abap dictionary table learning

本文介绍了企业信息系统中四种主要的数据类型:主数据、交易数据、组织数据及系统数据,并阐述了各自的特点与应用场景,如地址文件作为主数据的例子,以及库存变动作为交易数据的例子。
The most important data classes are master data,transaction data,organizational data and system data.

Master data is data that is only seldomly modified.An example of master data is the data of an address file,for example the

name, address and telephone number.

Transaction data is data that is frequently modified.An example is the material stock of a warehouse,which can change after

each purchase order.

Organizational data is data that is defined during customizing when the system is installed and that is only seldomly omodified

thereafter.The country keys are an example.

System data is data that the SAP System itself needs.The program sources are an example.

Further data classes,called customer data classes(USER,USER1),are provided for customers.These should be used for customer

developments.Special storage areas must be allocated in the database.


When creating indexes,please note:
-- An index can only be used up to the last specified field in the selection! The fields that are specified in the WHERE

clause for a large number of selections should be in the first position.

-- Only those fields whose values siginificantly restrict the amount of data are meaningful in an index.

-- When you change a data record of a table,you must adjust the index sorting.Tables whose contents are frquently changed

should not have too many indexes.

-- Make sure that the indexes on a table are as disjunct as possible.


A value table only becomes a check table when a foreign key is defined.If you refer to a domain with a value table in a

field,but no foreign key was defined at field level,there is no check.
内容概要:本文介绍了一个基于冠豪猪优化算法(CPO)的无人机三维路径规划项目,利用Python实现了在复杂三维环境中为无人机规划安全、高效、低能耗飞行路径的完整解决方案。项目涵盖空间环境建模、无人机动力学约束、路径编码、多目标代价函数设计以及CPO算法的核心实现。通过体素网格建模、动态障碍物处理、路径平滑技术和多约束融合机制,系统能够在高维、密集障碍环境下快速搜索出满足飞行可行性、安全性与能效最优的路径,并支持在线重规划以适应动态环境变化。文中还提供了关键模块的代码示例,包括环境建模、路径评估和CPO优化流程。; 适合人群:具备一定Python编程基础和优化算法基础知识,从事无人机、智能机器人、路径规划或智能优化算法研究的相关科研人员与工程技术人员,尤其适合研究生及有一定工作经验的研发工程师。; 使用场景及目标:①应用于复杂三维环境下的无人机自主导航与避障;②研究智能优化算法(如CPO)在路径规划中的实际部署与性能优化;③实现多目标(路径最短、能耗最低、安全性最高)耦合条件下的工程化路径求解;④构建可扩展的智能无人系统决策框架。; 阅读建议:建议结合文中模型架构与代码示例进行实践运行,重点关注目标函数设计、CPO算法改进策略与约束处理机制,宜在仿真环境中测试不同场景以深入理解算法行为与系统鲁棒性。
评论
成就一亿技术人!
拼手气红包6.0元
还能输入1000个字符
 
红包 添加红包
表情包 插入表情
 条评论被折叠 查看
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值