科研论文总览

发布者:张永韡发布时间:2023-03-21浏览次数:82

[1]ZHANG Y W, XIAO Q, SUN X Y, et al. Comparative Study of Swarm-Based Algorithms for Location-Allocation Optimization of Express Depots [J]. Discrete Dynamics in Nature and Society, 2022, 2022.

[2]ZHANG Y W, XIAO Q, SONG Y L, et al. Learning Path Optimization Based on Multi-Attribute Matching and Variable Length Continuous Representation [J]. Symmetry, 2022, 14(11).

[3]张永韡, 汪镭. 基于协同过滤的连续黑箱优化问题元启发算法选择研究 [J]. 控制与决策, 2020, 35(6): 1297-306.

[4]WAIBEL C, MAVROMATIDIS G, ZHANG Y W. Fitness Landscape Analysis Metrics based on Sobol Indices and Fitness- And State-Distributions; proceedings of the 2020 IEEE Congress on Evolutionary Computation, CEC 2020, F 2020, 2020 [C].

[5]ZHANG Y W, HALGAMUGE S K. Similarity of Continuous Optimization Problems from the Algorithm Performance Perspective; proceedings of the 2019 IEEE Congress on Evolutionary Computation, CEC 2019, Wellington, New Zealand, F 2019, 2019 [C]. IEEE.

[6]ZHANG Y W, HALGAMUGE S K. Metaheuristic Algorithm Similarity Analysis Based on Performance Metric Mapping of Fractional Ranking; proceedings of the 2018 IEEE 9th International Conference on Information and Automation for Sustainability, ICIAfS 2018, Colombo, Sri Lanka, F 2018, 2018 [C]. IEEE.

[7]GUO M, ZHANG Y, YE W, et al. Pricing the permission of pollution: Optimal control-based simulation of payments for the initial emission allowance in China [J]. Journal of Cleaner Production, 2018, 174: 139-49.

[8]肖琴, 张永韡, 汪镭. 增量极坐标编码的贝赛尔曲线智能优化算法 [J]. 智能系统学报, 2017, 12(6): 841-7.

[9]肖琴, 张永韡, 汪镭. 基于人工蜂群算法的自适应物流选址规划方法 [J]. 微型电脑应用, 2016, 32(3): 5-8.

[10]张永韡, 汪镭, 吴启迪. 动态适应布谷鸟搜索算法 [J]. 控制与决策, 2014, 29(4): 617-22.

[11]张永韡, 汪镭, 吴启迪. 自适应编码蜂群算法求解连续批量统一模型 [J]. 计算机集成制造系统, 2013, 19(3): 596-607.

[12]张永韡, 司呈勇, 高文倩, et al. 基于元启发的学生耐力典型评价标准研究 [J]. 微型电脑应用, 2013, 30(7): 9-11.

[13]ZHANG Y, WANG L, WU Q. Differential annealing for global optimization [M]. 2012.

[14]ZHANG Y, WANG L, WU Q. Modified Adaptive Cuckoo Search (MACS) algorithm and formal description for global optimisation [J]. International Journal of Computer Applications in Technology, 2012, 44(2).

[15]ZHANG Y W, WANG L, WU Q D. Mortal particles: Particle swarm optimization with life span [M]. 2011.

[16]汪镭, 张永韡, 郭为安, et al. 自然计算发展趋势研究 [J]. 微型电脑应用, 2010, 26(7): 1-11.

[17]张永韡, 汪镭, 吴启迪. 自然计算在九大高新技术领域的应用研究 [J]. 微型电脑应用, 2010, 26(10): 1-8.

[18]ZHANG Y, FEI Q, LU J, et al. Performance criteria research on PSO-PID control systems; proceedings of the Proceedings of International Conference on Intelligent Computing and Cognitive Informatics (CICCI), F 2010/06//, 2010 [C]. IEEE.

[19]LEI M, GUO W, ZHANG Y, et al. Design of time-variable boundary layer on sliding mode control; proceedings of the Proceedings of the World Congress on Intelligent Control and Automation (WCICA), F 2010, 2010 [C].

[20]曹洁, 张永韡. 基于PSO优化的交通信号预测控制 [J]. 科学技术与工程, 2008, 8(17): 4930-8.

[21]曲培娟, 张永韡, 曹洁. 温度控制系统的无超调模糊-PID控制器设计 [J]. 甘肃科技, 2008, 24(4): 45=8-=8.

[22]张永韡. 单路口交通信号ANN自校正预测控制的研究 [D]. 2008; 兰州理工大学, 2008.


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