Expert Systems with Applications最新文献_第10页

Multi-session transformers and multi-attribute integration of items for sequential recommendation

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-03-26 DOI: 10.1016/j.eswa.2025.127266

Jiahao Hu , Ruizhen Chen , Yihao Zhang , Yong Zhou

{"title":"Multi-session transformers and multi-attribute integration of items for sequential recommendation","authors":"Jiahao Hu , Ruizhen Chen , Yihao Zhang , Yong Zhou","doi":"10.1016/j.eswa.2025.127266","DOIUrl":"10.1016/j.eswa.2025.127266","url":null,"abstract":"<div><div>Modeling sequential dependencies plays a significant role in simulating the dynamic changes in users’ interests, and the introduction of deep learning can address long sequence data to some extent, thereby enabling more precise capture of these changes. However, most existing models still struggle to train sequences with insufficient interaction information or overly long sequences, and they also fail to capture the genuine intentions of users reflected by the interaction behaviors. Additionally, they overlook the characteristic that items interacted with by users are not strictly ordered and are highly homogeneous within a certain period, while the items between different periods are likely to be heterogeneous. In this paper, we propose a sequential recommendation model based on Multi-session Transformers and multi-attribute integration of items (MTMISRec), which enriches the missing interaction information of sparse data by integrating items’ attributes with users’ historical interaction sequences and distinguishes the true intentions of users under similar interactions. Furthermore, we set a time threshold to partition items with interaction intervals within this threshold into a session, thereby capturing homogeneous relationships within each session. We employ the dual attention mechanism to perform local attention within each session and introduce the learned type weights of each session into the complete interaction sequence to perform global attention, thereby blurring the sequential relationships within sessions and integrating global relevance with local details to handle overly long sequences precisely. We conducted extensive experiments on four datasets, and the results demonstrate that MTMISRec surpasses advanced sequential models on sparse and dense datasets.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127266"},"PeriodicalIF":7.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Grouped convolution dual-attention network for time series forecasting of water temperature in offshore aquaculture net pen

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-03-26 DOI: 10.1016/j.eswa.2025.127438

Xiaoyi Sun , Wenqiang Liu , Mengqi Wang , Jingsen Zhang , Ferrante Neri , Yang Wang

{"title":"Grouped convolution dual-attention network for time series forecasting of water temperature in offshore aquaculture net pen","authors":"Xiaoyi Sun , Wenqiang Liu , Mengqi Wang , Jingsen Zhang , Ferrante Neri , Yang Wang","doi":"10.1016/j.eswa.2025.127438","DOIUrl":"10.1016/j.eswa.2025.127438","url":null,"abstract":"<div><div>As a novel open aquaculture technique that approaches ecological farming, offshore aquaculture net pen provides significant value for the sustainable development of aquaculture. Water temperature, being a critical water quality parameter, directly influences the growth and development of fish. Moreover, trends in water temperature can guide the timing of relay in terrestrial-marine aquaculture models. Therefore, real-time monitoring and accurate multi-step prediction of water temperature can effectively ensure the safety of fish production and avoid severe economic losses due to weather changes. However, the openness of the offshore aquaculture net pen environment makes water temperature susceptible to spatial and temporal impacts of external factors, characterized by non-linearity, dynamics, and complexity, making accurate water temperature prediction challenging. This paper proposes a Grouped Convolution Dual-Attention Network (CDANet) framework for multivariate time series prediction based on grouped dual-attention convolution, which fully considers the spatiotemporal correlation between climate conditions and water quality parameters in the pen area, the spatial distribution of water body, and the temporal dependency of historical periods in sequence data. The framework includes a global attention feature extraction module to focus on complex relationships between various factors and a local attention feature extraction module that can overcome the shortcomings of attention mechanisms and handle anomalies. When applied to predict water temperature in offshore aquaculture net pen, the model achieved RMSEs of 0.1314, 0.1525, and 0.2002 for future 2, 6, and 12 time steps, respectively, representing improvements of 44.05%, 29.33%, and 31.56% compared to the other models in the comparative experiments.</div><div>Ablation experiments show that each component of the CDANet model can extract different information patterns from training data, demonstrating structural effectiveness. The experimental results indicate that the proposed method can accurately predict water temperature changes in offshore aquaculture net pen.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127438"},"PeriodicalIF":7.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Multi-View mutual learning network for multimodal fake news detection

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-03-26 DOI: 10.1016/j.eswa.2025.127407

Wei Cui , Xuerui Zhang , Mingsheng Shang

{"title":"Multi-View mutual learning network for multimodal fake news detection","authors":"Wei Cui , Xuerui Zhang , Mingsheng Shang","doi":"10.1016/j.eswa.2025.127407","DOIUrl":"10.1016/j.eswa.2025.127407","url":null,"abstract":"<div><div>Multimodal fake news is more deceptive than unimodal content and often has adverse social and economic impacts. However, most existing methods learn modal features from a single perspective, without considering simultaneously learning and sharing knowledge across modalities from different perspectives. Our work presents a novel Multi-View Mutual Learning (MVML) network for multimodal fake news detection, which explores the semantic relationship between words and scenes, as well as words and objects, and investigates the semantic connection that exists between global concepts and local objects from multiple perspectives. We first construct text-scenes and text-objects graphs respectively, and perform intra-graph inference to obtain multi-view features. Then, the multi-view fusion layer based on the cross-view attention mechanism interactively models the cross-view dependencies between the image and text. The extracted features before feeding into the final classifier are further processed via a feed-forward attention module, which adaptively reweights and aggregates the features for redundancy reduction. In addition, to exploit the respective advantages of two multi-view classifiers, we propose a mutual learning mechanism that allows them to perform knowledge distillation and align the learning targets. The proposed MVML is thoroughly assessed on four publicly available benchmark datasets, and the findings demonstrate that it outperforms the existing standard approaches.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"279 ","pages":"Article 127407"},"PeriodicalIF":7.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Reliable forecasting non-linear triaxial mechanical response of recycled aggregate concrete by knowledge-enhanced, modified, explainable and replicable machine learning algorithms

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-03-26 DOI: 10.1016/j.eswa.2025.127326

Hao-Yu Zhu , Ming-Zhi Guo , Yan Zhang

{"title":"Reliable forecasting non-linear triaxial mechanical response of recycled aggregate concrete by knowledge-enhanced, modified, explainable and replicable machine learning algorithms","authors":"Hao-Yu Zhu , Ming-Zhi Guo , Yan Zhang","doi":"10.1016/j.eswa.2025.127326","DOIUrl":"10.1016/j.eswa.2025.127326","url":null,"abstract":"<div><div>The constitutive modelling is the only method to describe the triaxial stress–strain behavior of cement-based materials while its theoretical deduction, modelling parameters determination and numerical calibrations made it difficult to be further applied. To overcome the limitation of constitutive modelling, a comprehensive machine learning (ML) approach, including Artificial Neural Network (ANN), Gaussian Process (GP), Gradient Boosting (GB) and Optimized Gaussian Process (OGP) was firstly proposed to predict triaxial mechanical behavior of recycled aggregate concrete (RAC). The data augment technology was employed to increase the training data size from 249 to 580, effectively improving the generalization performance. The performance statistics of the aforementioned ML models were compared and validated by R<sup>2</sup>, MAE, RMSE, and Taylor diagram, showing that the OGP had the best study ability and prediction accuracy. The 99 % prediction results generated by the OGP model concentrated within the ± 10 % confidence interval (R<sup>2</sup> = 0.991, MAE = 1.04, RMSE = 0.122). Furthermore, to address the black box nature of ML models, the shapley additive explanation and partial dependence analysis were employed to elucidate the underlying arithmetic mechanism. Finally, the best OGP model was compared with previous constitutive method and further utilized to validate its applicability. Unlike classical constitutive modeling, which requires specialized expertise, the proposed ML approach, available as open source at <span><span>https://doi.org/10.13140/RG.2.2.15784.89608</span><svg><path></path></svg></span>, offered an accessible and effective solution for predicting triaxial behavior with experimental data.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127326"},"PeriodicalIF":7.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

A machine learning-incorporated heuristic column generation algorithm for truck grouping and scheduling problem in trailer-swapping transport mode

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-03-26 DOI: 10.1016/j.eswa.2025.127327

Zhaojie Xue , Haopeng Xu , Haipeng Cui , Wenxiang Peng

{"title":"A machine learning-incorporated heuristic column generation algorithm for truck grouping and scheduling problem in trailer-swapping transport mode","authors":"Zhaojie Xue , Haopeng Xu , Haipeng Cui , Wenxiang Peng","doi":"10.1016/j.eswa.2025.127327","DOIUrl":"10.1016/j.eswa.2025.127327","url":null,"abstract":"<div><div>The logistics industry is facing significant challenges in both operation costs and practitioner satisfactions, necessitating a higher efficiency and cost control management. In this study, we introduce a novel trailer-swapping transport mode (TSTM) in long-haul road freight scenario based on container/trailer exchanging and study a truck grouping and scheduling problem (TGSP) with TSTM. We formulate the TGSP as a concise mixed-integer programming model (MILP). We propose a machine learning-based heuristic column generation (CGML) algorithm to solve the problem, where the incorporated machine learning technique can effectively improve the decision-making efficiency and accuracy of the column generation (CG) algorithm. We further assess the performance of the MILP, heuristic CG algorithm, and the proposed CGML algorithm for the TGSP based on massive numerical experiments. Results show that the proposed CGML algorithm outperforms other tested approaches in both solution accuracy and efficiency, especially for large-scale instances. Based on sensitivity analysis, several managerial insights are provided.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127327"},"PeriodicalIF":7.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-03-26 DOI: 10.1016/j.eswa.2025.127380

Dan Liang , Yongjiu Feng , Liang Hong , Xiaohua Tong

{"title":"Longest similar subsequence-modified Hausdorff distance: A new robust approach for measuring distances between linear features","authors":"Dan Liang , Yongjiu Feng , Liang Hong , Xiaohua Tong","doi":"10.1016/j.eswa.2025.127380","DOIUrl":"10.1016/j.eswa.2025.127380","url":null,"abstract":"<div><div>Accurately measuring the distance between linear features is crucial for understanding the similarity between objects. Traditional measures such as the Hausdorff distance (<em>HD</em>) are inadequate in handling length variations and outliers among linear features, and thus reducing the accuracy of similarity assessment. In this paper, we propose a new concept termed Longest Similar Subsequence (<em>LSS</em>), which aims to identify the longest overlapping subsequence of paired linear features. By integrating <em>LSS</em> with a modified Hausdorff Distance (<em>LSS-HD</em>), we propose a matching method that is based on <em>LSS-HD</em> and adaptive threshold-selection. The adaptive threshold-selection method, named the Connected Bin Threshold Selection Algorithm (<em>CBTSA</em>), is based on the distance histogram analysis. Experimental results clearly demonstrate that the <em>LSS</em>-based <em>HD</em> measure is more robust compared to the <em>HD</em> measure without <em>LSS</em> constraints. In the road matching experiments, our matching accuracy, with an F1-score of over 0.96, is significantly higher than that of the matching algorithms (Opt and OILRM), which are also solely based on distance-similarity metrics.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127380"},"PeriodicalIF":7.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

SA-TPE: An ideal thumbnail-preserving encryption method based on selective area

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-03-26 DOI: 10.1016/j.eswa.2025.127275

Yuexi Peng , Zeng Huang , Zhijun Li , Shaobo He

{"title":"SA-TPE: An ideal thumbnail-preserving encryption method based on selective area","authors":"Yuexi Peng , Zeng Huang , Zhijun Li , Shaobo He","doi":"10.1016/j.eswa.2025.127275","DOIUrl":"10.1016/j.eswa.2025.127275","url":null,"abstract":"<div><div>Cloud storage platform is widely used to store images due to easy uploading and space-saving. To ensure the security and preview of images in the cloud, an image privacy protection strategy called thumbnail-preserving encryption (TPE) has been proposed, which can effectively balance availability and privacy. However, existing TPE methods have some problems such as low efficiency and high memory expansion rate. To address these issues, this paper proposes a selective area encryption method, which selectively encrypts some areas of the image based on the information entropy of blocks. The algorithm adopts the permutation-diffusion framework and uses pseudo-random sequences generated by a new discrete memristor-based chaotic map. Basic experiments show that the NPCR value of the proposed method is close to the ideal value, and it can recover the original image under the interference of Salt & Pepper noise and data loss. Moreover, several relevant TPE methods are considered for the comparison, and simulation results demonstrate that our method has better performance in time consumption and memory expansion rate.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127275"},"PeriodicalIF":7.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Employment of fuzzy inference system in prediction of optimal solution area for thermal stress generated in the friction stir welding process

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-03-26 DOI: 10.1016/j.eswa.2025.127342

Masoud Seidi , Saeed Yaghoubi , Ali Shirazi

{"title":"Employment of fuzzy inference system in prediction of optimal solution area for thermal stress generated in the friction stir welding process","authors":"Masoud Seidi , Saeed Yaghoubi , Ali Shirazi","doi":"10.1016/j.eswa.2025.127342","DOIUrl":"10.1016/j.eswa.2025.127342","url":null,"abstract":"<div><div>The study of thermal stress in the friction stir welding (FSW) process is of particular importance due to its direct effect on the quality of manufactured part. The present research work is concerned with implementation of novel method to find the best solution area in friction stir welding process. The numerical simulation of FSW has been done using LS-Dyna software. The investigated variables include the rotational speed, transverse speed and shoulder diameter. Due to the necessity of reducing the tensile-thermal stress in FSW operation, the aim of current research work is to minimize this factor. Each variable has five levels and according to Taguchi method, the number of numerical tests was reduced to 25. After performing the simulation of FSW operation, the hierarchical clustering on inputs and output variables has been performed and based on similarity level (more than 80 %), the number of clusters was computed to ten. The extraction rules acquired from the employing of clusters were considered as input of the fuzzy inference system using MATLAB software. According to the surface and heat map plots obtained from the fuzzy inference system, the solution area was determined. Based on the response sensitivity analysis in the range of process variables, the most dependency of the tensile-thermal stress changes was on the rotational speed. In the appropriate feasible solutions set, the rotational speed was gained about 710 rpm and the ranges of the transverse speed and shoulder diameter were computed to, in turn, [70–110] (mm/min) and [19.5–23] (mm).</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127342"},"PeriodicalIF":7.5,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Frequency bounds for edges and paths in optimal Hamiltonian cycle based on frequency Kis

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-03-26 DOI: 10.1016/j.eswa.2025.127264

Yong Wang, Pengbo Liu, Yanlong He

引用次数: 0

A novel complex (p,q,r)- spherical fuzzy TOPSIS framework for sustainable urban development assessment

IF 7.5 1区计算机科学

Expert Systems with Applications Pub Date : 2025-03-25 DOI: 10.1016/j.eswa.2025.127288

Muhammad Rahim , Shah Zeb Khan , Adel M. Widyan , A. Almutairi , Hamiden Abd El-Wahed Khalifa

{"title":"A novel complex (p,q,r)- spherical fuzzy TOPSIS framework for sustainable urban development assessment","authors":"Muhammad Rahim , Shah Zeb Khan , Adel M. Widyan , A. Almutairi , Hamiden Abd El-Wahed Khalifa","doi":"10.1016/j.eswa.2025.127288","DOIUrl":"10.1016/j.eswa.2025.127288","url":null,"abstract":"<div><div>Sustainable urban development (SUD) projects aim to enhance infrastructure, services, and facilities in cities to improve residents’ quality of life, promote economic growth, and ensure long-term sustainability. As urbanization accelerates globally, decision-makers face significant challenges in selecting projects that balance environmental, economic, social, and technological factors while aligning with strategic urban planning goals. The complexity of these decisions is further heightened by uncertainties in stakeholder opinions, evolving policy frameworks, and real-world constraints. To address these challenges, this study introduces a multi-criteria group decision-making (MCGDM) framework designed specifically for evaluating SUD projects. The proposed methodology leverages complex <span><math><mrow><mo>(</mo><mi>p</mi><mo>,</mo><mi>q</mi><mo>,</mo><mi>r</mi><mo>)</mo><mo>-</mo></mrow></math></span> spherical fuzzy sets (<span><math><msub><mrow><mi>Com</mi></mrow><mrow><mo>(</mo><mi>p</mi><mo>,</mo><mi>q</mi><mo>,</mo><mi>r</mi><mo>)</mo></mrow></msub></math></span> SFSs) to provide a more flexible and adaptive decision-making structure. These fuzzy sets allow decision-makers to model varying degrees of membership with greater adaptability, ensuring a more precise and comprehensive evaluation of alternatives. The primary contribution of this study lies in its parametric approach, which enhances the dynamism and adaptability of decision-making in complex urban development scenarios. To achieve this, the study is structured into three phases. First, we introduce the fundamental notations and operational laws of <span><math><msub><mrow><mi>Com</mi></mrow><mrow><mo>(</mo><mi>p</mi><mo>,</mo><mi>q</mi><mo>,</mo><mi>r</mi><mo>)</mo></mrow></msub></math></span> SFSs, followed by the development of aggregation operators to handle uncertainty in expert evaluations. In the second phase, we construct a TOPSIS-based approach utilizing these aggregation operators, enabling systematic ranking of SUD project alternatives. The effectiveness of the proposed approach is demonstrated through a numerical example evaluating five alternatives across seven criteria, capturing key factors influencing sustainable urban planning. Finally, the results are compared with existing decision-making methodologies to validate the robustness, effectiveness, and applicability of the proposed framework. By providing a structured, data-driven, and adaptable approach, this study aims to assist urban planners and policymakers in making more informed, balanced, and sustainable decisions for future urban development.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"278 ","pages":"Article 127288"},"PeriodicalIF":7.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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