Even God lends a hand to honest boldness.

古希腊剧作家米南德曾言:Even God lends a hand to honest boldness. 即使是上帝也会帮助那些诚实且勇敢的人。这句话强调了诚实与勇气的重要性。

Even God lends a hand to honest boldness.
                -- Menander

连上帝都会帮诚实勇敢的人-米南德

连上帝都会给 诚实,勇气 搭把手 -米南德

which one is better?

 

请按以下描述,自定义数据结构,实现一个circular bufferIn computer science, a circular buffer, circular queue, cyclic buffer or ring buffer is a data structure that uses a single,fixed-size buffer as if it were connected end-to-end. This structure lends itself easily to bufering data streams. There were earlycircular buffer implementations in hardware. A circular buffer first starts out empty and has a set length. In the diagram below is a 7-element buffeiAssume that 1 is written in the center of a circular buffer (the exact starting locatiorimportant in a circular buffer)8Then assume that two more elements are added to the circulal2buffers use FIFOlf two elements are removed, the two oldest values inside of the circulal(first in, first out) logic. n the example, 1 8 2 were the first to enter the cremoved,leaving 3 inside of the buffer.If the buffer has 7 elements, then it is completely full6 7 8 5 3 4 5A property of the circular buffer is that when it is full and a subsequent write is performed,overwriting the oldesdata. In the current example, two more elements - A & B - are added and theythe 3 & 475 Alternatively, the routines that manage the buffer could prevent overwriting the data and retur an error or raise an exceptionWhether or not data is overwritten is up to the semantics of the buffer routines or the application using the circular bufer.Finally, if two elements are now removed then what would be retured is not 3 & 4 but 5 8 6 because A & B overwrote the 3 &the 4 yielding the buffer with:
05-26
【无人机】基于改进粒子群算法的无人机路径规划研究[和遗传算法、粒子群算法进行比较](Matlab代码实现)内容概要:本文围绕基于改进粒子群算法的无人机路径规划展开研究,重点探讨了在复杂环境中利用改进粒子群算法(PSO)实现无人机三维路径规划的方法,并将其与遗传算法(GA)、标准粒子群算法等传统优化算法进行对比分析。研究内容涵盖路径规划的多目标优化、避障策略、航路点约束以及算法收敛性和寻优能力的评估,所有实验均通过Matlab代码实现,提供了完整的仿真验证流程。文章还提到了多种智能优化算法在无人机路径规划中的应用比较,突出了改进PSO在收敛速度和全局寻优方面的优势。; 适合人群:具备一定Matlab编程基础和优化算法知识的研究生、科研人员及从事无人机路径规划、智能优化算法研究的相关技术人员。; 使用场景及目标:①用于无人机在复杂地形或动态环境下的三维路径规划仿真研究;②比较不同智能优化算法(如PSO、GA、蚁群算法、RRT等)在路径规划中的性能差异;③为多目标优化问题提供算法选型和改进思路。; 阅读建议:建议读者结合文中提供的Matlab代码进行实践操作,重点关注算法的参数设置、适应度函数设计及路径约束处理方式,同时可参考文中提到的多种算法对比思路,拓展到其他智能优化算法的研究与改进中。
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