1 |
CHEN H , HAN C Z , ZHANG Y C . Research on tracking of maneuvering multi-target based on bionics for IRST system[J]. Journal of Supercomputing, 2011, 58 (1): 106- 121.
doi: 10.1007/s11227-010-0534-8
|
2 |
CHEN H , LI C . Data association approach for two dimensional tracking based on bearing-only measurements in clutter environment[J]. Journal of Software, 2010, 5 (3): 336- 343.
|
3 |
MALLIK R G , DAINGADE S , SINHA A . Scalable multi-agent formation with bearing only measurement: consensus based approach[J]. European Journal of Control, 2016, 27, 28- 35.
doi: 10.1016/j.ejcon.2015.10.002
|
4 |
HUEMMER C , HOFMANN C , MAAS R , et al. Estimating parameters of nonlinear systems using the elitist particle filter based on evolutionary strategies[J]. IEEE/ACM Trans.on Audio, Speech and Language Processing, 2018, 26 (3): 595- 608.
doi: 10.1109/TASLP.2017.2788183
|
5 |
GUO C F , DAI Z X , YANG L , et al. Application of the strong tracking UKF in the maneuvering target tracking[J]. Journal of Physics Conference Series, 2016, 679 (1): 12- 48.
|
6 |
ZHOU Y Y , ZHANG Q C , WANG H , et al. EKF-based enhanced performance controller design for nonlinear stochastic systems[J]. IEEE Trans.on Automatic Control, 2018, 63 (4): 1155- 1162.
doi: 10.1109/TAC.2017.2742661
|
7 |
LI B . An improved Bernoulli particle filter for single target tracking[J]. Multidimensional Systems and Signal Processing, 2018, 29 (3): 799- 819.
doi: 10.1007/s11045-017-0471-2
|
8 |
LI K L , CHANG L B . Robust Gaussian particle filter based on modified likelihood function[J]. IET Science, Measurement & Technology, 2018, 12 (1): 132- 137.
|
9 |
胡振涛, 路杨, 刘宇. 量测提升策略下两级更新RBPF纯方位被动跟踪[J]. 红外与激光工程, 2013, 42 (S1): 161- 166.
|
|
HU Z T , LU Y , LIU Y . Bearings-only passive tracking based on two stages update Rao-Blackwellised particle filter in lifting scheme of observation[J]. Infrared and Laser Engineering, 2013, 42 (S1): 161- 166.
|
10 |
鹿传国, 冯新喜, 张迪. 基于改进容积卡尔曼滤波的纯方位目标跟踪[J]. 系统工程与电子技术, 2012, 34 (1): 28- 33.
doi: 10.3969/j.issn.1001-506X.2012.01.06
|
|
LU C G , FENG X X , ZHANG D . Pure bearing tracking based on improved cubature Kalman filter[J]. Systems Engineering and Electronics, 2012, 34 (1): 28- 33.
doi: 10.3969/j.issn.1001-506X.2012.01.06
|
11 |
SABET M , FATHI A R , DANIALI MOHAMMAD H R . Optimal design of the own ship maneuver in the bearing-only target motion analysis problem using a heuristically supervised extended Kalman filter[J]. Ocean Engineering, 2016, 123, 146- 153.
doi: 10.1016/j.oceaneng.2016.07.028
|
12 |
CAVAZZINI G , PAVESI G , ARDIZZON G . A novel two-swarm based PSO search strategy for optimal short-term hydro -thermal generation scheduling[J]. Energy Conversion and Management, 2018, 164, 460- 481.
doi: 10.1016/j.enconman.2018.03.012
|
13 |
MADOLIAT R , KHANMIRZA E , POURFARD A . Application of PSO and cultural algorithms for transient analysis of natural gas pipeline[J]. Journal of Petroleum Science and Engineering, 2017, 149, 504- 514.
doi: 10.1016/j.petrol.2016.09.042
|
14 |
ZHANG J H , XIA P Q . An improved PSO algorithm for parameter identification of nonlinear dynamic hysteretic models[J]. Journal of Sound and Vibration, 2017, 389, 153- 167.
doi: 10.1016/j.jsv.2016.11.006
|
15 |
JAFARI R , SMITH B K . Fluid genetic algorithm(FGA)[J]. Journal of Computational Design and Engineering, 2017, 4 (2): 158- 167.
doi: 10.1016/j.jcde.2017.03.001
|
16 |
COSTA P R D O D , MAUCERI S , CARROLL P , et al. A genetic algorithm for a green vehicle routing problem[J]. Electronic Notes in Discrete Mathematics, 2018, 64, 65- 74.
doi: 10.1016/j.endm.2018.01.008
|
17 |
PARINAM S , SHARMA A , PRAVEEN KUMAR V S R S , et al. Optimization of optical parameters for the design of multilayer bandpass filter using genetic algorithm[J]. Materials Today: Proceedings, 2018, 5 (2): 5091- 5096.
doi: 10.1016/j.matpr.2017.12.088
|
18 |
ABED-ALGUNI B , ALKHATEEB F . Novel selection schemes for cuckoo search[J]. Arabian Journal for Science and Engineering, 2017, 42 (8): 3635- 3654.
doi: 10.1007/s13369-017-2663-3
|
19 |
YANG X S , DEB S . Cuckoo search: recent advances and applications[J]. Neural Computing and Applications, 2014, 24 (1): 169- 174.
doi: 10.1007/s00521-013-1367-1
|
20 |
AZIZ M E A E , HASSANIEN A E . Modified cuckoo search algorithm with rough sets for feature selection[J]. Neural Computing and Applications, 2018, 29 (4): 925- 934.
doi: 10.1007/s00521-016-2473-7
|
21 |
STORN R , PRICE K . Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces[J]. Journal of Global Optimization, 1997, 11 (4): 341- 359.
doi: 10.1023/A:1008202821328
|
22 |
王勇, 蔡自兴, 周育人, 等. 约束优化进化算法[J]. 软件学报, 2009, 20 (1): 11- 29.
|
|
WANG Y , CAI Z X , ZHOU Y R , et al. Constrained optimization evolutionary algorithms[J]. Journal of Software, 2009, 20 (1): 11- 29.
|
23 |
李智勇,黄滔,陈少淼,等.约束优化进化算法综述[J]. 2017, 28(6): 1529-1546.
|
|
LI Z Y, HUANG T, CHEN S M, et al. Overview of constrained optimization evolutionary algorithms[J]. Journal of Software, 2017, 28(6): 1529-1546.
|
24 |
郑建国, 王翔, 刘荣辉. 求解约束优化问题的ε-DE算法[J]. 软件学报, 2012, 23 (9): 2374- 2387.
|
|
ZHENG J G , WANG X , LIU R H . ε-differential evolution algorithm for constrained optimization problems[J]. Journal of Software, 2012, 23 (9): 2374- 2387.
|
25 |
APOLLONI J , GARCÍA-NIETO J , ALBA E , et al. Empirical evaluation of distributed differential evolution on standard benchmarks[J]. Applied Mathematics and Computation, 2014, 236, 351- 366.
doi: 10.1016/j.amc.2014.03.083
|
26 |
段海滨, 张祥银, 徐春芳. 仿生智能计算[M]. 北京: 科学出版社, 2011: 113- 120.
|
|
DUAN H B , ZHANG X Y , XU C F . Bionic intelligent computing[M]. Beijing: Science Press, 2011: 113- 120.
|
27 |
苏海军, 杨煜普, 王宇嘉. 微分进化算法的研究综述[J]. 系统工程与电子技术, 2008, 30 (9): 1793- 1797.
doi: 10.3321/j.issn:1001-506X.2008.09.046
|
|
SU H J , YANG Y P , WANG Y J . Review of differential evolution algorithms[J]. Systems Engineering and Electronics, 2008, 30 (9): 1793- 1797.
doi: 10.3321/j.issn:1001-506X.2008.09.046
|
28 |
DA PELO P , MAZZIA F , MININNI R M . State and parameter estimation in solenoid nonlinear equations[J]. Optimal Control Applications and Methods, 2017, 39 (2): 809- 818.
|
29 |
TONG Q Q , YUAN Z Y , ZHENG M L , et al. A novel nonlinear parameter estimation method of soft tissues[J]. Genomics, Proteomics & Bioinformatics, 2017, 15 (6): 371- 380.
|
30 |
CHIOU J P . Variable scaling hybrid differential evolution for large- scale economic dispatch problems[J]. Electric Power System Research, 2007, 77 (3/4): 212- 218.
|
31 |
PIOTROWSKI A P . Review of differential evolution population size[J]. Swarm and Evolutionary Computation, 2017, 32, 1- 24.
doi: 10.1016/j.swevo.2016.05.003
|
32 |
AHRARI A , SHARIAT-PANAHI M . An improved evolution strategy with adaptive population size[J]. Optimization, 2015, 64 (12): 2567- 2586.
doi: 10.1080/02331934.2013.836651
|
33 |
CHEN T S , TANG K , CHEN G L , et al. A large population size can be unhelpful in evolutionary algorithms[J]. Theoretical Computer Science, 2012, 436, 54- 70.
doi: 10.1016/j.tcs.2011.02.016
|