基于机器学习算法的工业互联网平台技术研究

Zhengqin Wang
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引用次数: 1

摘要

工业互联网,是新一代信息技术与工业系统全方位深度融合的产品,主要用于制造业的转型升级,可以极大地促进生产力的发展,对拉动实体经济有着重要的作用。但由于工业互联网属于新兴产业,其开发建设经验和能力尚处于起步阶段。党的十九大报告明确提出,推动互联网、大数据、人工智能与实体经济深度融合。金融危机之后,制造业再次成为全球关注的焦点。随着制造业数字化转型,基于云计算、大数据、物联网、人工智能等新一代信息技术的工业互联网平台应运而生。随着机器学习和深度学习的发展,遗传算法、梯度优化等机器学习模型在数据分类、回归和拟合等方面都取得了很好的效果。互联网项目评估基于行业特点,提出了改进的基于机器学习的层次分析法(ahp)方法,并结合机器学习算法和层次分析法,提出了新的解决专家打分确定判断矩阵问题的方法,并为了实现算法的一致性和准确性,引入了粒子群算法对权重进行调整和排序;减少ahp算法在面对复杂问题时的不准确性和复杂性。实现专家评分更全面的综合考虑方法,以及更智能的一致性调整和最终权重计算,对工业互联网设计方案的各项指标进行权重计算,最后根据评分方案和最终发有最终的评价分数并对结果进行进一步的分析和解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on industrial Internet Platform Technology based on machine learning algorithm
Industrial Internet, is a new generation of information technology and industrial system full range of deep integration of the product, mainly for the transformation and upgrading of the manufacturing industry, can greatly boost the development of productivity, to pull the real economy has an important role. However, as the industrial Internet is an emerging industry, its development and construction experience and capacity are still in the initial stage. The report to the 19th National Congress of the Communist Party of China made it clear that we will promote the deep integration of the Internet, big data, artificial intelligence and the real economy. After the financial crisis, the manufacturing industry once again became the focus of global attention. With the digital transformation of the manufacturing industry, the industrial Internet platform based on cloud computing, big data, Internet of Things, artificial intelligence and other new generation of information technology emerged. With the development of machine learning and deep learning, machine learning models such as genetic algorithm and gradient optimization have achieved good results in data classification, regression and fitting. Internet project evaluation based on industry characteristics, puts forward the improved analytic hierarchy process (ahp) based on machine learning methods, and machine learning algorithms and hierarchical analysis method, puts forward a new solution to the problem of the expert scoring to determine judgment matrix and in order to achieve the consistency and accuracy of the algorithm and introduce the weight of the particle swarm algorithm to adjust and sorting, Reduce the inaccuracy and complexity of ahp algorithm in the face of complex problems. To achieve the expert scoring more comprehensive consideration method, as well as more intelligent consistency adjustment and final weight calculation, the index of the industrial Internet design scheme weight calculation, finally according to the scoring scheme and the final hair there are final evaluation scores and further analysis and explanation of the results.
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