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基于构件的梯形图算法模块封装方法

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针对传统的梯形图无法实现通用算法的封装复用及算法保密性问题,首先,从基于构件技术的梯形图实现原理出发,对构件的属性定义进行了详细地分析;其次,通过封装技术的继承性、可复用性以及基于梯形图数据结构模式的构件语言重写,设计出了一种将智能算法封装成梯形图中可复用构件模块的方法;最后,以整型权值的神经网络为例,介绍了在梯形图算法生成平台上将C语言编辑的神经网络测试算法封装成固定的构件模块的方法,并与实现相同功能的传统梯形图编程方法进行了比较.研究结果表明,该方法适用于任何常用算法的封装,并且由程序员自行进行智能算法模块的封装,大大减少了软件开发活动中大量的重复性工作.另外,封装技术的保密性同时也保证了内部算法的安全性.
Encapsulation of algorithm module based on component technology in ladder diagram programming
Aiming that the traditional ladder diagram programming can't realize generic algorithm multiplexing and algorithm secrecy problem,firstly,the component technology based on the ladder diagram principle was analyzed from the attribute and the definition in detail.Then,through the inheritance and reusability of the encapsulation technology and the rewrite of the component language which based on the ladder diagram data structure model,a method of packaging the intelligent algorithm into the reusable component module in ladder diagram was designed.At last,the type of the weights of the neural network was taken as an example,a method of packaging the neural network test algorithm which was edited by C language into a fixed component module was introduced,and it was compared with the method that realized the same function with the traditional ladder diagram programming.The results indicate that,this method is suitable for the encapsulation of any commonly algorithms,and packaging the intelligent algorithm module by the programmer themself can reduce a lot of repetitive work in software development activities.The confidentiality of the packaging technology ensures the security of the internal algorithm.

ladder diagramcomponentreuseladder chartneural network

吴盼盼、严义

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杭州电子科技大学计算机学院,浙江杭州310018

梯形图 构件 复用 梯形图 神经网络

国家自然科学基金

61272189

2013

机电工程
浙江大学 浙江省机电集团有限公司

机电工程

CSTPCD
影响因子:0.785
ISSN:1001-4551
年,卷(期):2013.30(6)
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