@IntellComput

Intelligent Computing is an open access journal that publishes the latest research outcomes and technological breakthroughs in intelligent computing.

Joined July 2022
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Intelligent Computing: A New Science Partner Journal in the field of #IntelligentComputing. Check out the mission and scope: spj.science.org/page/icomput… Waiving APCs thru Dec 2024. #openaccess
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We are delighted to announce the appointment of Prof. Philip Yu (UIC) and Prof. Osmar R. Zaïane (University of Alberta) as the new Editors‑in‑Chief of Intelligent Computing. We warmly welcome them and look forward to their visionary leadership.
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Exciting news! We are thrilled to announce that Intelligent Computing has achieved a new Impact Factor of 6.4! This represents a remarkable 45.5% increase year-over-year. #IntelligentComputing #AcademicPublishing #ImpactFactor #JCR #OpenAccess
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New research article Large Language Model-Enhanced Mutual Node-Edge Reinforcement for Inductive Fraud Detection in Financial Systems Yong Luo, Yan Huang, Songfeng Lu, Xiaofei Yin, & Yiting Weng #GraphLearning #PeerReviewed #OpenAccess #IntelligentComputing spj.science.org/doi/10.34133…

Large Language Model-Enhanced Mutual Node-Edge Reinforcement for Inductive Fraud Detection in...

Financial fraud detection requires advanced pattern recognition capabilities to address evolving risks. While existing graph neural networks (GNNs) have improved relational modeling, they still face...

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New research article Enhancing the Reliability of Affect Recognition in Social Platforms with Conformal Prediction Samad Roohi, Richard Skarbez, and Hien Nguyen #MachineLearning #AffectiveComputing #PeerReviewed #OpenAccess #IntelligentComputing spj.science.org/doi/10.34133…

Enhancing the Reliability of Affect Recognition in Social Platforms with Conformal Prediction |...

Reliable affect recognition is essential in computational social systems, particularly when analyzing user-generated content on social platforms, where accurate emotion interpretation supports...

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New research article Lightweight Orthogonal Adaptive Multi-scale Decomposition for Enhanced Time Series Prediction Chenhao Jing, Yifan Hu, Lizhao Zhu, Dawei Cheng #TimeSeries #Forecasting #ML #MachineLearning #PeerReviewed #OpenAccess #IntelligentComputing spj.science.org/doi/10.34133…
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New research article Traffic-Aware Electric Vehicle Charge-Route Planning Using Data-Driven Ant Colony Optimization Xin-Can Wang, Yuan-Ting Zhong, Yue-Jiao Gong, Sheng Bi, and Jun Zhang spj.science.org/doi/full/10.… #EVs #Charging #PeerReviewed #OpenAccess #IntelligentComputing

Traffic-Aware Electric Vehicle Charge-Route Planning Using Data-Driven Ant Colony Optimization |...

Charge-route planning (CRP) optimizes the route with charging schedules for electric vehicles (EVs) in order to minimize time and expense, thereby enhancing the overall user experience, especially...

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New research article FSFDLLM: Financial Statement Fraud Detection Aided by Large Language Models Yumeng Dai, Yanyu Qian, Xiaoguang Wang, Yixin Liu, and Chenxu Wang #LLMs #PeerReviewed #OpenAccess #IntelligentComputing spj.science.org/doi/10.34133…

FSFDLLM: Financial Statement Fraud Detection Aided by Large Language Models | Intelligent Computing

Financial reporting fraud poses a considerable threat to financial market stability. Traditional detection methods predominantly rely on quantitative data analysis while neglecting the informational...

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New article Orthogonality in Quantum-Probabilistic Machine Learning: An Investigation on Multiqubit Encoding Sheng-Chen Bai, Kun Zhang, and Shi-Ju Ran #QuantumComputing #TensorNetworks #MachineLearning #PeerReviewed #OpenAccess #IntelligentComputing spj.science.org/doi/10.34133…

Orthogonality in Quantum-Probabilistic Machine Learning: An Investigation on Multiqubit Encoding |...

The “black-box” nature of deep learning models fundamentally limits their reliability in critical applications. Tensor networks (TNs), drawing on their interpretable, quantum-probabilistic foundati...

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New article Identification of Difficult Laryngoscopy via Double-Pose Feature Clustering Network in Patients with Cervical Spondylosis M Wang, F Jia, C Yang, J Fang, J Li, Y Tian, M Li, X Guo, C Wei, Y Han #PeerReviewed #OpenAccess #IntelligentComputing spj.science.org/doi/10.34133…

Identification of Difficult Laryngoscopy via Double-Pose Feature Clustering Network in Patients...

Background: The identification of difficult laryngoscopy is a critical skill for anesthesiologists, particularly in high-risk procedures such as cervical spine surgery, which demands heightened...

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New research article Identifying Financial Risk Contagion with Large Language Models and Temporal Graph Learning Moyang Liu, Letian Zhao, Junqi Chen, Xiang Li, Shuo Zhang, Zhibin Niu #LLMs #GraphLearning #PeerReviewed #OpenAccess #IntelligentComputing spj.science.org/doi/10.34133…

Identifying Financial Risk Contagion with Large Language Models and Temporal Graph Learning |...

Fostering economic growth, particularly the development of small and medium-sized enterprises, is central to United Nations Sustainable Development Goal 8. Small and medium-sized enterprises can...

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New research article Probing Privacy Risks in Deep Neural Networks: A Jacobian Rank-Based Analysis of Intermediate Layers Sheng Liu, Xuefeng Zhang, Tao Huang, Guolong Zheng, Wencheng Yang, Ji Zhang #Privacy #PeerReviewed #OpenAccess #IntelligentComputing spj.science.org/doi/10.34133…

Probing Privacy Risks in Deep Neural Networks: A Jacobian Rank-Based Analysis of Intermediate...

Deep learning models are known to be vulnerable to privacy attacks that can reconstruct or infer sensitive information from the training data. While many privacy assessment methods exist, they are...

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New research article Neural Network-Aided Linear Parameter-Varying Modeling and Finite-Time Control for Autonomous Driving Mohamed Saber, Mohamed Ouahi, Saad Motahhir, and Nabil El Akchioui #AutonomousDriving #PeerReviewed #OpenAccess #IntelligentComputing spj.science.org/doi/10.34133…

Neural Network-Aided Linear Parameter-Varying Modeling and Finite-Time Control for Autonomous...

Irresponsible driving behavior remains one of the primary causes of road accidents. Given the limited effectiveness of repressive measures, this study proposes an intelligent-vehicle-based solution...

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New research article FFD-DHG: Financial Fraud Detection Based on Dynamic Heterogeneous Graph Representation Learning Chenxu Wang, Mengqin Wang, Ruofan Wang, and Xiaoguang Wang #GNN #FraudDetection #PeerReviewed #OpenAccess #IntelligentComputing spj.science.org/doi/10.34133…

FFD-DHG: Financial Fraud Detection Based on Dynamic Heterogeneous Graph Representation Learning |...

With the expansion of the capital market, financial fraud incidents have become increasingly frequent. Existing financial fraud detection methods have made some progress, but most approaches overlook...

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New research article Semi-Implicit Temporal Variational Graph Autoencoder for Dynamic Graph Generation Shenglong Liu, Yixin Li, Xiao Peng, Xu Cheng, Zicai Zhou, and Dawei Cheng #PeerReviewed #OpenAccess #GNN #IntelligentComputing spj.science.org/doi/10.34133…

Semi-Implicit Temporal Variational Graph Autoencoder for Dynamic Graph Generation | Intelligent...

Graph simulation has emerged as a practical route to release realistic yet privacy-preserving network data, especially for temporal graphs that evolve through node and edge arrivals. However,...

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New research article A Graph-Based Method for Molecular Spectral Line Identification Yijun Pan, Tianwei Zhang, Ruqiao An, Baoquan Gao, Huaxi Chen, and Donghui Quan #Astronomy #Astrophysics #Astrochemistry #PeerReviewed #OpenAccess #IntelligentComputing spj.science.org/doi/10.34133…

A Graph-Based Method for Molecular Spectral Line Identification | Intelligent Computing

To address the high computational cost associated with molecular identification in spectral lines, we propose a graph-based feature learning framework to determine the molecular composition of...

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New research article Scalable Audiovisual Masked Autoencoders for Efficient Affective Video Facial Analysis X Wu, J Xue, X Yin, Y Shi, L Fu, D Huang, Y Wang, J Zhang, J Nie, and J Wang #AffectiveComputing #PeerReviewed #OpenAccess #IntelligentComputing spj.science.org/doi/10.34133…

Scalable Audiovisual Masked Autoencoders for Efficient Affective Video Facial Analysis | Intellig...

Affective video facial analysis (AVFA) has emerged as a key research field for building emotion-aware intelligent systems, yet this field continues to suffer from limited data availability. In recent...

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New article Construction and Simulation of an Automatic Generation Model of Security Defense Strategies Based on Reinforcement Learning Shuhan Yang, Xiaolong Deng, Jingying Wang, Ruizhi Xiong, and Junwen Lu #PeerReviewed #OpenAccess #IntelligentComputing spj.science.org/doi/10.34133…

Construction and Simulation of an Automatic Generation Model of Security Defense Strategies Based...

To address the issue of traditional defense strategies being inflexible in handling new types of attacks due to resource rigidification, this study focuses on constructing a self-generating defense...

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New research article ELfolio: Strategy Evolution via Large Language Models for Portfolio Optimization Xirui Zeng, Cen Chen, Yanhao Wang, and Yuqi Liang #PeerReviewed #OpenAccess #IntelligentComputing #LLMs #Finance #ReinforcementLearning #DeepLearning spj.science.org/doi/10.34133…

ELfolio: Strategy Evolution via Large Language Models for Portfolio Optimization | Intelligent...

With increasing financial market fluctuation, classical portfolio optimization methods, particularly those based on static market assumptions and heavily relying on feature engineering, face consid...

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New research article Mutual Information with Experts: An Approach to Graph Pooling for Graph Neural Networks Tong Yang and Zhong Li #PeerReviewed #OpenAccess #IntelligentComputing #GraphComputing spj.science.org/doi/10.34133…

Mutual Information with Experts: An Approach to Graph Pooling for Graph Neural Networks | Intelli...

Graph neural networks are powerful for graph-structured data, with graph pooling critical for tasks like classification. Graph pooling methods discard nodes to form a coarser graph representation,...

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New review article spj.science.org/doi/10.34133… Graph Learning-Empowered Financial Fraud Detection: Progress and Future Directions Enxia Li, Mengshi Chen, Sheng Xiang, and Ling Chen #PeerReviewed #OpenAccess #IntelligentComputing #FraudDetection #GraphLearning

Graph Learning-Empowered Financial Fraud Detection: Progress and Future Directions | Intelligent...

Financial fraud detection is an important task in ensuring the integrity and security of financial systems. In recent years, it has been shown that graph learning, which utilizes the relational...

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