What is LotusScript ?

本文介绍了使用Domino平台进行OA系统开发的相关知识,涵盖了多种编程语言如Formula、LotusScript、JavaScript等,并详细解释了LotusScript的重要性及其在产品对象操作中的应用。

          前言:最近一个项目使用的是Domino平台的OA系统开发,所以找些相关资料学习下,有相同需求的,大家可以多多交流

        Programming Notes and Domino applications using Domino Desinger is accomplished with several distinct programming/scripting languages including Formula(@Functions), LotusScript, JavaScript, Java and C/C++. Depending on what you want to accomplish, you must master, to some degree, all of these languages to create sophisticated, cross-client applications for Domino. Of the languages, Formula and LotusScript are essential for Notes applications, and if coding browser application, JavaScript is additionally required.

        Java is used to code the Eclipse/Lotus Expeditor framework in which Notes Standard configuration is extended and "injected" as just another plug-in(albeit a very large one). But within the Notes "plug-in" LotusScript is still the most powerful language.

        LotusScript is a BASIC derivative that uses many of the same statements and function names, so most developers will find it easy to understand and use without too much relearning.

        LotusScript is also implemented in all Lotus SmartSuite products. Although the base of LotusScript is the same across Lotus products(allowing cross-product automation across multiple operating systems), each product--including Notes/Domino--includes product-specific object-oriented extensions.

        To use LotusScript in any meaningfull way, you must learn not only the base language but also how to manipulate the product objects, and if necessary make calls to external programs.

        LotusScript isn't the only way to access the Domino Object Model. Lotus also exposes its product object classes to programs written in C/C++(via the Notes C/C++ API), Java(Class Libraries), and Visual Basic/VBA/VBScript/.NET(OLE and COM). Or, if all you need to access is the data(and not the product objects), you can use the Notes/SQL and JDBC drivers.

【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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