朱善良

朱善良

正教授
博士,教授,硕士生导师,人工智能技术海洋场景化应用山东省工程研究中心副主任,青岛市人工智能海洋技术创新中心副主任,青岛科技大学数学与交叉研究院副院长。山东赛区数学建模竞赛专家组成员、山东省数学会理事、山东省应用统计学会理事、人工智能海洋学专业委员会委员。近年来,主持或参与国家自然科学基金、省自然基金、省教改项目等各类教学科研项目20多项,在国内外期刊发表学术论文80余篇,其中被SCI、EI检索70余篇,参编教材1部。指导学生参加全国大学生数学建模竞赛、中国研究生数学建模竞赛、美国大学生数学建模竞赛等各类竞赛获国家一等奖9项、国家二等奖29项、国家三等奖13项、山东省一等奖37项、山东省二等奖12项、山东省三等奖7项。指导本科生参加国家大学生创新计划项目4项。

Multi-Dimensional Taylor Network-Based Adaptive Output-Feedback Tracking Control for a Class of Nonlinear Systems

In this paper, the output feedback adaptive multi-dimensional Taylor network (MTN) tracking control for a class of nonlinear systems with unmeasurable states is investigated. …

lianlian-zhai

Multi-Dimensional Taylor Network-Based Adaptive Output-Feedback Tracking Control for a Class of Nonlinear Systems

In this paper, the output feedback adaptive multi-dimensional Taylor network (MTN) tracking control for a class of nonlinear systems with unmeasurable states is investigated. …

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朱善良

高压油管的压强控制策略研究

yuyang-han

Adaptive Neural Output Feedback Tracking Control for a Class of Nonlinear Systems

In this paper, an adaptive neural output feedback control scheme based on backstepping technique and dynamic surface control (DSC) approach is developed to solve the tracking …

yuqun-han

Adaptive Neural Output Feedback Tracking Control for a Class of Nonlinear Systems

In this paper, an adaptive neural output feedback control scheme based on backstepping technique and dynamic surface control (DSC) approach is developed to solve the tracking …

yuqun-han

A Fast Low-Rank Matrix Factorization Method for Dynamic Magnetic Resonance Imaging Restoration

Nowadays, over 90 percent of the medical data comes from the medical image. People can reduce the medical faults in diagnoses by using computer to analyze and process these medical …

fei-xu

一种基于改进混合高斯模型的运动目标检测算法

针对运动目标检测中ViBe算法的鬼影、阴影和噪声干扰问题,本研究提出一种融入改进混合高斯模型(GMM)的ViBe算法。该算法改进混合高斯模型的自适应性,使混合高斯模型的K值与学习率对背景进行自适应调节;对视频帧进行训练,构造\"虚拟\"背景代替第一帧图像进行背景建模,算法能够有效地提取背景建模初始化的视频运动目标,从而消除鬼影现象。该算法用像素分类法提取前景 …

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朱善良

一种基于改进混合高斯模型的运动目标检测算法

针对运动目标检测中ViBe算法的鬼影、阴影和噪声干扰问题,本研究提出一种融入改进混合高斯模型(GMM)的ViBe算法。该算法改进混合高斯模型的自适应性,使混合高斯模型的K值与学习率对背景进行自适应调节;对视频帧进行训练,构造\"虚拟\"背景代替第一帧图像进行背景建模,算法能够有效地提取背景建模初始化的视频运动目标,从而消除鬼影现象。该算法用像素分类法提取前景 …

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朱善良