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Novel computational approaches and their applications
1. | Department of Mathematics, University of Auckland, Private Bag 92019, Auckland 1142, New Zealand |
2. | School of Natural and Computational Sciences, Massey University, Private Bag 102-904 NSMC, Auckland 0745, New Zealand |
[1] |
Dominik Wodarz. Computational modeling approaches to studying the dynamics of oncolytic viruses. Mathematical Biosciences & Engineering, 2013, 10 (3) : 939-957. doi: 10.3934/mbe.2013.10.939 |
[2] |
John A. Doucette, Robin Cohen. A testbed to enable comparisons between competing approaches for computational social choice. Big Data & Information Analytics, 2016, 1 (4) : 309-340. doi: 10.3934/bdia.2016013 |
[3] |
Martina Bukač, Sunčica Čanić. Longitudinal displacement in viscoelastic arteries: A novel fluid-structure interaction computational model, and experimental validation. Mathematical Biosciences & Engineering, 2013, 10 (2) : 295-318. doi: 10.3934/mbe.2013.10.295 |
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Burcu Gürbüz. A computational approximation for the solution of retarded functional differential equations and their applications to science and engineering. Journal of Industrial and Management Optimization, 2022, 18 (4) : 2319-2334. doi: 10.3934/jimo.2021069 |
[5] |
Harish Garg. Novel correlation coefficients under the intuitionistic multiplicative environment and their applications to decision-making process. Journal of Industrial and Management Optimization, 2018, 14 (4) : 1501-1519. doi: 10.3934/jimo.2018018 |
[6] |
M. Fernández-Martínez, Yolanda Guerrero-Sánchez, Pía López-Jornet. A novel approach to improve the accuracy of the box dimension calculations: Applications to trabecular bone quality. Discrete and Continuous Dynamical Systems - S, 2019, 12 (4&5) : 1527-1534. doi: 10.3934/dcdss.2019105 |
[7] |
Yubo Yuan, Chenglong Ma, Dongmei Pu. A novel discriminant minimum class locality preserving canonical correlation analysis and its applications. Journal of Industrial and Management Optimization, 2016, 12 (1) : 251-268. doi: 10.3934/jimo.2016.12.251 |
[8] |
Marcin Mazur, Jacek Tabor. Computational hyperbolicity. Discrete and Continuous Dynamical Systems, 2011, 29 (3) : 1175-1189. doi: 10.3934/dcds.2011.29.1175 |
[9] |
Vaughn Climenhaga. A note on two approaches to the thermodynamic formalism. Discrete and Continuous Dynamical Systems, 2010, 27 (3) : 995-1005. doi: 10.3934/dcds.2010.27.995 |
[10] |
Robinson Duque, Alejandro Arbelaez, Juan Francisco Díaz. CP and MIP approaches for soccer analysis. Journal of Industrial and Management Optimization, 2019, 15 (4) : 1535-1564. doi: 10.3934/jimo.2018109 |
[11] |
Jelena Grbić, Jie Wu, Kelin Xia, Guo-Wei Wei. Aspects of topological approaches for data science. Foundations of Data Science, 2022, 4 (2) : 165-216. doi: 10.3934/fods.2022002 |
[12] |
Peter Giesl, Sigurdur Hafstein. Computational methods for Lyapunov functions. Discrete and Continuous Dynamical Systems - B, 2015, 20 (8) : i-ii. doi: 10.3934/dcdsb.2015.20.8i |
[13] |
Shu Liao, Jin Wang, Jianjun Paul Tian. A computational study of avian influenza. Discrete and Continuous Dynamical Systems - S, 2011, 4 (6) : 1499-1509. doi: 10.3934/dcdss.2011.4.1499 |
[14] |
Nur Aidya Hanum Aizam, Louis Caccetta. Computational models for timetabling problem. Numerical Algebra, Control and Optimization, 2014, 4 (3) : 269-285. doi: 10.3934/naco.2014.4.269 |
[15] |
Ian H. Dinwoodie. Computational methods for asynchronous basins. Discrete and Continuous Dynamical Systems - B, 2016, 21 (10) : 3391-3405. doi: 10.3934/dcdsb.2016103 |
[16] |
Wenxiong Chen, Congming Li. Some new approaches in prescribing gaussian and salar curvature. Conference Publications, 1998, 1998 (Special) : 148-159. doi: 10.3934/proc.1998.1998.148 |
[17] |
Giancarlo Bigi. Componentwise versus global approaches to nonsmooth multiobjective optimization. Journal of Industrial and Management Optimization, 2005, 1 (1) : 21-32. doi: 10.3934/jimo.2005.1.21 |
[18] |
H. Thomas Banks, Shuhua Hu, Zackary R. Kenz, Hien T. Tran. A comparison of nonlinear filtering approaches in the context of an HIV model. Mathematical Biosciences & Engineering, 2010, 7 (2) : 213-236. doi: 10.3934/mbe.2010.7.213 |
[19] |
Sahani Pathiraja, Sebastian Reich. Discrete gradients for computational Bayesian inference. Journal of Computational Dynamics, 2019, 6 (2) : 385-400. doi: 10.3934/jcd.2019019 |
[20] |
Peter Giesl, Sigurdur Hafstein. Review on computational methods for Lyapunov functions. Discrete and Continuous Dynamical Systems - B, 2015, 20 (8) : 2291-2331. doi: 10.3934/dcdsb.2015.20.2291 |
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