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学者姓名：吴升
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Abstract ：
建立了采摘机器人运动学模型，并设计了基于深度神经网络和大数据技术的多元信息融合模型，实现了对采摘机器人的定位和轨迹预测。仿真结果表明：模型对采摘机器人的预测精度较高，误差在允许的范围内，对采摘机器人定位和轨迹预测具有一定参考意义。
Keyword ：
信息融合 信息融合 大数据 大数据 定位 定位 神经网络 神经网络 轨迹预测 轨迹预测 采摘机器人 采摘机器人
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| GB/T 7714 | 聂恒志 , 吴升 , 张璐 . 采摘机器人的定位和轨迹预测算法研究——基于大数据技术 [J]. | 农机化研究 , 2024 , 46 (04) : 53-57 . |
| MLA | 聂恒志 等. "采摘机器人的定位和轨迹预测算法研究——基于大数据技术" . | 农机化研究 46 . 04 (2024) : 53-57 . |
| APA | 聂恒志 , 吴升 , 张璐 . 采摘机器人的定位和轨迹预测算法研究——基于大数据技术 . | 农机化研究 , 2024 , 46 (04) , 53-57 . |
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Abstract ：
建立了采摘机器人运动学模型,并设计了基于深度神经网络和大数据技术的多元信息融合模型,实现了对采摘机器人的定位和轨迹预测.仿真结果表明:模型对采摘机器人的预测精度较高,误差在允许的范围内,对采摘机器人定位和轨迹预测具有一定参考意义.
Keyword ：
信息融合 信息融合 大数据 大数据 定位 定位 神经网络 神经网络 轨迹预测 轨迹预测 采摘机器人 采摘机器人
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| GB/T 7714 | 聂恒志 , 吴升 , 张璐 . 采摘机器人的定位和轨迹预测算法研究 [J]. | 农机化研究 , 2024 , 46 (4) : 53-57 . |
| MLA | 聂恒志 等. "采摘机器人的定位和轨迹预测算法研究" . | 农机化研究 46 . 4 (2024) : 53-57 . |
| APA | 聂恒志 , 吴升 , 张璐 . 采摘机器人的定位和轨迹预测算法研究 . | 农机化研究 , 2024 , 46 (4) , 53-57 . |
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The construction of China's ecological civilization, known as 'Beautiful China', necessitates implementing precision watershed management through scientifically informed decision-making. This entails optimizing the spatial distribution of watershed best management practices (the so- called BMP scenario) and proposing multistage implementation plans, or roadmaps that align with practical requirements based on the overarching vision of comprehensive water shed management.The'water shed system simulation-scenariooptimization' method frame work (the simulation-and-optimization-based frame work for short) has demonstrated considerable potential in recent years. To address challenges arising from practical applications of this framework, this study systematically conducted the methodological research: (1) proposing a novel watershed process modeling framework that strikes a balance between modeling flexibility and high-performance computing to model and simulate watershed systems efficiently; (2) introducing slope position units as BMP configuration units and enabling dynamic boundary adjustments during scenario optimization, effectively incorporating practical knowledge of watershed management to ensure reasonable outcomes; (3) presenting an optimization method for determining the implementation orders of BMPs that considers stepwise investment constraints, thereby recommending feasible roadmaps that meet practical needs; and (4) designing a user-friendly participatory watershed planning system to facilitate collaborative decision-making among stakeholders. The effectiveness and practical value of these new methods, tools, and prototype systems are validated through application cases in a representative small watershed. This research contributes to advancing precision watershed management and provides valuable insights for sustainable ecological conservation. The methods proposed within the simulation-and-optimization-based framework in this study are universal methods, which means their application does not depend on the specific implementation, such as the watershed process model, the BMP types considered, the designed BMP configuration strategy, and so on. Further studies should be conducted not only to deepen related theory and method research but also to strengthen promotion and application, especially cooperating with local watershed management agents to provide valuable insights for their sustainable ecological conservation. © 2024 Science Press. All rights reserved.
Keyword ：
Computation theory Computation theory Decision making Decision making Decision support systems Decision support systems Ecology Ecology Investments Investments Soil conservation Soil conservation Water conservation Water conservation Water management Water management Watersheds Watersheds
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| GB/T 7714 | Qin, Chengzhi , Zhu, Liangjun , Shen, Shen et al. Methods for supporting decision-making of precision watershed management based on watershed system simulation and scenario optimization [J]. | Acta Geographica Sinica , 2024 , 79 (1) : 58-75 . |
| MLA | Qin, Chengzhi et al. "Methods for supporting decision-making of precision watershed management based on watershed system simulation and scenario optimization" . | Acta Geographica Sinica 79 . 1 (2024) : 58-75 . |
| APA | Qin, Chengzhi , Zhu, Liangjun , Shen, Shen , Wu, Tong , Xiao, Guirong , Wu, Sheng et al. Methods for supporting decision-making of precision watershed management based on watershed system simulation and scenario optimization . | Acta Geographica Sinica , 2024 , 79 (1) , 58-75 . |
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“乒乓效应”是手机位置数据中一种典型的噪声数据，分析其时空分布特征对科学应对噪音数据影响、准确理解分析结果、提高手机位置数据质量具有重要意义。本研究基于速度阈值、重复跳转和频繁大幅度转向3种模式的“乒乓效应”检测方法，采用3个不同研究区(上海、西宁和深圳)的手机位置数据，构建了时间与空间易发指数，对手机数据中的“乒乓效应”进行识别，并从跳转距离特征、空间分布特征、时间分布特征3个方面进行了对比分析。结果表明：空间分布上，“乒乓效应”总体呈现出较高的空间自相关现象，表现为远郊区易发、基站密度高处不易发的特点；在时间分布特征上，呈现出白天易发、夜晚不易发的特点；同时“乒乓效应”的存在会对研究结果产生一定程度的影响。
Keyword ：
“乒乓效应” “乒乓效应” 手机位置数据 手机位置数据 数据质量 数据质量 时空数据挖掘 时空数据挖掘
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| GB/T 7714 | 赵志远 , 张雯婷 , 杨喜平 et al. 手机位置数据中“乒乓效应”的时空特征研究 [J]. | 测绘与空间地理信息 , 2024 , 47 (03) : 12-17 . |
| MLA | 赵志远 et al. "手机位置数据中“乒乓效应”的时空特征研究" . | 测绘与空间地理信息 47 . 03 (2024) : 12-17 . |
| APA | 赵志远 , 张雯婷 , 杨喜平 , 吴升 . 手机位置数据中“乒乓效应”的时空特征研究 . | 测绘与空间地理信息 , 2024 , 47 (03) , 12-17 . |
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面向美丽中国生态文明建设所需，亟待有效实现流域精细治理的科学决策，以根据流域综合治理愿景目标，优化流域管理措施（BMP）的空间布局方案（即BMP情景）、制定符合实际需求的实施路线图。对此，“流域系统模拟—情景优化”方法框架近年展现出广阔应用前景。本文介绍了该框架在应对实际应用需求中尚存的一系列问题，开展了体系性的方法研究：(1)提出新的流域过程建模框架，以兼顾建模灵活性和高性能计算、高效实现流域系统模拟；(2)提出以坡位单元作为BMP空间配置单元、并在情景优化过程中可进行单元边界动态调整的BMP情景优化方法，可有效考虑流域综合治理的经验知识，保障优化结果合理性；(3)提出考虑分阶段投资约束的BMP情景实施次序优化方法，可推荐出符合实际落地需求的实施路线图；(4)设计研发用户友好的参与式流域规划系统，供各方利益相关者协商决策。通过典型小流域应用案例验证了上述新方法、工具和原型系统的有效性和实用价值。
Keyword ：
决策支持 决策支持 情景分析 情景分析 智能优化 智能优化 流域管理措施 流域管理措施 流域系统模拟 流域系统模拟
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| GB/T 7714 | 秦承志 , 朱良君 , 申申 et al. 基于流域系统模拟一情景优化的精细治理决策支持方法 [J]. | 地理学报 , 2024 , 79 (01) : 58-75 . |
| MLA | 秦承志 et al. "基于流域系统模拟一情景优化的精细治理决策支持方法" . | 地理学报 79 . 01 (2024) : 58-75 . |
| APA | 秦承志 , 朱良君 , 申申 , 吴彤 , 肖桂荣 , 吴升 et al. 基于流域系统模拟一情景优化的精细治理决策支持方法 . | 地理学报 , 2024 , 79 (01) , 58-75 . |
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The accurate extraction of agricultural parcels from remote sensing images is crucial for advanced agricultural management and monitoring systems. Existing methods primarily emphasize regional accuracy over boundary quality, often resulting in fragmented outputs due to uniform crop types, diverse agricultural practices, and environmental variations. To address these issues, this paper proposes DSTBA-Net, an end-to-end encoder-decoder architecture. Initially, we introduce a Dual-Stream Feature Extraction (DSFE) mechanism within the encoder, which consists of Residual Blocks and Boundary Feature Guidance (BFG) to separately process image and boundary data. The extracted features are then fused in the Global Feature Fusion Module (GFFM), utilizing Transformer technology to further integrate global and detailed information. In the decoder, we employ Feature Compensation Recovery (FCR) to restore critical information lost during the encoding process. Additionally, the network is optimized using a boundary-aware weighted loss strategy. DSTBA-Net aims to achieve high precision in agricultural parcel segmentation and accurate boundary extraction. To evaluate the model's effectiveness, we conducted experiments on agricultural parcel extraction in Denmark (Europe) and Shandong (Asia). Both quantitative and qualitative analyses show that DSTBA-Net outperforms comparative methods, offering significant advantages in agricultural parcel extraction.
Keyword ：
agricultural parcel extraction agricultural parcel extraction boundary-aware weighted loss boundary-aware weighted loss dual-stream feature extraction (DSFE) dual-stream feature extraction (DSFE) feature compensation restoration (FCR) feature compensation restoration (FCR) global feature fusion module (GFFM) global feature fusion module (GFFM)
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| GB/T 7714 | Xu, Weiming , Wang, Juan , Wang, Chengjun et al. Utilizing Dual-Stream Encoding and Transformer for Boundary-Aware Agricultural Parcel Extraction in Remote Sensing Images [J]. | REMOTE SENSING , 2024 , 16 (14) . |
| MLA | Xu, Weiming et al. "Utilizing Dual-Stream Encoding and Transformer for Boundary-Aware Agricultural Parcel Extraction in Remote Sensing Images" . | REMOTE SENSING 16 . 14 (2024) . |
| APA | Xu, Weiming , Wang, Juan , Wang, Chengjun , Li, Ziwei , Zhang, Jianchang , Su, Hua et al. Utilizing Dual-Stream Encoding and Transformer for Boundary-Aware Agricultural Parcel Extraction in Remote Sensing Images . | REMOTE SENSING , 2024 , 16 (14) . |
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Travel mode recognition is a key issue in urban planning and transportation research. While traditional travel surveys use manual data collection and have limited coverage, poor timeliness, and insufficient sample capacity, recent advancements in Global Positioning System (GPS) technology allow large-scale data collection and offer novel opportunities to enhance travel mode recognition. However, existing studies often neglect regular differences and changes in motion states across different travel modes and fail to fully integrate multi-scale spatio-temporal features, which limits the accurate classification of travel modes. To fill this gap, this study proposes a multi-scale spatio-temporal attribute fusion (MSAF) model for precise travel mode identification using solely GPS trajectories without altering their sampling rate. The MSAF model segments GPS trajectories into various temporal and spatial scales, extracting local motion states and spatial features at multiple scales. The spatio-temporal feature extraction module is constructed to extract local motion states and capture spatio-temporal dependencies. Additionally, the model incorporates a multi-scale feature fusion module, which effectively combines features of various scales through a series of fusion techniques to obtain a comprehensive representation, enabling automatic and accurate travel mode identification. Experiments on real-world datasets, including the GeoLife Trajectories dataset and the Sussex-Huawei Locomotion-Transportation (SHL) dataset, demonstrate the effectiveness of the MSAF model, achieving a competitive accuracy of 95.16% and 91.70%. This represents an improvement of 2.50% to 7.95% and 0.8% to 6.62% over several state-of-the-art baselines, effectively addressing sample imbalance challenges. Moreover, the experiments demonstrate the significant role of multiscale feature fusion in improving model performance.
Keyword ：
GPS trajectory GPS trajectory multi-scale attributes multi-scale attributes spatio-temporal convolution spatio-temporal convolution trajectory segmentation trajectory segmentation travel mode identification travel mode identification
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| GB/T 7714 | Fan, Kunkun , Li, Daichao , Jin, Xinlei et al. A multi-scale attributes fusion model for travel mode identification using GPS trajectories [J]. | GEO-SPATIAL INFORMATION SCIENCE , 2024 . |
| MLA | Fan, Kunkun et al. "A multi-scale attributes fusion model for travel mode identification using GPS trajectories" . | GEO-SPATIAL INFORMATION SCIENCE (2024) . |
| APA | Fan, Kunkun , Li, Daichao , Jin, Xinlei , Wu, Sheng . A multi-scale attributes fusion model for travel mode identification using GPS trajectories . | GEO-SPATIAL INFORMATION SCIENCE , 2024 . |
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This paper proposes a novel model for named entity recognition of Chinese crop diseases and pests. The model is intended to solve the problems of uneven entity distribution, incomplete recognition of complex terms, and unclear entity boundaries. First, a robustly optimized BERT pre-training approach-whole word masking (RoBERTa-wwm) model is used to extract diseases and pests' text semantics, acquiring dynamic word vectors to solve the problem of incomplete word recognition. Adversarial training is then introduced to address unclear boundaries of diseases and pest entities and to improve the generalization ability of models in an effective manner. The context features are obtained by the bi-directional gated recurrent unit (BiGRU) neural network. Finally, the optimal tag sequence is obtained by conditional random fields (CRF) decoding. A focal loss function is introduced to optimize conditional random fields (CRF) and thus solve the problem of unbalanced label classification in the sequence. The experimental results show that the model's precision, recall, and F1 values on the crop diseases and pests corpus reached 89.23%, 90.90%, and 90.04%, respectively, demonstrating effectiveness at improving the accuracy of named entity recognition for Chinese crop diseases and pests. The named entity recognition model proposed in this study can provide a high-quality technical basis for downstream tasks such as crop diseases and pests knowledge graphs and question-answering systems.
Keyword ：
adversarial training adversarial training crop diseases and pests crop diseases and pests deep learning deep learning named entity recognition named entity recognition pre-training language model pre-training language model
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| GB/T 7714 | Liang, Jianqin , Li, Daichao , Lin, Yiting et al. Named Entity Recognition of Chinese Crop Diseases and Pests Based on RoBERTa-wwm with Adversarial Training [J]. | AGRONOMY-BASEL , 2023 , 13 (3) . |
| MLA | Liang, Jianqin et al. "Named Entity Recognition of Chinese Crop Diseases and Pests Based on RoBERTa-wwm with Adversarial Training" . | AGRONOMY-BASEL 13 . 3 (2023) . |
| APA | Liang, Jianqin , Li, Daichao , Lin, Yiting , Wu, Sheng , Huang, Zongcai . Named Entity Recognition of Chinese Crop Diseases and Pests Based on RoBERTa-wwm with Adversarial Training . | AGRONOMY-BASEL , 2023 , 13 (3) . |
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The digital economy is an important engine for building a modern economic system. Corporate investment is an important factor driving the growth of the digital economy. The development and decision-making of the digital economy industry requires an urgent insight into the structural characteristics of the investment and financing of related companies and their temporal and spatial evolution patterns. This paper takes Fujian Province, the ideological source and practical starting point of "Digital China" as a research case, based on the investment and financing data of digital economy enterprises from 2000 to 2021, adopts complex network analysis and negative binomial regression model, and takes prefecture-level cities as the basic research unit to explore spatial characteristics and influencing factors of investment and financing of digital economy enterprises in Fujian Province. This research finds that: firstly, the investment and financing scale of digital economy enterprises in Fujian shows an increasing trend, and the source of investment has changed from non-digital economy enterprises to digital economy enterprises. Secondly, the proportion of inter-provincial of investment has gradually increased. Inter-provincial of investment increases from 856 million yuan in 2000 to 28.808 billion yuan in 2021, and the proportion increases from 11.59% to 31.06%. The amount of financing is "high in the east and low in the west". Thirdly, Fuzhou has always been the preferred city for corporate investment, but with the passage of time, Xiamen, Quanzhou, and other hubs continue to emerge, agglomerating to form the Fuzhou-Xiamen-Quan Corridor at its core. Fourthly, among the influencing factors, policies and the development environment of informatization have a significant role in promoting the investment and financing connection of digital economy enterprises, and the influence of geographical distance on the investment and financing connection of digital industry is gradually weakened. Finally, combined with the spatiotemporal evolution of the development of the digital industry in Fujian and its influencing factors, the paper puts forward policy suggestions, in order to provide scientific support for the construction of "Digital Fujian" and the sustained and healthy development of the digital economy in Fujian. © 2023 Journal of Geo-Information Science. All rights reserved.
Keyword ：
digital economy digital economy enterprise investment and financing enterprise investment and financing Fujian Fujian network analysis network analysis spatio-temporal evolution spatio-temporal evolution
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| GB/T 7714 | Wei, J. , Wu, S. , Peng, P. et al. Exploring the Digital Industry Development in Fujian Province: A Perspective of Enterprise Investment and Financing [企业投融资视角下福建省数字产业发展时空演化] [J]. | Journal of Geo-Information Science , 2023 , 25 (2) : 354-367 . |
| MLA | Wei, J. et al. "Exploring the Digital Industry Development in Fujian Province: A Perspective of Enterprise Investment and Financing [企业投融资视角下福建省数字产业发展时空演化]" . | Journal of Geo-Information Science 25 . 2 (2023) : 354-367 . |
| APA | Wei, J. , Wu, S. , Peng, P. , Lu, F. , Xu, Y. . Exploring the Digital Industry Development in Fujian Province: A Perspective of Enterprise Investment and Financing [企业投融资视角下福建省数字产业发展时空演化] . | Journal of Geo-Information Science , 2023 , 25 (2) , 354-367 . |
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随着互联网租赁自行车（共享单车）的兴起，“共享单车+地铁”“共享单车+公交”已成为城市通勤的主要接驳方式，但共享单车的“潮汐效应”也成为共享单车管理和资源调配的“痛点”和“难点”。因此，发现共享单车的“潮汐规律”，准确预测共享单车停车区（电子围栏）的租还需求，对于共享单车的有序规范发展，优化用车体验和环境等具有重要意义。本文首先基于共享单车订单数据和“电子围栏”空间数据，提出一种识别共享单车潮汐点的时空模型并分析其潮汐性时空特征。该模型将潮汐点定义为短时间内因大量共享单车租或还从而导致无车可租或无车位可停的电子围栏，然后根据电子围栏在某时间段的状态进行分类，并赋予不同的缺车/缺停指数。结果显示该模型能够精准识别特定时段出现的潮汐点。随后，基于共享单车订单、城市信息点（POI）、道路、人口、土地利用、气温、风速等时空数据，并考虑局部范围内的电子围栏相关性，构建KNNLightGBM模型来预测共享单车租还需求：(1)利用主成分分析（Principal Component Analysis,PCA）进行特征提取；(2)利用KNN(K Nearest Neighbors)算法计算局部范围内电子围栏之间相关信息；(3)整合PCA提取的特征向量和电子围栏相关信息作为输入特征，利用LightGBM方法进行租还需求预测；(4)评估影响租还需求预测的特征重要性。结果表明：与常用的4种机器学习方法进行对比，KNN-LightGBM在不同时间尺度下的预测实验中RMSE、MAE的平均值均最小，R~2和r平均值均最大，预测效果较好；利用KNN计算局部范围内的电子围栏相关性，能够有效的提高预测精度，与LightGBM相比，KNN-LightGBM的RMSE和MAE分别降低了10%和11%,R~2和r分别提高了3%和4%；共享单车的历史订单数据对租还需求预测最为重要，与最近公共交通接驳站距离的重要性次之。
Keyword ：
共享单车 共享单车 厦门 厦门 时空模型 时空模型 机器学习 机器学习 潮汐性 潮汐性 电子围栏 电子围栏 需求预测 需求预测
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| GB/T 7714 | 柯日宏 , 吴升 , 柯玮文 . 一种识别共享单车潮汐点的时空模型和基于KNN-LightGBM的租还需求预测方法 [J]. | 地球信息科学学报 , 2023 , 25 (04) : 741-753 . |
| MLA | 柯日宏 et al. "一种识别共享单车潮汐点的时空模型和基于KNN-LightGBM的租还需求预测方法" . | 地球信息科学学报 25 . 04 (2023) : 741-753 . |
| APA | 柯日宏 , 吴升 , 柯玮文 . 一种识别共享单车潮汐点的时空模型和基于KNN-LightGBM的租还需求预测方法 . | 地球信息科学学报 , 2023 , 25 (04) , 741-753 . |
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