计算机科学最新文献

Data-driven frequency-domain iterative learning control with transfer learning

IF 3.1 3区计算机科学

Mechatronics Pub Date : 2025-04-27 DOI: 10.1016/j.mechatronics.2025.103327

Yu-Hsiu Lee, Yu-Hsiang Chin, Chun-Yuan Hsueh

{"title":"Data-driven frequency-domain iterative learning control with transfer learning","authors":"Yu-Hsiu Lee, Yu-Hsiang Chin, Chun-Yuan Hsueh","doi":"10.1016/j.mechatronics.2025.103327","DOIUrl":"10.1016/j.mechatronics.2025.103327","url":null,"abstract":"<div><div>Data-driven iterative learning control (ILC) can achieve improved tracking performance over model-based ILC by eliminating the fitting error from parametric system representations. Existing data-driven approaches in frequency domain take advantage of the affordability and speed associated with acquiring non-parametric frequency response function data for effective learning. However, the quality of data significantly influences the achievable performance. Additionally, a notable drawback is that learning is reset whenever the tracked trajectory changes, despite having learned similar frequency contents before. Extending these approaches to multivariate systems with non-negligible coupling is also not straightforward. This paper aims to address the aforementioned challenges in data-driven ILC by employing spectral analysis (SA), which improves the learned data-driven inversion by mitigating the measurement noise. Fast and robust convergence is made possible through an iteration-varying learning gain. Also proposed is a transfer learning strategy in the frequency domain, wherein the inversion learned in specific frequency bin(s) will be preserved and utilized to expedite convergence in subsequent tasks. The presented ILC algorithm based on SA naturally extends to the multi-input multi-output (MIMO) framework, and the convergence can be ensured by complex-valued matrix analysis. The methodology is experimentally validated on a galvanometer for the SISO case and an H-type dual-drive gantry system for the MIMO case, demonstrating enhanced performance, transfer learning capabilities, and applicability to MIMO systems.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"108 ","pages":"Article 103327"},"PeriodicalIF":3.1,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MRLCD-A: Lag-aware alignment for multivariate time series forecasting in multiple scenarios

IF 7.4 1区管理学

Information Processing & Management Pub Date : 2025-04-27 DOI: 10.1016/j.ipm.2025.104191

Dezhi Sun , Jiwei Qin , Zihao Zhang , Xizhong Qin , Huiguo Zhang

引用次数: 0

CAOC: Cooperative adaptive optimal control algorithm for networked direct current servo systems

IF 3.1 3区计算机科学

Mechatronics Pub Date : 2025-04-27 DOI: 10.1016/j.mechatronics.2025.103312

Loi Ho Thai-Dai, Luy Nguyen Tan, Dung Nguyen Le, Lam Phan Huynh, Giap Nguyen Hoang

{"title":"CAOC: Cooperative adaptive optimal control algorithm for networked direct current servo systems","authors":"Loi Ho Thai-Dai, Luy Nguyen Tan, Dung Nguyen Le, Lam Phan Huynh, Giap Nguyen Hoang","doi":"10.1016/j.mechatronics.2025.103312","DOIUrl":"10.1016/j.mechatronics.2025.103312","url":null,"abstract":"<div><div>This letter proposes a novel cooperative adaptive optimal control (CAOC) algorithm for networked direct current servo (DCS) systems to achieve tracking synchronization in a cooperative system, where the leader generates the desired speed and the DCS followers track its output and synchronize with their own neighbors according to the communication graph topology in real time. As consensus tracking error dynamics is affected by the control inputs of the neighboring agents, the cost function for each agent includes not only its consensus tracking error and energy, but also the energies of the neighbors. Firstly, based on the Lyapunov theory and backstepping techniques, we design feedforward controllers that generate augmented control inputs to transform local consensus tracking dynamics in strict feedback form into affine form. Secondly, based on adaptive dynamic programming (ADP), we design the CAOC algorithm to minimize the performance index function. Finally, we conduct the simulation and experiment on the STM32F103 microcontrollers to validate the effectiveness of the proposed algorithm.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"108 ","pages":"Article 103312"},"PeriodicalIF":3.1,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing text-to-SQL conversion techniques through the integration of intelligent agents and large language models

IF 7.4 1区管理学

Information Processing & Management Pub Date : 2025-04-27 DOI: 10.1016/j.ipm.2025.104136

Samuel Ojuri , The Anh Han , Raymond Chiong , Alessandro Di Stefano

{"title":"Optimizing text-to-SQL conversion techniques through the integration of intelligent agents and large language models","authors":"Samuel Ojuri , The Anh Han , Raymond Chiong , Alessandro Di Stefano","doi":"10.1016/j.ipm.2025.104136","DOIUrl":"10.1016/j.ipm.2025.104136","url":null,"abstract":"<div><div>In many organizations, retrieving valuable information from complex databases has traditionally required specialized technical skills, often leaving non-technical professionals dependent on others for timely insights. This study presents an approach that allows anyone, even without knowledge of query languages, to directly interact with databases by asking questions in everyday language. We achieve this by combining advanced generative language models, such as a high-capacity Generative Pre-trained Transformer (GPT) model, with intelligent software agents that translate natural language queries into precise SQL statements. Our evaluation compares different strategies, including models specifically trained on a particular database domain versus those guided by only a handful of examples. The results show that training a model with tailored examples yields more accurate and reliable database queries than relying solely on minimal guidance for the given use case. This work highlights the practical value of refining model complexity and balancing computational costs to empower business users with easy, direct access to data. By reducing reliance on technical teams, organizations can enable faster, more informed decision-making and foster a more inclusive environment where everyone can uncover data-driven insights on their own.</div></div>","PeriodicalId":50365,"journal":{"name":"Information Processing & Management","volume":"62 5","pages":"Article 104136"},"PeriodicalIF":7.4,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

GTHNN: Graph Transformer and Sequential Hypergraph Neural Network with dynamic aggregation mechanism for multi-task prediction

IF 7.4 1区管理学

Information Processing & Management Pub Date : 2025-04-27 DOI: 10.1016/j.ipm.2025.104180

Yanchao Liu, Qing Song, Wenchao Song, Pengzhou Zhang, Chi Zhang

{"title":"GTHNN: Graph Transformer and Sequential Hypergraph Neural Network with dynamic aggregation mechanism for multi-task prediction","authors":"Yanchao Liu, Qing Song, Wenchao Song, Pengzhou Zhang, Chi Zhang","doi":"10.1016/j.ipm.2025.104180","DOIUrl":"10.1016/j.ipm.2025.104180","url":null,"abstract":"<div><div>Information cascade multitask prediction, which encompasses information diffusion prediction and information popularity prediction, is crucial to understand how information items spread on social networks with a wide range of real-world applications. Existing works primarily focus on information diffusion prediction or information popularity prediction by using the sequential or graph-structured model, which could yield over-smoothing and over-squashing during aggregating user preference features, resulting in suboptimal performance. In this paper, we propose a novel <u><strong>G</strong></u>raph <u><strong>T</strong></u>ransformer and Sequential <u><strong>H</strong></u>ypergraph <u><strong>N</strong></u>eural <u><strong>N</strong></u>etwork with dynamic aggregation mechanism framework (<u><strong>GTHNN</strong></u>), which is specifically tailored for multitask prediction. Specifically, to mitigate over-squashing of user dynamic features, we construct a sequential hypergraph neural network with the dynamic aggregation mechanism to directly aggregate user dynamic preferences across global periods. To reduce over-smoothness of user static features, the graph transformer architecture is designed to explore the potential high-level social homogeneity among users. To improve the expressive ability of user features, we further build the structure-enhanced self-attention mechanism with exponential decay factor to exhume the complex dependencies among any user. Finally, the prediction layer is applied to simultaneously predict the next infected user and information popularity. Extensive experiments demonstrate that our model outperforms the advanced methods on four real-world datasets, exhibiting the superior performance of our model. The study is beneficial for gaining a better understanding of multitask prediction and revealing the potential of graph transformer architecture.</div></div>","PeriodicalId":50365,"journal":{"name":"Information Processing & Management","volume":"62 5","pages":"Article 104180"},"PeriodicalIF":7.4,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A bidirectional bi-objective graph search model for sustainable urban railway alignment optimization

IF 7.5 2区计算机科学

Engineering Applications of Artificial Intelligence Pub Date : 2025-04-26 DOI: 10.1016/j.engappai.2025.110943

Tianlong Zhang , Yan Gao , Shuangting Xu , Ting Deng , Qing He , Paul Schonfeld , Yang Zou , Dong Liang , Ping Wang

{"title":"A bidirectional bi-objective graph search model for sustainable urban railway alignment optimization","authors":"Tianlong Zhang , Yan Gao , Shuangting Xu , Ting Deng , Qing He , Paul Schonfeld , Yang Zou , Dong Liang , Ping Wang","doi":"10.1016/j.engappai.2025.110943","DOIUrl":"10.1016/j.engappai.2025.110943","url":null,"abstract":"<div><div>Designing railway alignments in building-dense urban areas is a challenging task, requiring consideration of both costs and impacts on existing buildings and the environment. Achieving a viable solution necessitates the application of computer-aided techniques for three-dimensional (3D) global path searches while simultaneously optimizing multiple objectives. To tackle this challenge, this study proposes a bidirectional bi-objective graph search model. This model efficiently searches the 3D space to generate high-quality railway alignment solutions that simultaneously consider both comprehensive costs (including railway construction, ecological, and affected building costs) and carbon emissions (covering emissions from railways and buildings). It provides valuable reference solutions for designers, enhancing the design efficiency. The model includes two main innovations: (1) the ability to quickly search the entire 3D space using a graph-based strategy, generating multiple alignment solutions that meet design constraints in a single optimization process, and (2) the ability to accurately and efficiently account for the impact of railway alignments on existing buildings during optimization. Testing the model on a real-world urban case demonstrates its capability to generate multiple alternative railway alignments within minutes. The Pareto balanced solution achieves an 18.91 % reduction in comprehensive costs and a 13.46 % decrease in carbon emissions compared to manual design. The estimation error of affected building areas is approximately 2 %–4 % along the approximately 40 km alignment. Overall, the significance of this study lies in exploring the application of efficient graph search algorithms in the multi-objective optimization design of railway alignments in urban areas, advancing ongoing research in this field.</div></div>","PeriodicalId":50523,"journal":{"name":"Engineering Applications of Artificial Intelligence","volume":"153 ","pages":"Article 110943"},"PeriodicalIF":7.5,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143874358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mean-shift-based robust distributed set-membership fusion filtering for sensor network systems with outliers

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-04-26 DOI: 10.1016/j.automatica.2025.112345

Hongbo Zhu , Minane Joel Villier Amuri , Jinzhong Shen , Xueyang Li

{"title":"Mean-shift-based robust distributed set-membership fusion filtering for sensor network systems with outliers","authors":"Hongbo Zhu , Minane Joel Villier Amuri , Jinzhong Shen , Xueyang Li","doi":"10.1016/j.automatica.2025.112345","DOIUrl":"10.1016/j.automatica.2025.112345","url":null,"abstract":"<div><div>Outliers can contaminate the communication and measurement processes of many sensor network systems, which may be induced by environmental disturbances, model uncertainties, sensor faults or errors, subnetwork faults or malicious cyberattacks. Once the distributed set-membership filter (DSMF) is used into such sensor network systems with outliers for distributed state estimation, the estimation performance can be seriously degraded in each sensor node. To address this problem, this article proposes a mean-shift-based trust set and zonotope extraction mechanism to modify the zonotopic DSMF toward building resilience and robustness against outliers. The proposed mechanism is capable of sifting out the outlier-contaminated local corrected zonotopes, and a sufficient condition for the full effectiveness of it is given and proved. Based on the proposed mechanism, the mean-shift-based outliers-robust zonotopic DSMF (MSRDSMF) is derived for estimating the state of a sensor network system in a distributed way. Simulation experiment results demonstrate the practical validity and superiority of the MSRDSMF in effectively suppressing the effects of outliers.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"177 ","pages":"Article 112345"},"PeriodicalIF":4.8,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143874523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Energy-based control approaches for weakly coupled electromechanical systems

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-04-26 DOI: 10.1016/j.automatica.2025.112336

Najmeh Javanmardi , Pablo Borja , Mohammad Javad Yazdanpanah , Jacquelien M.A. Scherpen

引用次数: 0

Comprehensive survey on deoldifying images and videos

IF 4 3区计算机科学

Computers & Electrical Engineering Pub Date : 2025-04-26 DOI: 10.1016/j.compeleceng.2025.110396

Aradhana Mishra, Bumshik Lee

{"title":"Comprehensive survey on deoldifying images and videos","authors":"Aradhana Mishra, Bumshik Lee","doi":"10.1016/j.compeleceng.2025.110396","DOIUrl":"10.1016/j.compeleceng.2025.110396","url":null,"abstract":"<div><div>In the field of image processing, Deoldify refers to the revitalization of aging visual media, such as historical photos and videos, which present unique challenges due to accumulated defects, unpredictable degradation, and physical damage. Traditional restoration techniques, such as manual retouching, chemical treatments, and manual colorization, are often insufficient for addressing the complexity of these tasks, particularly in areas such as denoising, super-resolution, brightness enhancement, deblurring, colorization, compression, and inpainting. These methods lack automation, scalability, and precision, especially when dealing with severely degraded media. This survey highlights the limitations of conventional approaches. We focus on how recent advancements in deep learning, including convolutional neural networks, variational autoencoders, generative adversarial networks, Transformers, and diffusion models, have surpassed traditional methods in these subtasks. By leveraging deep learning, tasks such as noise reduction, contrast restoration, and resolution enhancement are performed with greater accuracy and efficiency, significantly improving restoration outcomes. This work aims to provide a comprehensive review of these techniques, showcasing their superiority over traditional methods while identifying challenges such as dataset limitations and the need for better handling of extreme degradation,and proposing directions for future research in old media restoration.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"124 ","pages":"Article 110396"},"PeriodicalIF":4.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143876539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improvement of tracking control performance of quadrotors under Simultaneous Planning, Estimation, and Execution

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2025-04-26 DOI: 10.1016/j.conengprac.2025.106360

Zhou Liu , Shaoting Liu , Yang Qu , Lilong Cai

{"title":"Improvement of tracking control performance of quadrotors under Simultaneous Planning, Estimation, and Execution","authors":"Zhou Liu , Shaoting Liu , Yang Qu , Lilong Cai","doi":"10.1016/j.conengprac.2025.106360","DOIUrl":"10.1016/j.conengprac.2025.106360","url":null,"abstract":"<div><div>The dynamics of quadrotors present significant challenges, including underactuation, external disturbances, and parametric uncertainties. To address these challenges and achieve precise given-time tracking, this paper propose a novel control strategy called Simultaneous Planning, Estimation, and Execution (SPEE) for quadrotor systems. The SPEE strategy integrates dynamic and kinematic equations. Initially, the kinematic equations planning the desired higher-order derivative online to compensate for current state errors. Subsequently, the dynamics equation estimates lumped disturbances and executes the desired higher-order derivative algebraically. Unlike traditional control methods, the proposed strategy eliminates the need for fine-tuning feedback gains and a precise system model, ensuring state convergence within a specified time frame. Theoretical error bounds of this strategy are analyzed, and its effectiveness is validated through comprehensive simulations and practical experiments. The closed-loop system demonstrates robust performance against internal uncertainties, external disturbances, and insufficient battery power.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"162 ","pages":"Article 106360"},"PeriodicalIF":5.4,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143877195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0