JSF: Managed Bean VS. Backing Bean

本文探讨了JSF中Managed Bean的概念,即Bean如何被创建及初始化,并解析了Backing Bean的角色,通常作为页面组件的服务器端表示。文章还讨论了Bean的作用域及时机问题。
(Quoted from [url=http://saloon.javaranch.com/cgi-bin/ubb/ultimatebb.cgi?ubb=get_topic&f=82&t=000951]here[/url])
Managed bean is about how the bean is created and initialized. As you know, jsf uses the lazy initialization model. It means that the bean in the particular scope is created and initialized not at the moment when the scope is started, but on-demand, i.e. when the bean is first time required.

Backing bean is about the role a particular managed bean plays. This is a role to be a server-side representation of the components located on the page. Usually, the backing beans have a request scope, but it is not a restriction.

If you use or try to work with Java Studio Creator, you can find the backing bean work more explicitly. The same for Shale, because it is designed by the same architect. Generally, it is not required by specification to bind all the components with the properties of the backing bean, so, on practice, the differentiation between the backing bean and managed bean is not evident. Sometimes people call all the beans like backing beans even they are just used for value binding. There is no a thumb rule here, just because the JSF specification has no explicit definition for those terms.[flash=200,200][/flash]
【无人机】基于改进粒子群算法的无人机路径规划研究[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在收敛速度全局寻优方面的优势。; 适合人群:具备一定Matlab编程基础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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