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首页> 外文期刊>Advances in Science, Technology and Engineering Systems >Development of Smart Technology for Complex Objects Prediction and Control on the Basis of a Distributed Control System and an Artificial Immune Systems Approach
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Development of Smart Technology for Complex Objects Prediction and Control on the Basis of a Distributed Control System and an Artificial Immune Systems Approach

机译:基于分布式控制系统和人工免疫系统方法的复杂对象预测与控制智能技术的发展

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This paper is an extension of work originally presented in 2018 Global Smart Industry Conference (GloSIC). Researches are devoted to the development of Smart technology for complex objects control and prediction on the basis of a distributed Honeywell DCS control system of the TengizChevroil enterprise using the example of a technological process of medium pressure gas cleaning. The article describes how on the basis of the multi-algorithm approach there was developed a modified algorithm based on modern artificial intelligence methods in order to select informative features (principal component method, Random Forest algorithm, particle swarm algorithm) and artificial immune systems (clonal selection) solving the image recognition problem and predicting the state of a complex control object. There was conducted a comparative analysis of the simulation results using the example of real production data (daily data of sensors from an average pressure absorber).
机译:本文是对最初在2018年全球智能产业大会(GloSIC)中提出的工作的扩展。以TengizChevroil企业的分布式霍尼韦尔DCS控制系统为基础,以中压气体净化技术过程为例,致力于智能技术的复杂对象控制和预测开发。本文介绍了如何在多算法方法的基础上开发一种基于现代人工智能方法的改进算法,以选择信息特征(主要成分方法,随机森林算法,粒子群算法)和人工免疫系统(克隆)选择)解决图像识别问题并预测复杂控制对象的状态。以实际生产数据(来自平均压力吸收器的传感器的每日数据)为例,对模拟结果进行了比较分析。

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