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学者姓名：王武
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Abstract ：
金线莲是一种珍贵中药材,其治疗、保健作用十分显著.金线莲培育方式主要有种植、组培等,不同培育方式的金线莲,在性状上仅表现出细微差异,但药用、市场价值差异显著,培育方式鉴别能有效保证药用疗效、维护良好市场秩序,然而由于不同品系、产地、培育时间等复合差异的影响,增加了培育方式鉴别难度与复杂度.提出一种基于改进1D-Inception-CNN模型的金线莲培育方式鉴别方法.采用近红外光谱仪采集种植、组培金线莲的光谱,首先使用合成少数类过采样技术(SMOTE)进行过采样以解决种植品、组培品样本比例不平衡问题,其次构建基于改进Inception结构的一维卷积神经网络对来自不同品系、产地、培育时间的金线莲进行种植品、组培品鉴别,最后采用贝叶斯优化方法对构建的卷积神经网络模型超参数进行优化;最终五折交叉验证平均鉴别准确率、精确率、召回率、综合评价指标高达97.95％、96.16％、100％、98.02％.研究表明,实验提出的鉴别模型为快速鉴别金线莲种植品、组培品提供一种有效方法.
Keyword ：
Inception模块 Inception模块 一维卷积神经网络 一维卷积神经网络 少数类过采样技术 少数类过采样技术 贝叶斯优化 贝叶斯优化 金线莲 金线莲
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| GB/T 7714 | 蓝艳 , 王武 , 许文 et al. 基于SMOTE和Inception-CNN的种植和组培金线莲鉴别 [J]. | 光谱学与光谱分析 , 2024 , 44 (1) : 158-163 . |
| MLA | 蓝艳 et al. "基于SMOTE和Inception-CNN的种植和组培金线莲鉴别" . | 光谱学与光谱分析 44 . 1 (2024) : 158-163 . |
| APA | 蓝艳 , 王武 , 许文 , 柴琴琴 , 李玉榕 , 张勋 . 基于SMOTE和Inception-CNN的种植和组培金线莲鉴别 . | 光谱学与光谱分析 , 2024 , 44 (1) , 158-163 . |
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在电气工程专业实践教学过程中凝练出由Turn up、Turn away、Turn back等环节组成的3-Turns教学法。经过多轮的实践应用，3-Turns教学法在实践共同体中提供了一个兼具解释性与可操作性的教学样例。研究发现，3-Turns教学法对实践共同体促进工科生深度学习起到了提质增效的作用；3-Turns教学法为工程实践学习情境的强化设计提供了理论依据与经验支持。该研究验证了基于3-Turns教学法的实践共同体促进工科生深度学习的有效性，为助力工科人才培养质量的持续提升做出了积极的探索与实践。
Keyword ：
3-Turns教学法 3-Turns教学法 实践共同体 实践共同体 实践教学 实践教学 深度学习 深度学习
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| GB/T 7714 | 陈东毅 , 王武 , 林建新 et al. 3-Turns教学法在实践共同体促进深度学习中的应用 [J]. | 实验室研究与探索 , 2024 , 43 (04) : 151-154 . |
| MLA | 陈东毅 et al. "3-Turns教学法在实践共同体促进深度学习中的应用" . | 实验室研究与探索 43 . 04 (2024) : 151-154 . |
| APA | 陈东毅 , 王武 , 林建新 , 黄捷 , 陈建国 . 3-Turns教学法在实践共同体促进深度学习中的应用 . | 实验室研究与探索 , 2024 , 43 (04) , 151-154 . |
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针对传统三相电压源逆变器开路故障诊断方法存在准确率低和鲁棒性差的问题，提出一种用于故障诊断的改进二维卷积神经网络优化方法.该方法首先引入一种新的数据预处理方式，通过马尔可夫变迁场(MTF)将原始时域电压信号数据转换成二维灰度图像，有效保留特征的时空关系；其次，提出采用并行注意力机制对卷积神经网络ResNet18特征提取层提取的特征分别进行通道和空间特征筛选，并完成有效特征融合；最后，融合的特征经ResNet18全连接层和输出层得到故障分类结果.实验结果表明，所提出的改进故障诊断方法能将诊断精度提升至99.80%;在不同噪声条件下均能保持90%以上的分类准确性，验证该方法可有效提高逆变器开路故障诊断性能和鲁棒性.
Keyword ：
ResNet18网络 ResNet18网络 开路故障 开路故障 注意力机制 注意力机制 逆变器 逆变器 马尔可夫变迁场 马尔可夫变迁场
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| GB/T 7714 | 谢泽文 , 陈裕成 , 柴琴琴 et al. 改进残差网络的逆变器开路电路故障诊断 [J]. | 福州大学学报(自然科学版) , 2024 , 52 (01) : 45-52 . |
| MLA | 谢泽文 et al. "改进残差网络的逆变器开路电路故障诊断" . | 福州大学学报(自然科学版) 52 . 01 (2024) : 45-52 . |
| APA | 谢泽文 , 陈裕成 , 柴琴琴 , 林琼斌 , 王武 . 改进残差网络的逆变器开路电路故障诊断 . | 福州大学学报(自然科学版) , 2024 , 52 (01) , 45-52 . |
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Anoectochilus roxburghii (Wall.) Lindl. (Orchidaceae) is one of the most precious Chinese medicine with extraordinary effects in medical treatment and health protection. Planting and tissue-cultured are two main cultivated methods of A. roxburghii. There are slight characteristic differences between Planting and tissue-cultured A. roxburghii, but they show significant differences in medicinal and market value. Therefore, the identification of cultivated methods plays an important role in effectively securing the medicinal efficacy of A. roxburghii and maintaining a good market order. However, due to the influence of composite differences such as different cultivars, different geographical origins and different times of cultivation, the difficulty and complexity of identification in cultivated methods increase heavily. This paper proposes an effective model to discriminative different cultivated methods of A. roxburghii based on improved 1D-inception-CNN. The experiments were conducted on two kinds of A. roxburghii, and their NIRS data were collected by a Fourier transform near-infrared spectrometer. Considering the unbalanced proportion of planting and tissue-cultured samples,the NIRS data was over sampled by using SMOTE first. Secondly, a one-dimensional convolutional neural network based on improved Inception was constructed to identify planting and tissue-cultured A. roxburghii though both include different varieties, different geographical origins and different cultivating times. Finally, Bayesian optimization was used to optimize the hyperparameters of the model. The final average identification accuracy, precision, recall, and F1-score of five-fold crossvalidation reached 97.95%, 96.16%, 100%, and 98.02%. The identification model proposed in this experiment provides a useful method to identify planting and tissue-cultured A. roxburghii effectively and rapidly and provides an idea for the identification of cultivation methods of other Chinese herbal medicines.
Keyword ：
Anoectochilus roxburghii Anoectochilus roxburghii Bayesian optimization Bayesian optimization Inception module Inception module One-dimensional convolutional neural network One-dimensional convolutional neural network SMOTE SMOTE
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| GB/T 7714 | Lan Yan , Wang Wu , Xu Wen et al. Discrimination of Planting and Tissue-Cultured Anoectochilus Roxburghii Based on SMOTE and Inception-CNN [J]. | SPECTROSCOPY AND SPECTRAL ANALYSIS , 2024 , 44 (1) : 158-163 . |
| MLA | Lan Yan et al. "Discrimination of Planting and Tissue-Cultured Anoectochilus Roxburghii Based on SMOTE and Inception-CNN" . | SPECTROSCOPY AND SPECTRAL ANALYSIS 44 . 1 (2024) : 158-163 . |
| APA | Lan Yan , Wang Wu , Xu Wen , Chai Qin-qin , Li Yu-rong , Zhang Xun . Discrimination of Planting and Tissue-Cultured Anoectochilus Roxburghii Based on SMOTE and Inception-CNN . | SPECTROSCOPY AND SPECTRAL ANALYSIS , 2024 , 44 (1) , 158-163 . |
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该文以双有源桥DC-DC变换器为对象，详细分析了变换器在三重移相调制下的两种数学模型，又基于这两种数学模型提出了对应的电感电流优化控制策略，搭建了包含MATLAB/Simulink仿真平台、StarSim半实物仿真平台和实物平台的三阶段实验平台，在平台中通过实验验证了优化控制策略的可行性和有效性。所设计的三阶段开发流程能够加深学生对电力电子领域相关知识的理解，逐步提升学生的理论分析能力、仿真验证能力和实践操作能力。
Keyword ：
仿真 仿真 优化控制策略 优化控制策略 半实物仿真 半实物仿真 双有源桥变换器 双有源桥变换器 实验平台设计 实验平台设计
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| GB/T 7714 | 蔡逢煌 , 龚兴阳 , 柴琴琴 et al. 基于“仿真—半实物仿真—实物”三阶段开发流程的DAB变换器实验探索与研究 [J]. | 实验技术与管理 , 2024 , 41 (05) : 46-53 . |
| MLA | 蔡逢煌 et al. "基于“仿真—半实物仿真—实物”三阶段开发流程的DAB变换器实验探索与研究" . | 实验技术与管理 41 . 05 (2024) : 46-53 . |
| APA | 蔡逢煌 , 龚兴阳 , 柴琴琴 , 王武 . 基于“仿真—半实物仿真—实物”三阶段开发流程的DAB变换器实验探索与研究 . | 实验技术与管理 , 2024 , 41 (05) , 46-53 . |
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Advanced wind power prediction technique plays an essential role in the stable operation of the grid with largescale grid integration of wind power. Most research focuses on distance-based static classification where the subjective nature of initial center selection increases the uncertainty of the prediction. And the data classification on a daily basis neglects the potentially significant climate changes at smaller time scales. To address these issues, the improved snake optimization-long short-term memory (ISO-LSTM) model with Gaussian mixture model (GMM) clustering is proposed to forecast wind power from an adaptive perspective. By exploiting the merits of the probabilistic classification, the K-means optimized GMM clustering enables an appropriate feature modelling for substantial climate changes at smaller time scales. Then the ISO algorithm exhibits higher search accuracy and is better suited for finding hyperparameter combinations for LSTM neural networks. The data from the National Aeronautics and Space Administration (NASA) of the US is used to validate the effectiveness of the proposed method. Compared to the traditional K-means clustering, the K-means optimized GMM clustering has increased accuracy by 2.63 %. Simultaneously, with the adoption of the enhanced ISO algorithm, the accuracy further increases by 7.27 %. Different existing models have also been tested; it shows that the proposed model demonstrates higher prediction accuracy.
Keyword ：
Gaussian mixture model Gaussian mixture model Improved snake optimization Improved snake optimization K -means algorithm K -means algorithm Long short-term memory network Long short-term memory network Probabilistic classification Probabilistic classification
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| GB/T 7714 | Zhou, Yu , Huang, Ruochen , Lin, Qiongbin et al. Probabilistic optimization based adaptive neural network for short-term wind power forecasting with climate uncertainty [J]. | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS , 2024 , 157 . |
| MLA | Zhou, Yu et al. "Probabilistic optimization based adaptive neural network for short-term wind power forecasting with climate uncertainty" . | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 157 (2024) . |
| APA | Zhou, Yu , Huang, Ruochen , Lin, Qiongbin , Chai, Qinqin , Wang, Wu . Probabilistic optimization based adaptive neural network for short-term wind power forecasting with climate uncertainty . | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS , 2024 , 157 . |
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针对传统化学需氧量(chemical oxygen demand, COD)检测存在检测成本高、耗时、易造成二次污染，以及现有检测模型泛化性较差等不足，难以满足水环境实时监测需求的问题，提出基于近红外光谱技术的COD快速无损定量预测模型.实验结果表明，本模型在污水COD光谱数据集上的预测性能，相较于传统机器学习算法和现有其他深度学习算法更优.测试的决定系数(R~2)和均方根误差(E_(RMS))分别达到0.992 1和27.47 mg·L~(-1),模型卷积层的输出特征可解释性强，能有效表征关键波长点.该预测模型为实际水体COD含量快速检测提供一种新的方法.
Keyword ：
一维卷积神经网络 一维卷积神经网络 化学需氧量 化学需氧量 定量预测模型 定量预测模型 实时监测 实时监测 水环境 水环境 近红外光谱 近红外光谱
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| GB/T 7714 | 范日高 , 王武 , 郑芝芳 et al. 近红外光谱的水体污染指标COD定量预测模型 [J]. | 福州大学学报(自然科学版) , 2024 , 52 (02) : 228-235 . |
| MLA | 范日高 et al. "近红外光谱的水体污染指标COD定量预测模型" . | 福州大学学报(自然科学版) 52 . 02 (2024) : 228-235 . |
| APA | 范日高 , 王武 , 郑芝芳 , 柴琴琴 . 近红外光谱的水体污染指标COD定量预测模型 . | 福州大学学报(自然科学版) , 2024 , 52 (02) , 228-235 . |
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在工程教育专业认证持续深入推进的背景下，结合电气工程专业特色，对“组态软件技术”课程教学进行重新设计与教学实践。引入高阶思维临场认知对教学内容进行重构，应用课堂多源数据建立教学评测一体化的教学新模式。实践表明该课程的教学设计有着良好的沉浸式体验感，学生主动建构、解决问题的高阶思维能力得到提升，新的教学模式促进了课程教学的高质量发展。
Keyword ：
临场认知 临场认知 教学实践 教学实践 课堂多源数据 课堂多源数据 高阶思维 高阶思维
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| GB/T 7714 | 陈东毅 , 王武 , 林建新 et al. “组态软件技术”课程教学设计与实践 [J]. | 电气电子教学学报 , 2024 , 46 (02) : 19-23 . |
| MLA | 陈东毅 et al. "“组态软件技术”课程教学设计与实践" . | 电气电子教学学报 46 . 02 (2024) : 19-23 . |
| APA | 陈东毅 , 王武 , 林建新 , 崔凤新 . “组态软件技术”课程教学设计与实践 . | 电气电子教学学报 , 2024 , 46 (02) , 19-23 . |
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For the problems of modeling difficulties and signal feature extraction in inverter open-circuit fault diagnosis methods, the methods based on machine learning and deep learning still have limitations in practical applications. In this paper, a three-phase inverter fault diagnosis method based on Markov variational field and residual convolutional network is proposed. The method encodes the phase voltage signal output from the inverter by MTF to generate a two-dimensional image with timing information and state migration information, avoiding the problem of signal information loss when directly converting voltage or circuit signals into one-dimensional or two-dimensional images. At the same time, the method uses ResNet to process MTF images to extract fault features of phase voltage signals and enhance the propagation of feature information so that the feature information can be fully utilized and accurate fault classification and identification can be achieved. The experimental results show that the proposed method can effectively identify 22 open-circuit fault types of three-phase inverters with a diagnostic accuracy of 98.10%. © 2023 SPIE.
Keyword ：
Fault diagnosis Fault diagnosis Markov transition fields Markov transition fields Open-circuit fault Open-circuit fault ResNet ResNet
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| GB/T 7714 | Xie, Z. , Chen, Y. , Wang, W. et al. Three-Phase Inverter Fault Diagnosis Based on MTF-ResNet [未知]. |
| MLA | Xie, Z. et al. "Three-Phase Inverter Fault Diagnosis Based on MTF-ResNet" [未知]. |
| APA | Xie, Z. , Chen, Y. , Wang, W. , Han, Q. . Three-Phase Inverter Fault Diagnosis Based on MTF-ResNet [未知]. |
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Potential malicious attacks have been a significant security concern for network system applications. However, there are few studies on filtering for hybrid network attacks in switching systems. This paper considers a Kalman filtering problem for the switched systems that suffer from deception attacks and denial-of-service attacks. A new network transmission model for switching systems is established. Then, based on the minimum mean square error criterion, a Kalman filter with low conservatism is designed for the discrete-time switched system. The newly switched Kalman gain matrix is deduced including the random variation of the switching signal after being attacked by the network. Finally, the effectiveness of the proposed filter is verified by the numerical simulation. A switching system is considered to be a typical hybrid system. As it often works in a network environment, the switching signal is vulnerable to the network and thus to various cyber-attacks (e.g. spoofing attacks and denial-of-service attacks). Few studies have been conducted on the impact of switching signals in network transmission. To address this problem, this paper proposes a Kalman filter design method with low conservativeness, which describes network attacks and data loss by building a Kalman filter model associated with the switching signal in terms of satisfying Bernoulli random variables. For practitioners, the ability to recover data to a certain extent when the data transmission is affected by different network attacks will save a lot of costs and is important for improving the stability and performance of switching systems. Our future work will aim to improve the performance of different filtering algorithms under different cyber-attacks.
Keyword ：
deception attack deception attack denial-of-service attack denial-of-service attack Hybrid cyber-attack Hybrid cyber-attack Kalman filter Kalman filter switched system switched system
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| GB/T 7714 | Cai, Fenghuang , Liao, Shuying , Chen, Yucheng et al. Kalman Filter of Switching System Under Hybrid Cyber Attack [J]. | IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING , 2023 . |
| MLA | Cai, Fenghuang et al. "Kalman Filter of Switching System Under Hybrid Cyber Attack" . | IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (2023) . |
| APA | Cai, Fenghuang , Liao, Shuying , Chen, Yucheng , Wang, Wu . Kalman Filter of Switching System Under Hybrid Cyber Attack . | IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING , 2023 . |
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