基于卷积神经网络的认知智能信息融合系统结构研究

摘要：

认知计算是模拟人类行为的个性化交互和服务来实现人机交互.近年来已有许多研究探讨认知计算对海量数据的分析,但仍未能解决大数据环境下数据智能采集的可扩展性和灵活性等问题.在研究土地大数据下并联数据库网络基础上,提出了一个基于卷积神经网络认知智能信息融合系统体系结构,使用认知计算分析智能信息融合应用程序收集与处理数据,以解决系统的可扩展性和灵活性问题.实验结果证明该系统可以有效面对各种外部应用需求,从数百万数据源捕获的数据可以跨越各种应用程序交叉实施与实时响应.

Cognitive computing is to simulate the personalized interaction and service to achieve human-computer interaction.In recent years,there have been many researches on the analysis of massive data in cognitive computing,but they still fail to solve the scalability and flexibility of intelligent data collection in big data environment.Based on the study of parallel database network under big land data,this paper proposes a cognitive intelligent information fusion system architecture based on convolutional neural network.The cognitive computing is used to analyze the data collected and processed by the application program of intelligent information fusion,so as to solve the problem of scalability and flexibility of the system.The experimental results show that the system can effectively meet various external application requirements,and the data captured from millions of data sources can be crossingly implemented and response in real time across various applications.

作者：

田野 孙瑞志

Tian Ye;Sun Ruizhi(College of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China)

机构地区：

中国农业大学信息与电气工程学院

出处：

《betway官方app 学报：自然科学版》 CAS 北大核心 2021年第5期33-39,共7页

Journal of Henan Normal University(Natural Science Edition)

基金：

中华人民共和国国土资源部资助项目(201511010-02)。

关键词：

卷积神经网络 认知计算 智能信息融合系统 土地利用

convolutional neural network cognitive computing intelligent information fusion system land use

分类号：

TP391 [自动化与计算机技术—计算机应用技术]

基于卷积神经网络的认知智能信息融合系统结构研究.pdf