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[Software Engineering] xindeDMC DL : 0: :针对时滞系统的特点和采用神经网络单值预测控制存在的不足,提出了多步超前预测与补偿的控制算法,有效地增加了控制力度,改善了动态性能,并论述了增加的预测与补偿步数与稳定的关系 -With regards to the characteristics of time-delay system and the weakness of single predictive control, this pa- per puts forward a control scheme of multi-step-ahead prediction and compensation, which increases control power effectively, and improves dynamic characteristics ofthe system. The paper also discusses the relationship between the step number of predic- tion and compensation and the stability of systems
Date : 2025-12-24 Size : 1kb User : liubo
[Software Engineering] yuce DL : 0: 动态矩阵的预测控制源程序，可以实现预测控制中的模型预测和优化算法。- this pa- per puts forward a control scheme of multi-step-ahead prediction and compensation, which increases control power effectively, and improves dynamic characteristics ofthe system. The paper also discusses the relationship between the step number of predic- tion and compensation and the stability of systems.
Date : 2025-12-24 Size : 1kb User : liubo
[Software Engineering] stereopairs DL : 0: 立体图像校准的matlab程序算法讲解。可以直接下载源码-A compact algorithm for rectification of stereo pairs
Date : 2025-12-24 Size : 171kb User : xujie
[Software Engineering] aaaa DL : 0: 基于生物免疫系统的自适应学习、免疫记忆、抗体多样性及动态平衡维持等功能,提出一种动态多目标免疫优化算法处理动态多目标优化问题.算法设计中,依据自适应ζ邻域及抗体所处位置设计抗体的亲和力,基于Pa- reto控制的概念,利用分层选择确定参与进化的抗体,经由克隆扩张及自适应高斯变异,提高群体的平均亲和力,利用免疫记忆、动态维持和Average linkage聚类方法,设计环境识别规则和记忆池,借助3种不同类型的动态多目标测试问题,通过与出众的动态环境优化算法比较,数值实验表明所提出算法解决复杂动态多目标优化问题具有较大潜力.-:A dynamic multi-objective immune optimization algorithm suitable for dynamic multi-objective optimization problems is proposed based on the functions of adaptive learning, immune memory, antibody diversity and dynamic balance maintenance, etc. In the design of the algorithm, the scheme of antibody af- finity was designed based on the locations of adaptive-neighborhood and antibody antibodies participating in evolution were selected by Pareto dominance. In order to enhance the average affinity of the population, clonal proliferation and adaptive Gaussian mutation were adopted to evolve excellent antibodies. Further- more, the average linkage method and several functions of immune memory and dynamic balance mainte- nance were used to design environmental recognition rules and the memory pool. The proposed algorithm was compared against several popular multi-objective algorithms by means of three different kinds of dy- namic multi-objective benchmark problems. Simulations show
Date : 2025-12-24 Size : 488kb User : 王飞