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水质监测节点优化及采集路径规划研究
期刊论文 | 2025 , 57 (2) , 114-119 | 智能物联技术
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Abstract :

针对传统水质监测方法存在的节点固定、时效性不足及灵活性差等问题,提出一种融合节点优化与路径规划的水质监测方案.首先,基于历史水质数据的空间分布特征,采用动态贴近度算法对监测节点进行多维度筛选和优化,进而找出代表性节点,在保障数据准确性的同时减少维护成本;其次,针对节点优化后的路径规划问题,提出遗传算法与蚁群算法的协同优化策略,通过遗传算法的快速全局搜索能力生成初始路径,结合蚁群算法的局部精细优化特性显著缩短监测耗时.系统集成光伏供电和云平台技术,支持多场景能源供给及水质数据远程可视化.实验表明,在2 800 m2水域中,优化后路径长度缩短至159.5 m,较传统方法效率提升显著,且系统可自适应不同规模水域.该方案为复杂水域的精准监测提供了高效、低成本的解决方案,具备生态保护与灾害预警等领域的应用潜力.

Keyword :

水质监测 水质监测 节点优化 节点优化 路径优化 路径优化

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GB/T 7714 何华煦 , 章杰 . 水质监测节点优化及采集路径规划研究 [J]. | 智能物联技术 , 2025 , 57 (2) : 114-119 .
MLA 何华煦 等. "水质监测节点优化及采集路径规划研究" . | 智能物联技术 57 . 2 (2025) : 114-119 .
APA 何华煦 , 章杰 . 水质监测节点优化及采集路径规划研究 . | 智能物联技术 , 2025 , 57 (2) , 114-119 .
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张拉仿生机器鱼身体刚度分布对鱼体波参数的影响
期刊论文 | 2025 , 53 (2) , 159-167 | 福州大学学报(自然科学版)
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Abstract :

借助前期研制的张拉仿生机器鱼,通过实验初步探索鱼体的身体刚度分布与鱼体波参数之间的关系.使用鱼体波重构方法,获取张拉机器鱼在频率为 1.87 Hz时不同刚度分布下的鱼体波参数.实验结果表明,摆幅、相位、波速和曲率与刚度分布之间存在关系.通过调整机器鱼的刚度分布,波速最大可提高约 21.5%,并且可以实现与真实鱼类相似的摆幅和改变最大曲率发生的位置.非均匀刚度分布在改变摆幅等方面存在优势.机器鱼第 4 关节的刚度对波速具有较大影响,但对曲率影响较小.刚度分布与鱼体波参数的相关性有助于机器鱼通过控制身体刚度优化鱼体波参数,提高游动性能.

Keyword :

仿生机器鱼 仿生机器鱼 刚度分布 刚度分布 张拉整体结构 张拉整体结构 鱼体波参数 鱼体波参数

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GB/T 7714 陈文祥 , 章杰 , 姜洪洲 et al. 张拉仿生机器鱼身体刚度分布对鱼体波参数的影响 [J]. | 福州大学学报(自然科学版) , 2025 , 53 (2) : 159-167 .
MLA 陈文祥 et al. "张拉仿生机器鱼身体刚度分布对鱼体波参数的影响" . | 福州大学学报(自然科学版) 53 . 2 (2025) : 159-167 .
APA 陈文祥 , 章杰 , 姜洪洲 , 姚立纲 , 陈炳兴 . 张拉仿生机器鱼身体刚度分布对鱼体波参数的影响 . | 福州大学学报(自然科学版) , 2025 , 53 (2) , 159-167 .
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融合卷积神经网络的混凝投药模型研究
期刊论文 | 2025 , 44 (5) , 29-34 | 网络安全与数据治理
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Abstract :

以东南某百万人口城市水厂为对象,针对传统水质监测效率低及混凝剂投加量预判困难的问题,提出基于卷积神经网络(CNN)的混凝剂预测模型.通过数据预处理提升数据质量后,采用信息增益比率筛选出关键特征,构建包含一维卷积层、池化层和全连接层的CNN模型,采用ReLU激活函数优化特征表达能力.实验显示模型预测结果的RMSE为68.550,MAE为50.709,拟合优度达0.926,较传统方法显著提升.

Keyword :

卷积神经网络 卷积神经网络 水质监测 水质监测 混凝剂预测 混凝剂预测

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GB/T 7714 李泽楷 , 章杰 . 融合卷积神经网络的混凝投药模型研究 [J]. | 网络安全与数据治理 , 2025 , 44 (5) : 29-34 .
MLA 李泽楷 et al. "融合卷积神经网络的混凝投药模型研究" . | 网络安全与数据治理 44 . 5 (2025) : 29-34 .
APA 李泽楷 , 章杰 . 融合卷积神经网络的混凝投药模型研究 . | 网络安全与数据治理 , 2025 , 44 (5) , 29-34 .
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A rapid tunable stiffness bistable adaptive tensegrity joint for gripper and swimmer SCIE
期刊论文 | 2025 , 34 (9) | SMART MATERIALS AND STRUCTURES
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Abstract :

Joints are the core components of robotic actuation systems. Their performance directly affects the system's dynamic characteristics. However, rigid and flexible joints both face a trade-off between environmental adaptability and response velocity due to their structural properties. A bionic tensegrity joint inspired by biological tensegrity principle is proposed. We present its structural design and stiffness model. The joint features tunable bistability, allowing synergistic optimization between adaptability and response velocity. Experiments show that the joint has negative stiffness and fast response. To validate the effectiveness of the proposed joint design, a gripper and a swimmer were developed. The gripper demonstrates a high response velocity of 56 ms while maintaining a payload capacity of up to 4 kg. Leveraging the bistable tensegrity joint, the swimmer achieves a swimming speed of 1.1 body lengths per second (BL s-1). A novel robotic design framework centered on rotational tensegrity joints has been developed, which demonstrates significant potential for agile locomotion, human-robot interaction, and adaptive manipulation.

Keyword :

bistable characteristics bistable characteristics intelligent robot intelligent robot rotational joint rotational joint tensegrity structure tensegrity structure tunable stiffness tunable stiffness

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GB/T 7714 Ye, Fang , Huang, Jianmeng , Yu, Jianming et al. A rapid tunable stiffness bistable adaptive tensegrity joint for gripper and swimmer [J]. | SMART MATERIALS AND STRUCTURES , 2025 , 34 (9) .
MLA Ye, Fang et al. "A rapid tunable stiffness bistable adaptive tensegrity joint for gripper and swimmer" . | SMART MATERIALS AND STRUCTURES 34 . 9 (2025) .
APA Ye, Fang , Huang, Jianmeng , Yu, Jianming , Zhang, Jiaze , Yang, Yi , Zhang, Jie et al. A rapid tunable stiffness bistable adaptive tensegrity joint for gripper and swimmer . | SMART MATERIALS AND STRUCTURES , 2025 , 34 (9) .
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All-Solid-State Thin-Film Lithium-Selenium Batteries SCIE
期刊论文 | 2025 , 35 (38) | ADVANCED FUNCTIONAL MATERIALS
WoS CC Cited Count: 1
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Abstract :

All-solid-state batteries (ASSBs) with high-energy-density and enhanced safety are ideal for next-generation energy storage in electric transportation and Internet of Things. Fundamentally, the augmentation of their energy density relays on advanced cathode materials. This imperative has driven growing interest in Se-based cathodes, which demonstrate a high volumetric energy density, as well as higher electrical conductivity and better environmental adaptability compared to the well-known S cathodes. However, to ensure sufficient mechanical strength and mitigate the continuous deterioration of the solid-solid interface caused by the substantial volume expansion of the Se, the all-solid-state Li-Se batteries reported thus far typically employ thick solid electrolytes (50-200 mu m), which severely limits their energy density. Here, the first successful fabrication of all-solid-state thin-film Li-Se batteries is reported, featuring an ultra-thin (approximate to 1.4 mu m) lithium phosphorus oxynitride solid electrolyte and a hybrid Se cathode supported by vertical graphene nanoarrays (VGs). The conductive VGs, serving as the Se host, effectively mitigate the volume change during cycling and ensure stable solid-solid contact. Consequently, the cells exhibit over 1000 stable cycles with a capacity retention rate of 89% are attained in the "all-thin film" configuration. This study provides a novel design strategy for the development of next-generation high-performance ASSBs.

Keyword :

all-solid-state battery all-solid-state battery graphene nanoarrays graphene nanoarrays Li-Se battery Li-Se battery lithium phosphorous oxynitride lithium phosphorous oxynitride Se cathode Se cathode

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GB/T 7714 Zhang, Jie , Li, Wangyang , Liu, Zongnian et al. All-Solid-State Thin-Film Lithium-Selenium Batteries [J]. | ADVANCED FUNCTIONAL MATERIALS , 2025 , 35 (38) .
MLA Zhang, Jie et al. "All-Solid-State Thin-Film Lithium-Selenium Batteries" . | ADVANCED FUNCTIONAL MATERIALS 35 . 38 (2025) .
APA Zhang, Jie , Li, Wangyang , Liu, Zongnian , Huang, Zewei , Wang, Haiming , Ke, Bingyuan et al. All-Solid-State Thin-Film Lithium-Selenium Batteries . | ADVANCED FUNCTIONAL MATERIALS , 2025 , 35 (38) .
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Low-Temperature Flexible Integration of All-Solid-State Thin-Film Lithium Batteries Enabled by Spin-Coating Electrode Architecture SCIE
期刊论文 | 2024 , 14 (12) | ADVANCED ENERGY MATERIALS
WoS CC Cited Count: 36
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Abstract :

Micro energy sources as the nucleus of intelligent microdevices guarantee their full autonomy in the dimensions of time and space. However, the state-of-the-art micro energy storage components, like all-solid-state thin-film microbatteries (ASSTFBs), whose direct integration is impeded by the stereotyped vacuum-based manufacturing technologies, for which an inevitable high-temperature annealing step (> 500 degrees C) can exert catastrophic effects on the attached microdevices during the crystallization of manufactured insertion thin-film cathodes, especially in flexible integration. Herein, a prototype construction is created to benchmark concrete feasibility for the low-temperature manufacturing of ASSTFBs via a nonvacuum-based spin-coating electrode architecture. Results show that the spin-coated LiFePO4 films enable low-temperature (approximate to 45 degrees C) manufacturing of ASSTFBs, by which it can deliver excellent cycling performance up to 1000 cycles. Importantly, this technology presents the versatility of integrating various cathode composites into ASSTFBs and is therefore generalized to the LiCoO2- and Li4Ti5O12-based solid-state chemistries. Furthermore, ASSTFBs with such compliant electrodes manifest outstanding flexibility without pronounced capacity degradation by successfully integrating on flexible temperature-sensitive substrates. The spin-coating protocol provides a general solution for excessive processing temperatures and ample opportunities for the development of on-chip integratable and flexible ASSTFBs.

Keyword :

flexible batteries flexible batteries LiPON LiPON microbatteries microbatteries on-chip integration on-chip integration spin-coating spin-coating

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GB/T 7714 Ke, Bingyuan , Cheng, Shoulin , Zhang, Congcong et al. Low-Temperature Flexible Integration of All-Solid-State Thin-Film Lithium Batteries Enabled by Spin-Coating Electrode Architecture [J]. | ADVANCED ENERGY MATERIALS , 2024 , 14 (12) .
MLA Ke, Bingyuan et al. "Low-Temperature Flexible Integration of All-Solid-State Thin-Film Lithium Batteries Enabled by Spin-Coating Electrode Architecture" . | ADVANCED ENERGY MATERIALS 14 . 12 (2024) .
APA Ke, Bingyuan , Cheng, Shoulin , Zhang, Congcong , Li, Wangyang , Zhang, Jie , Deng, Renming et al. Low-Temperature Flexible Integration of All-Solid-State Thin-Film Lithium Batteries Enabled by Spin-Coating Electrode Architecture . | ADVANCED ENERGY MATERIALS , 2024 , 14 (12) .
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Multi-timescale short-term urban water demand forecasting based on an improved PatchTST model SCIE
期刊论文 | 2024 , 651 | JOURNAL OF HYDROLOGY
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Short-term water demand forecasting is essential for ensuring the sustainable use of water resources. The accuracy of water demand forecasting directly impacts the rationality of water resources management and the effectiveness of scheduling. Therefore, it is vital to accurately forecast water demand across various timescales. Based on this motivation, we propose an improved patch time series Transformer (PatchTST) model to forecast the multi-timescale short-term water demand. By introducing relative positional encoding (RPE), the model effectively learns the relationships between tokens. The model combines the global token information capture ability of the self-attention mechanism with the local token information capture ability of the convolutional network to enhance feature extraction abilities. Additionally, the model integrates the advantages of patch-wise and series-wise representation, enabling it to simultaneously capture both local and global dependencies in time series. We utilize historical data collected from district metering area to experimentally validate the effectiveness of the proposed model. Compared with one-dimensional convolutional neural network (1D-CNN), long shortterm memory (LSTM), Transformer, DLinear, and PatchTST models, our model demonstrates superior performance across all five forecasting scales. Finally, the effectiveness of the proposed design is further validated through ablation experiments.

Keyword :

Deep learning Deep learning Multi-timescale Multi-timescale PatchTST PatchTST Water demand forecasting Water demand forecasting

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GB/T 7714 Lin, Peijie , Zhang, Xiangxin , Gong, Longcong et al. Multi-timescale short-term urban water demand forecasting based on an improved PatchTST model [J]. | JOURNAL OF HYDROLOGY , 2024 , 651 .
MLA Lin, Peijie et al. "Multi-timescale short-term urban water demand forecasting based on an improved PatchTST model" . | JOURNAL OF HYDROLOGY 651 (2024) .
APA Lin, Peijie , Zhang, Xiangxin , Gong, Longcong , Lin, Jingwei , Zhang, Jie , Cheng, Shuying . Multi-timescale short-term urban water demand forecasting based on an improved PatchTST model . | JOURNAL OF HYDROLOGY , 2024 , 651 .
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结合改进的DCGAN和Attention-LSTM的光伏功率预测 PKU
期刊论文 | 2023 , 51 (4) , 498-504 | 福州大学学报(自然科学版)
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针对新建光伏发电站在光伏功率预测过程中因缺少训练数据导致预测精度较低和光伏发电功率的不稳定等问题,提出一种结合改进的深度卷积生成对抗网络(DCGAN)、注意力机制(Attention)和LSTM网络组合的光伏功率预测方法.首先,将DCGAN中生成器的特征提取网络由二维卷积改为一维卷积,对光伏数据进行扩充.其次,将Attention模块加入LSTM模块中,生成新的输入特征.最后,对新生成的LSTM模型进行功率预测,并采用澳大利亚沙漠知识太阳能中心(DKASC)Alice Springs电站的数据进行验证.实验结果表明,结合深层卷积生成的对抗网络与Attention-LSTM混合预测方法能有效提升预测精度.

Keyword :

光伏功率预测 光伏功率预测 注意力机制 注意力机制 深度卷积生成对抗网络 深度卷积生成对抗网络 长短期记忆网络 长短期记忆网络

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GB/T 7714 徐柔 , 章杰 , 赖松林 et al. 结合改进的DCGAN和Attention-LSTM的光伏功率预测 [J]. | 福州大学学报(自然科学版) , 2023 , 51 (4) : 498-504 .
MLA 徐柔 et al. "结合改进的DCGAN和Attention-LSTM的光伏功率预测" . | 福州大学学报(自然科学版) 51 . 4 (2023) : 498-504 .
APA 徐柔 , 章杰 , 赖松林 , 林培杰 , 卢箫扬 , 余平平 . 结合改进的DCGAN和Attention-LSTM的光伏功率预测 . | 福州大学学报(自然科学版) , 2023 , 51 (4) , 498-504 .
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一种基于长短期记忆神经网络的智慧路灯控制方法 incoPat
专利 | 2022-06-15 00:00:00 | CN202210682896.0
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本发明涉及一种基于长短期记忆神经网络的智慧路灯控制方法。从气象网站获取路灯所在地的湿度、风速、PM2.5、PM10等气象数据,并利用照度传感器采集照度信息,以此作为智慧路灯控制的样本数据集;对每个样本信号进行归一化处理;调用长短期记忆神经网络算法,以湿度、风速、PM2.5、PM10作为模型的输入特征,能见度作为模型的输出,构建能见度检测算法模型;结合能见度检测算法模型所得的能见度情况与当前的照度情况构建路灯控制策略;根据所构建的路灯控制策略,在高能见度时,采用普通亮度与高色温照明模式,节约能源;在低能见度时输出更高的亮度与更低的色温,增强路灯透雾能力。本发明能够实现不同能见度下的路灯自适应调光。

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GB/T 7714 林培杰 , 程树英 , 章杰 et al. 一种基于长短期记忆神经网络的智慧路灯控制方法 : CN202210682896.0[P]. | 2022-06-15 00:00:00 .
MLA 林培杰 et al. "一种基于长短期记忆神经网络的智慧路灯控制方法" : CN202210682896.0. | 2022-06-15 00:00:00 .
APA 林培杰 , 程树英 , 章杰 , 郑伟彬 , 陈志聪 , 吴丽君 et al. 一种基于长短期记忆神经网络的智慧路灯控制方法 : CN202210682896.0. | 2022-06-15 00:00:00 .
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基于树莓派的服装识别系统设计 CSCD PKU
期刊论文 | 2021 , 40 (1) , 98-100,103 | 传感器与微系统
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Abstract :

针对用户家中服装存放无序、分类管理难度大且效率低下等问题,提出了一种基于树莓派的服装识别系统,该系统使用树莓派作为嵌入式开发板.系统通过树莓派调用摄像头获取待存放的服装图片,将图像传输到已训练好的MobileNet模型为核心的服装识别系统中进行类型识别;最后将服装识别的结果和相对应的储存位置通过语音的方式告知用户,以便用户快速准确地找到服装储存的位置.经实验测试,服装识别的正确率为95.19%.系统能够在准确识别服装的基础上,获取该类服装在衣橱中的存放位置,以帮助用户高效、准确地分类管理不同款式的服装.

Keyword :

MobileNet模型 MobileNet模型 服装识别 服装识别 树莓派 树莓派

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GB/T 7714 江美玲 , 章杰 . 基于树莓派的服装识别系统设计 [J]. | 传感器与微系统 , 2021 , 40 (1) : 98-100,103 .
MLA 江美玲 et al. "基于树莓派的服装识别系统设计" . | 传感器与微系统 40 . 1 (2021) : 98-100,103 .
APA 江美玲 , 章杰 . 基于树莓派的服装识别系统设计 . | 传感器与微系统 , 2021 , 40 (1) , 98-100,103 .
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