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Implementation of Artificial Neural Network in Concurrency Control of Computer Integrated Manufacturing (CIM) Database

机译:人工神经网络在计算机集成制造(CIM)数据库并发控制中的实现

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Manufacturing database store large amount of interrelated data. The designersaccess specific information or group of information in the data. Each designeraccessing an entity tries to modify the design parameters meeting therequirements of different customers. Sister concerns of the same group ofcompany will be modifying the data as per design requirements. Wheninformation is updated with new modification by different group of designers,what is the order in which modification of the data has to be allowed. Ifsimultaneous access of the information is done, how to maintain the consistencyof the data. and a designer voluntarily corrupts the data, how to make sure thedesigner is responsible for the corruption of data. In any case if the transactionprocess corrupts the data, how to maintain the consistency of the data. Deletingthe information wantedly can be identified with extra security for the data.However, when transaction protocol is not implemented properly, then corruptionof data in the form of misleading information that showing less numerical valuethan what it has to be or showing more numerical than before updation. In thisresearch work, we have proposed a neural network method for the managing thelocks assigned to objects and the corresponding transactions are stored in a datastructure. The main purpose of using the ANN is that it will require less memoryin storing the lock information assigned to objects. We have attempted to usebackpropagation algorithm for storing lock information when multi users areworking on computer integrated manufacturing (CIM) database.
机译:制造数据库存储大量相互关联的数据。设计人员可以访问数据中的特定信息或一组信息。每个访问实体的设计人员都试图修改设计参数,以满足不同客户的需求。同一集团公司的姊妹关系将根据设计要求修改数据。当信息由不同的设计者组进行新的修改时,必须允许对数据进行修改的顺序是什么。如果同时进行信息访问,如何保持数据的一致性。设计者自愿破坏数据,如何确保设计者对数据破坏负责。无论如何,如果transactionprocess破坏了数据,那么如何保持数据的一致性。可以通过对数据的额外安全性来识别恶意删除信息。但是,如果未正确实施交易协议,则数据会以误导性信息的形式被破坏,这些信息显示的数值比必须更新的数值小,或者显示的数值大于更新之前的数值。在这项研究工作中,我们提出了一种用于管理分配给对象的锁的神经网络方法,并将相应的事务存储在数据结构中。使用ANN的主要目的是在存储分配给对象的锁信息时需要较少的内存。当多个用户在计算机集成制造(CIM)数据库上工作时,我们尝试使用反向传播算法来存储锁信息。

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