pushlet笔记 3种发布方式

本文介绍了Pushlet应用中三种发布事件的方式:直接使用Dispatcher的方法、创建并配置EventSource类及利用Pushlet协议进行远程交互。这三种方式适用于不同的场景,如直接发布、定时推送和跨服务器交互。

1.2.1. Direct Publishing (local)

Your application may directly publish Events by using /src/nl/justobjects/pushlet/core/Dispatcher.getInstance().java . Since Dispatcher is (currently) a Singleton, sending the Event is a matter of callingDispatcher.getInstance().multicast()/unicast()/broadcast() .

The other two methods (EventSource and Pushlet protocol) will eventually call Dispatcher.getInstance().multicast()/unicast()/broadcast() .

Note that in order to call Dispatcher.getInstance().multicast()/unicast()/broadcast() , your class needs to be in the same classloader as the Dispatcher.getInstance(). This may be an issue when for example your sender is in another web application. You may use the Pushlet protocol in that case or put pushlet.jar on the system CLASSPATH. In Tomcat you can also make pushlet.jar a shared library.

 

直接用Dispatcher的方法发布,可以向所有人广播,发布给订阅者,指定sessionid发布

1.2.2. Using EventSource

An EventSource is an object that is managed (activated/passivated) by the Pushlet framework. Developing your own EventSource involves creating a class that implements nl.justobjects.pushlet.core.EventSource (when your EventSource pushes Events to the framework) or that extends nl.justobjects.pushlet.core.EventPullSource (when the framework should pull your EventSource at dedicated intervals) and adding your EventSource to a properties file aptly namedsources.properties .

See /webapps/pushlet/WEB-INF/classes/sources.properties for an example. This file specifies which EventSource objects need to be created and managed. Note: since v2.0.3 sources.properties can also be placed under WEB-INF. See /src/nl/justobjects/pushlet/core/EventSourceManager.java how this is done. See examples in /src/nl/justobjects/pushlet/test/TestEventPullSources where several example sources are bundled.

During initialization the EventSourceManager will look for the file sources.properties in the CLASSPATH. Usually this file will be put under WEB-INF/classes.

一个自己写的事件源类,需要配置在sources.properties ,要继承EventPullSource 或实现EventSource

1.2.3. Using the Pushlet protocol

The Chat and WebPresentation examples use the remote publication of events through the Pushlet (control) protocol. In a webapp the Pushlet JS API provides a p_publish() method through which your app may send events.

The /src/nl/justobjects/pushlet/test/PushletPingApplication.java provides a complete example illustrating sending and receiving Events and using/src/nl/justobjects/pushlet/client/PushletClient.java . DHTML clients may use the JavaScript pushlet library.

 

使用pushlet 协议 收发交互   ,  可以跨服务器

MATLAB代码实现了一个基于多种智能优化算法优化RBF神经网络的回归预测模型,其核心是通过智能优化算法自动寻找最优的RBF扩展参数(spread),以提升预测精度。 1.主要功能 多算法优化RBF网络:使用多种智能优化算法优化RBF神经网络的核心参数spread。 回归预测:对输入特征进行回归预测,适用于连续值输出问题。 性能对比:对比不同优化算法在训练集和测试集上的预测性能,绘制适应度曲线、预测对比图、误差指标柱状图等。 2.算法步骤 数据准备:导入数据,随机打乱,划分训练集和测试集(默认7:3)。 数据归一化:使用mapminmax将输入和输出归一化到[0,1]区间。 标准RBF建模:使用固定spread=100建立基准RBF模型。 智能优化循环: 调用优化算法(从指定文件夹中读取算法文件)优化spread参数。 使用优化后的spread重新训练RBF网络。 评估预测结果,保存性能指标。 结果可视化: 绘制适应度曲线、训练集/测试集预测对比图。 绘制误差指标(MAE、RMSE、MAPE、MBE)柱状图。 十种智能优化算法分别是: GWO:灰狼算法 HBA:蜜獾算法 IAO:改进天鹰优化算法,改进①:Tent混沌映射种群初始化,改进②:自适应权重 MFO:飞蛾扑火算法 MPA:海洋捕食者算法 NGO:北方苍鹰算法 OOA:鱼鹰优化算法 RTH:红尾鹰算法 WOA:鲸鱼算法 ZOA:斑马算法
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