolic Regression Technology , 2011 .
[27] Andy J. Keane,et al. Engineering Design via Surrogate Modelling - A Practical Guide , 2008 .
[28] Anthony Worm,et al. Prioritized Grammar Enumeration: A novel method for symbolic regression , 2016 .
[29] Yajie Wang,et al. The Recent Developments and Comparative Analysis of Neural Network and Evolutionary Algorithms for Solving Symbolic Regression , 2015, ICIC.
[30] Dervis Karaboga,et al. Artificial bee colony programming for symbolic regression , 2012, Inf. Sci..
[31] Mark Johnston,et al. Using Numerical Simplification to Control Bloat in Genetic Programming , 2008, SEAL.
[32] J. Anderson,et al. Hypersonic and High-Temperature Gas Dynamics, Third Edition , 2006 .
[33] Vinicius Veloso de Melo,et al. Studying bloat control and maintenance of effective code in linear genetic programming for symbolic regression , 2016, Neurocomputing.
[34] John R. Koza,et al. Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.
[35] Tomoyuki Miyashita,et al. A method to learn high-performing and novel product layouts and its application to vehicle design , 2017, Neurocomputing.
[36] Conor Ryan,et al. Grammatical evolution , 2007, GECCO '07.
[37] Chee Peng Lim,et al. Classification of transcranial Doppler signals using individual and ensemble recurrent neural networks , 2017, Neurocomputing.
[38] Bo Yu,et al. Low dimensional simplex evolution: a new heuristic for global optimization , 2011, Journal of Global Optimization.
[39] Hamid Reza Karimi,et al. Reliable Output Feedback Control of Discrete-Time Fuzzy Affine Systems With Actuator Faults , 2017, IEEE Transactions on Circuits and Systems I: Regular Papers.