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人工智能科学在软土地下工程施工变形预测与控制中的应用实践——理论基础、方法实施、精细化智能管理(示例) 被引量:30
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作者 孙钧 温海洋 《隧道建设(中英文)》 北大核心 2020年第1期1-8,共8页
首先,介绍了基于人工神经网络的智能预测方法(多步滚动预测)和基于智能模糊逻辑法则的施工变形控制方法对策;其次,介绍了基坑施工和盾构掘进施工变形智能预测与控制案例。经过应用实践,认为智能方法的优点是:对于结构变形位移和周边地... 首先,介绍了基于人工神经网络的智能预测方法(多步滚动预测)和基于智能模糊逻辑法则的施工变形控制方法对策;其次,介绍了基坑施工和盾构掘进施工变形智能预测与控制案例。经过应用实践,认为智能方法的优点是:对于结构变形位移和周边地表沉降/隆起,智能方法所得的预测值(3~5 d)与其相应实测值的精度偏差一般为5%~10%;不只是可以了解到当天已发生的信息,还可预见3~5 d将要发生的变形位移和沉降/隆起等的预测定量值;在施工变形达到超限阈值前,采用智能模糊逻辑控制法则作处理,通过调整相应的施工技术参数,即可使后续变形始终处于允许的限值之内,而无需附加额外的巨大花费,节约造价,节省工期,还可实现远程、无线、视频监控。在探讨地铁施工变形智能预测与控制的基础上,开发了盾构掘进施工中工程周边地表沉降/隆起变形的多媒体三维动态可视化仿真程序软件,研制了盾构掘进施工计算机智能管理系统。目前,上海隧道工程有限公司已在上海市沿江通道盾构施工中进行试验性应用,取得了良好的技术效益。最后,对人工智能科学发展的前景及存在的一些问题进行了探讨。 展开更多
关键词 人工智能 神经网络 机器学习 轨道交通/地铁 地下车站深大基坑 盾构法区间隧道 施工技术参数 施工变形智能预测 智能模糊逻辑控制 精细化智能技术管理 5G网络系统
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AN INTELLIGENT METHOD FOR REAL-TIME DETECTION OF DDOS ATTACK BASED ON FUZZY LOGIC 被引量:2
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作者 Wang Jiangtao Yang Geng 《Journal of Electronics(China)》 2008年第4期511-518,共8页
The paper puts forward a variance-time plots method based on slide-window mechanism tocalculate the Hurst parameter to detect Distribute Denial of Service(DDoS)attack in real time.Basedon fuzzy logic technology that c... The paper puts forward a variance-time plots method based on slide-window mechanism tocalculate the Hurst parameter to detect Distribute Denial of Service(DDoS)attack in real time.Basedon fuzzy logic technology that can adjust itself dynamically under the fuzzy rules,an intelligent DDoSjudgment mechanism is designed.This new method calculates the Hurst parameter quickly and detectsDDoS attack in real time.Through comparing the detecting technologies based on statistics andfeature-packet respectively under different experiments,it is found that the new method can identifythe change of the Hurst parameter resulting from DDoS attack traffic with different intensities,andintelligently judge DDoS attack self-adaptively in real time. 展开更多
关键词 Abnormal traffic Distribute Denial of Service (DDoS) Real-time detection Intelligent control Fuzzy logic
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Fuzzy Logic Controlled Induction Motor Based Intelligent Controller
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作者 Salim Mahdab Linda Barazane Seghir Boucherit 《Journal of Energy and Power Engineering》 2013年第6期1192-1197,共6页
The indirect vector controlled IM (induction motor) drive involves decoupling of the stator current into torque and flux producing components. This paper proposes the implementation of a fuzzy logic control scheme a... The indirect vector controlled IM (induction motor) drive involves decoupling of the stator current into torque and flux producing components. This paper proposes the implementation of a fuzzy logic control scheme applied to a two d-q current components model of an induction motor. An intelligent based on fuzzy logic controller is developed with the help of knowledge rule base for efficient control. The performance of fuzzy logic controller is compared with that of the proportional integral controller in terms of the settling time and dynamic response to sudden load changes. The harmonic pattern of the output current is evaluated for both fixed gain proportional integral controller and the fuzzy logic based controller. The performance of the IM drive has been analyzed under steady state and transient conditions. Simulation results of both the controllers are presented for comparison. 展开更多
关键词 IVC (indirect vector control) PI controller FLC (fuzzy logic controller).
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