[1] |
黄旭,张世义,李军. 图像分割技术研究综述[J]. 装备机械, 2021(2):6-9.
|
[2] |
SRINIVAS N, DEB K. Multiobjective optimization using nondominated sorting in genetic algorithms[J]. Evolutionary Computation, 1994,2(3):221-248.
|
[3] |
DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ[J]. IEEE Transactions on Evolutionary Computation, 2002,6(2):182-197.
|
[4] |
ZHANG Q F, LI H. MOEA/D: A multiobjective evolutionary algorithm based on decomposition[J]. IEEE Transactions on Evolutionary Computation, 2007,11(6):712-731.
|
[5] |
CAO J, ZHANG J L, ZHAO F Q, et al. A two-stage evolutionary strategy based MOEA/D to multi-objective problems[J]. Expert Systems with Applications,2021,185. DOI: 10.
|
|
1016/j.eswa.2021.115654.
|
[6] |
ZHANG M X, JIAO L C, MA W P, et al. Multi-objective evolutionary fuzzy clustering for image segmentation with MOEA/D[J]. Applied Soft Computing, 2016,48:621-637.
|
[7] |
WANG G C, LI X Y, GAO L, et al. Energy-efficient distributed heterogeneous welding flow shop scheduling problem using a modified MOEA/D[J]. Swarm and Evolutionary Computation,2021,62. DOI: 10.1016/j.swevo.2021.100858.
|
[8] |
神显豪,李军,张祁. 基于改进MOEA/D算法的WSN覆盖优化方法[J]. 计算机应用研究, 2016,33(4):1203-1206.
|
[9] |
罗顺根,郭秀萍. 用改进的MOEA/D算法求解微电网电力调度多目标优化问题[J]. 系统科学与数学, 2020,40(1):81-104.
|
[10] |
RAO R V. JAYA: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems[J]. International Journal of Industrial Engineering Computations, 2016,7(1):19-34.
|
[11] |
裴小兵,祁文博,戴毓彤. 求解柔性作业车间调度问题的新型改进JAYA算法[J]. 计算机工程与应用, 2022,58(19):318-325.
|
[12] |
张小萍. 带惯性权重的JAYA算法求解0-1背包问题[J]. 太原师范学院学报(自然科学版), 2022,21(1):73-76.
|
[13] |
李洪辉,伍宏科. 基于JAYA算法的高层建筑粘滞阻尼器优化布置[J]. 四川建筑, 2020,40(6):153-154.
|
[14] |
HOUSSEIN E H, SAAD M R, HASHIM F A, et al. Lévy flight distribution: A new metaheuristic algorithm for solving engineering optimization problems[J]. Engineering Applications of Artificial Intelligence, 2020,94. DOI: 10.1016/
|
|
j.engappai.2020.103731.
|
[15] |
REN Z W, JIANG R Q, YANG F, et al. A multi-objective elitist feedback teaching-learning-based optimization algorithm and its application[J]. Expert Systems with Applications, 2022,188. DOI: 10.1016/j.eswa.2021.115972.
|
[16] |
ZITZLER E, DEB K, THIELE L. Comparison of multiobjective evolutionary algorithms: Empirical results[J]. Evolutionary Computation, 2000,8(2):173-195.
|
[17] |
LI Y F, LIU H L, XIE K, et al. A method for distributing reference points uniformly along the Pareto front of DTLZ test functions in many-objective evolutionary optimization[C]// Proceedings of the 2015 5th International Conference on Information Science and Technology (ICIST). 2015:541-546.
|
[18] |
ZOU F, CHEN D B, XU Q Z, et al. A two-stage personalized recommendation based on multi-objective teaching-learning-based optimization with decomposition[J]. Neurocomputing, 2021,452:716-727.
|
[19] |
DE FARIAS L R C, ARAUJO A F R. A decomposition-based many-objective evolutionary algorithm updating weights when required[J]. Swarm and Evolutionary Computation, 2022,68. DOI: 10.1016/j.swevo.2021.100980.
|
[20] |
VAN VELDHUIZEN D A, LAMONT G B. Evolutionary computation and convergence to a Pareto front[C]// Late Breaking Papers at the Genetic Programming 1998 Conference. 1998:221-228.
|
[21] |
SCHOTT J R. Fault Tolerant Design Using Single and Multicriteria Genetic Algorithm Optimization[D]. Massachusetts Institute of Technology, 1995.
|
[22] |
REN T B, WANG H H, FENG H L, et al. Study on the improved fuzzy clustering algorithm and its application in brain image segmentation[J]. Applied Soft Computing, 2019,81. DOI: 10.1016/j.asoc.2019.105503.
|
[23] |
朱占龙,刘永军. 融合混沌优化和改进模糊聚类的图像分割算法[J]. 电子学报, 2020,48(5):975-984.
|
[24] |
周晓宇,张龙波,王雷. 基于蚁群优化的直觉模糊聚类脑MR图像分割[J]. 计算机应用与软件, 2021,38(11):226-231.
|
[25] |
WU C M, CAO Z. Entropy-like divergence based kernel fuzzy clustering for robust image segmentation[J]. Expert Systems with Applications, 2021,169. DOI: 10.1016/j.eswa.2020.114327.
|
[26] |
YANG D D, FEI R, YAO J L, et al. Two-stage SAR image segmentation framework with an efficient union filter and multi-objective kernel clustering[J]. Applied Soft Computing, 2016,44:30-44.
|
[27] |
SETIADI D R I M. PSNR vs SSIM: Imperceptibility quality assessment for image steganography[J]. Multimedia Tools and Applications, 2021,80(6):8423-8444.
|
[28] |
ZHANG L, ZHANG L, MOU X Q, et al. FSIM: A feature similarity index for image quality assessment[J]. IEEE Transactions on Image Processing, 2011,20(8):2378-2386.
|