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学者姓名：韩红桂
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Abstract ：
Point clouds and RGB images are both critical data for 3D object detection. While recent multi-modal methods combine them directly and show remarkable performances, they ignore the distinct forms of these two types of data. For mitigating the influence of this intrinsic difference on performance, we propose a novel but effective fusion model named LI-Attention model, which takes both RGB features and point cloud features into consideration and assigns a weight to each RGB feature by attention mechanism. Furthermore, based on the LI-Attention model, we propose a 3D object detection method called image attention transformer network (IAT-Net) specialized for indoor RGB-D scene. Compared with previous work on multi-modal detection, IAT-Net fuses elaborate RGB features from 2D detection results with point cloud features in attention mechanism, meanwhile generates and refines 3D detection results with transformer model. Extensive experiments demonstrate that our approach outperforms state-of-the-art performance on two widely used benchmarks of indoor 3D object detection, SUN RGB-D and NYU Depth V2, while ablation studies have been provided to analyze the effect of each module. And the source code for the proposed IAT-Net is publicly available at https://github.com/wisper181/IAT-Net.
Keyword ：
attention mechanism attention mechanism transformer transformer 3D object detection 3D object detection
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| GB/T 7714 | Ren, Keyan , Yan, Tong , Hu, Zhaoxin et al. Image attention transformer network for indoor 3D object detection [J]. | SCIENCE CHINA-TECHNOLOGICAL SCIENCES , 2024 , 67 (7) : 2176-2190 . |
| MLA | Ren, Keyan et al. "Image attention transformer network for indoor 3D object detection" . | SCIENCE CHINA-TECHNOLOGICAL SCIENCES 67 . 7 (2024) : 2176-2190 . |
| APA | Ren, Keyan , Yan, Tong , Hu, Zhaoxin , Han, Honggui , Zhang, Yunlu . Image attention transformer network for indoor 3D object detection . | SCIENCE CHINA-TECHNOLOGICAL SCIENCES , 2024 , 67 (7) , 2176-2190 . |
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Abstract ：
Membrane fouling caused by many direct and indirect triggering factors has become an obstacle to the application of membrane bioreactors (MBRs). The nonlinear relationship between those factors is subject to complex causality or affiliation, which is difficult to clarify for the diagnosis of membrane fouling. To solve this problem, this paper proposes a compressible diagnosis model (CDM) based on transfer entropy to facilitate the fault diagnosis of the root cause for membrane fouling. The novelty of this model includes the following points: Firstly, a framework of a CDM between membrane fouling and causal variables is built based on a feature extraction algorithm and mechanism analysis. The framework can identify fault transfer scenarios following the changes in operating conditions. Secondly, the fault transfer topology of a CDM based on transfer entropy is constructed to describe the causal relationship between variables dynamically. Thirdly, an information compressible strategy is designed to simplify the fault transfer topology. This strategy can eliminate the repetitious affiliation relationship, which contributes to diagnosing the root causal variables speedily and accurately. Finally, the effectiveness of the proposed CDM is verified by the measured data from an actual MBR. The results of experiments demonstrate that the proposed CDM fulfills the diagnosis of membrane fouling.
Keyword ：
transfer entropy transfer entropy causal relationship causal relationship membrane fouling membrane fouling root causal variables root causal variables diagnosis diagnosis
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| GB/T 7714 | Wu, Xiaolong , Hou, Dongyang , Yang, Hongyan et al. Compressible Diagnosis of Membrane Fouling Based on Transfer Entropy [J]. | APPLIED SCIENCES-BASEL , 2024 , 14 (18) . |
| MLA | Wu, Xiaolong et al. "Compressible Diagnosis of Membrane Fouling Based on Transfer Entropy" . | APPLIED SCIENCES-BASEL 14 . 18 (2024) . |
| APA | Wu, Xiaolong , Hou, Dongyang , Yang, Hongyan , Han, Honggui . Compressible Diagnosis of Membrane Fouling Based on Transfer Entropy . | APPLIED SCIENCES-BASEL , 2024 , 14 (18) . |
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Abstract ：
The aim of this article is to address the modeling and control problems of discrete-time Takagi-Sugeno (T-S) fuzzy systems that are affected by stochastic packet dropouts. To describe the stochastic behavior of packet dropout between the sensor-controller and controller-actuator, a consecutive packet dropout model is employed. By treating consecutive packet dropouts (CPDs) as an extension of the transmission interval, the considered T-S system is transformed into a stochastic system with bounded stochastic input delay. In addition, a novel equivalent model for the closed-loop system is proposed, which captures the nonuniform distribution of the input delay caused by CPDs. Using the obtained equivalent model, it is possible to evaluate the probability distribution of each stochastic input delay value using the formula for total probability. This approach allows us to fully consider the probability information of CPDs in subsequent stability analysis and controller design. Based on this model, delay-probability dependent stability conditions are derived using stochastic Lyapunov functionals, and controller design conditions are also provided. Finally, the correctness and conservatism reduction of the proposed design method are demonstrated using numerical examples of two physical systems described by T-S fuzzy models.
Keyword ：
Symmetric matrices Symmetric matrices Sensors Sensors discrete-time Takagi-Sugeno fuzzy systems (DTTSFs) discrete-time Takagi-Sugeno fuzzy systems (DTTSFs) stochastic input delay stochastic input delay Stability criteria Stability criteria Numerical stability Numerical stability controller design controller design Stochastic processes Stochastic processes Delays Delays Fuzzy systems Fuzzy systems Consecutive packet dropouts (CPDs) Consecutive packet dropouts (CPDs)
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| GB/T 7714 | Sun, Hao-Yuan , Hou, Shuang , Han, Hong-Gui et al. Modeling and Control of Discrete-Time T-S Fuzzy Systems Subject to Stochastic Packet Dropouts [J]. | IEEE TRANSACTIONS ON FUZZY SYSTEMS , 2024 , 32 (4) : 2129-2139 . |
| MLA | Sun, Hao-Yuan et al. "Modeling and Control of Discrete-Time T-S Fuzzy Systems Subject to Stochastic Packet Dropouts" . | IEEE TRANSACTIONS ON FUZZY SYSTEMS 32 . 4 (2024) : 2129-2139 . |
| APA | Sun, Hao-Yuan , Hou, Shuang , Han, Hong-Gui , Qiao, Jun-Fei . Modeling and Control of Discrete-Time T-S Fuzzy Systems Subject to Stochastic Packet Dropouts . | IEEE TRANSACTIONS ON FUZZY SYSTEMS , 2024 , 32 (4) , 2129-2139 . |
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Abstract ：
This paper investigates the observer-based sampled-data control problem for networked systems with consecutive packet dropouts. A new consecutive packet dropout model is established to describe the phenomenon of packet dropout in both the sensor-controller (S-C) and controller-actuator (C-A) channels. First, the considered system with observer-based control scheme is studied in the discrete-time domain by using equivalent discretization transformation. In order to simplify subsequent analysis, matrix exponential computation is employed to transform the discrete-time system into a more tractable form. Then, the proposed new consecutive packet dropout model is taken into consideration to establish the stochastic mean square exponential stability condition. Furthermore, a novel two-step synthesis approach is used to design the observer-based controller. Finally, the effectiveness of the proposed observer-based sampled-data control approach is verified using a numerical example. In addition, the advantages of the proposed approach are validated through comparisons.
Keyword ：
sampled-data systems sampled-data systems observer-based control observer-based control consecutive packet dropouts consecutive packet dropouts controller design controller design
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| GB/T 7714 | Sun, Hao-Yuan , Han, Hong-Gui , Sun, Jian et al. Observer-based sampled-data control for networked systems with consecutive packet dropouts [J]. | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL , 2023 , 33 (17) : 10662-10677 . |
| MLA | Sun, Hao-Yuan et al. "Observer-based sampled-data control for networked systems with consecutive packet dropouts" . | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 33 . 17 (2023) : 10662-10677 . |
| APA | Sun, Hao-Yuan , Han, Hong-Gui , Sun, Jian , Qiao, Jun-Fei . Observer-based sampled-data control for networked systems with consecutive packet dropouts . | INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL , 2023 , 33 (17) , 10662-10677 . |
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Abstract ：
厌氧氨氧化技术是当今最有发展前景的生物脱氮工艺,在厌氧条件下由厌氧氨氧化菌以亚硝酸盐作为电子受体将氨氮直接氧化为氮气,具有无需曝气、无需有机碳源、剩余污泥产量少等优点.然而厌氧氨氧化菌对生长环境的要求苛刻,影响因素众多,成为其大规模工程化应用的最大瓶颈.本文综述了五种主要影响因素(底物浓度、有机物、溶解氧、温度、pH值)对厌氧氨氧化的影响,并结合不同反应器类型、不同菌种针对不同情况分别讨论如何最大程度利用厌氧氨氧化技术,以期为主流污水处理中厌氧氨氧化的应用提供参考.
Keyword ：
厌氧氨氧化 厌氧氨氧化 溶解氧 溶解氧 底物浓度 底物浓度 有机物 有机物 影响因素 影响因素
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| GB/T 7714 | 韩雪恪 , 王峥嵘 , 彭永臻 et al. 几种重要因素对厌氧氨氧化过程的影响综述 [J]. | 中国环境科学 , 2023 , 43 (05) : 2220-2227 . |
| MLA | 韩雪恪 et al. "几种重要因素对厌氧氨氧化过程的影响综述" . | 中国环境科学 43 . 05 (2023) : 2220-2227 . |
| APA | 韩雪恪 , 王峥嵘 , 彭永臻 , 韩红桂 . 几种重要因素对厌氧氨氧化过程的影响综述 . | 中国环境科学 , 2023 , 43 (05) , 2220-2227 . |
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Abstract ：
针对城市污水处理过程时滞导致难以稳定控制的问题,提出一种自适应滑模控制方法 (Adaptive sliding mode control, ASMC).首先,分析推流时滞对城市污水处理生化反应过程的影响,建立时滞影响下的城市污水处理运行控制模型;其次,设计一种基于模糊神经网络的预估补偿模型,完成滞后变量的准确预测,实现控制模型中变量时刻的统一;最后,设计一种具有自适应开关增益系数的滑模控制器(Sliding mode control, SMC),实现溶解氧和硝态氮的稳定控制.将提出的自适应滑模控制方法应用于城市污水处理过程基准仿真平台,实验结果显示该方法能够实现城市污水处理运行过程稳定控制.
Keyword ：
滑模控制 滑模控制 时滞 时滞 模糊神经网络 模糊神经网络 城市污水处理过程 城市污水处理过程
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| GB/T 7714 | 韩红桂 , 秦晨辉 , 孙浩源 et al. 城市污水处理过程自适应滑模控制 [J]. | 自动化学报 , 2023 , 49 (05) : 1010-1018 . |
| MLA | 韩红桂 et al. "城市污水处理过程自适应滑模控制" . | 自动化学报 49 . 05 (2023) : 1010-1018 . |
| APA | 韩红桂 , 秦晨辉 , 孙浩源 , 乔俊飞 . 城市污水处理过程自适应滑模控制 . | 自动化学报 , 2023 , 49 (05) , 1010-1018 . |
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Abstract ：
一种基于数据离散化的出水氨氮智能预测方法于污水处理领域，针对城市污水处理过程出水氨氮预测峰值精度低的问题。先判断数据离散化间隔，对输入的数据进行离散化线性插值，获得间隔为一分钟的污水运行数据，在对离散化插值后的数据进行主成分分析获得辅助变量，用离散化插值后的辅助变量对模糊神经网络进行训练，预测下一时刻的出水氨氮，解决了出水氨氮峰值预测精度低的问题，实现出水氨氮浓度的实时预测。实验结果表明该方法提高了出水氨氮预测峰值的精度，以离散化数据空间的方式为获得可信度高的城市污水处理过程出水总氮预测值提供了一种有效的方法，满足城市污水处理厂的实际需求。
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| GB/T 7714 | 韩红桂 , 赵子凡 , 伍小龙 et al. 一种基于数据离散化的出水总氮智能预测方法 : CN202210265969.6[P]. | 2022-03-17 . |
| MLA | 韩红桂 et al. "一种基于数据离散化的出水总氮智能预测方法" : CN202210265969.6. | 2022-03-17 . |
| APA | 韩红桂 , 赵子凡 , 伍小龙 , 乔俊飞 . 一种基于数据离散化的出水总氮智能预测方法 : CN202210265969.6. | 2022-03-17 . |
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Abstract ：
The selection of global best (Gbest) exerts a high influence on the searching performance of multi-objective particle swarm optimization algorithm (MOPSO). The candidates of MOPSO in external archive are always estimated to select Gbest. However, in most estimation methods, the candidates are considered as the Gbest in a fixed way, which is difficult to adapt to varying evolutionary requirements for balance between convergence and diversity of MOPSO. To deal with this problem, an adaptive candidate estimation-assisted MOPSO (ACE-MOPSO) is proposed in this paper. First, the evolutionary state information, including both the global dominance information and global distribution information of non-dominated solutions, is introduced to describe the evolutionary states to extract the evolutionary requirements. Second, an adaptive candidate estimation method, based on two evaluation distances, is developed to select the excellent leader for balancing convergence and diversity during the dynamic evolutionary process. Third, a leader mutation strategy, using the elite local search (ELS), is devised to select Gbest to improve the searching ability of ACE-MOPSO. Fourth, the convergence analysis is given to prove the theoretical validity of ACE-MOPSO. Finally, this proposed algorithm is compared with popular algorithms on twenty-four benchmark functions. The results demonstrate that ACE-MOPSO has advanced performance in both convergence and diversity.
Keyword ：
multi-objective particle swarm optimization multi-objective particle swarm optimization convergence and diversity convergence and diversity convergence analysis convergence analysis evolutionary state information evolutionary state information adaptive candidate estimation adaptive candidate estimation
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| GB/T 7714 | Han HongGui , Zhang LinLin , Hou Ying et al. Adaptive candidate estimation-assisted multi-objective particle swarm optimization [J]. | SCIENCE CHINA-TECHNOLOGICAL SCIENCES , 2022 , 65 (8) : 1685-1699 . |
| MLA | Han HongGui et al. "Adaptive candidate estimation-assisted multi-objective particle swarm optimization" . | SCIENCE CHINA-TECHNOLOGICAL SCIENCES 65 . 8 (2022) : 1685-1699 . |
| APA | Han HongGui , Zhang LinLin , Hou Ying , Qiao JunFei . Adaptive candidate estimation-assisted multi-objective particle swarm optimization . | SCIENCE CHINA-TECHNOLOGICAL SCIENCES , 2022 , 65 (8) , 1685-1699 . |
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Abstract ：
针对城市污水脱氮过程中的非线性时变特性与强扰动问题，提出一种自适应模糊滑模控制策略。首先，结合模糊控制和滑模控制方法，建立了适用于城市污水脱氮过程的自适应鲁棒控制结构；其次，基于滑模面对系统的动态影响，设计了控制参数实时调整方法；最后，依据李雅普诺夫理论，证明了控制系统的稳定性。基于国际基准仿真平台的实验结果，验证了所述方法的有效性。所述方法可以自适应调节参数以适应工作环境的变化，从而能在环境复杂变化的城市污水脱氮过程中改善控制性能，保障系统长期可靠运行。
Keyword ：
滑模控制 滑模控制 自适应控制 自适应控制 城市污水脱氮过程 城市污水脱氮过程 模糊控制 模糊控制
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| GB/T 7714 | 韩红桂 , 王童 , 伍小龙 et al. 城市污水脱氮过程自适应模糊滑模控制 [J]. | 控制工程 , 2022 , 29 (10) : 1729-1735 . |
| MLA | 韩红桂 et al. "城市污水脱氮过程自适应模糊滑模控制" . | 控制工程 29 . 10 (2022) : 1729-1735 . |
| APA | 韩红桂 , 王童 , 伍小龙 , 乔俊飞 . 城市污水脱氮过程自适应模糊滑模控制 . | 控制工程 , 2022 , 29 (10) , 1729-1735 . |
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Abstract ：
With the appearance of a huge number of reusable electronic products, the precise value evaluation has become an urgent problem to be solved in the recycling process. Traditional methods rely on manual intervention mostly. In order to make the model more suitable for the dynamic updating, this paper proposes the reinforcement learning based electronic products value prediction model, and it integrates market information to achieve timely and stable prediction results. The basic attributes and depreciation attributes of the product are modeled by two parallel neural networks separately to learn the different effects for prediction. Most importantly, the double deep Q network is adopted to fuse market information by reinforcement learning strategy, and the training on the old product data can be used to predict the following appeared product, which alleviates the cold start problem. Experiments on the real mobile phone recycling platform data verify that the model has achieved higher accuracy and it has a better generalization ability.
Keyword ：
deep Q network deep Q network reinforcement learning reinforcement learning market factor market factor electronic products value prediction electronic products value prediction
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| GB/T 7714 | Du YongPing , Jin XingNan , Han HongGui et al. Reusable electronic products value prediction based on reinforcement learning [J]. | SCIENCE CHINA-TECHNOLOGICAL SCIENCES , 2022 , 65 (7) : 1578-1586 . |
| MLA | Du YongPing et al. "Reusable electronic products value prediction based on reinforcement learning" . | SCIENCE CHINA-TECHNOLOGICAL SCIENCES 65 . 7 (2022) : 1578-1586 . |
| APA | Du YongPing , Jin XingNan , Han HongGui , Wang LuLin . Reusable electronic products value prediction based on reinforcement learning . | SCIENCE CHINA-TECHNOLOGICAL SCIENCES , 2022 , 65 (7) , 1578-1586 . |
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