145 hasil
Menampilkan 1–20 · 0,28 detik · RSS
Intelligent Computing
Scopus
ISSN 2771-5892 · American Association for the Advancement of Science (AAAS) · 145 artikel di indeks
-
Artikel Jurnal
A Graph-Based Method for Molecular Spectral Line Identification
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 spectral lines that incorporates rule-driven and node-level constraints to enhance identification…
-
Artikel Jurnal
Semi-Implicit Temporal Variational Graph Autoencoder for Dynamic Graph Generation
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, prevailing approaches rely on temporal random walks that introduce sampling bias and become prohibitively…
-
Artikel Jurnal
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 secure bank loans with the help of guarantors, forming interconnected networked-loans. While essential…
-
Artikel Jurnal
Neural Network-Aided Linear Parameter-Varying Modeling and Finite-Time Control for Autonomous Driving
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 aimed at enhancing driving safety. The proposed approach focuses on the real-time estimation of…
-
Artikel Jurnal
Probing Privacy Risks in Deep Neural Networks: A Jacobian Rank-Based Analysis of Intermediate Layers
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 often computationally prohibitive or overlook the considerable information leakage occurring from the…
-
Artikel Jurnal
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 at least one critical issue: First, they rely solely on single data sources or static data, failing…
-
Artikel Jurnal
Variable-Adaptive Low-Rank Guidance for Diffusion-Based Atmospheric Super-Resolution
Diffusion-based atmospheric super-resolution can generate realistic high-resolution samples, but unconstrained sampling may still fail to preserve desirable global structure across multiple variables. Such structure is important because downstream meteorological analysis relies not only on local…
-
Artikel Jurnal
Obstacle-Aware Distributed Coverage for Multiagent Systems
Multiagent systems (MASs) are pivotal for large-scale monitoring and exploration, where achieving efficient area coverage is fundamental to comprehensive environmental sensing. However, practical deployments are often hindered by static, nonnavigable obstacles of unknown geometry, which complicate…
-
Artikel Jurnal
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 considering the prolonged charging durations of EVs. Efficiently solving CRP is challenging due to…
-
Artikel Jurnal
LM-TTR: Lightweight Monocular Truck-Type Recognition for Source-Based Overload Control
Truck overloading compromises infrastructure and road safety. Since weight limits vary with axle configurations, accurate truck-type recognition is critical for intelligent source-based overload control systems. However, existing methods usually rely on full-vehicle global views or complex image…
-
Artikel Jurnal
Multi-View Fusion: An Advanced Intelligent Computation for Embodied Agents in IoT-Enabled Insulator Inspection Systems
The intelligent inspection of power grids, a critical component of modern internet of things (IoT) ecosystems, increasingly relies on embodied intelligent agents like drones to ensure operational safety. However, the perceptual accuracy of these agents in identifying insulator anomalies is often…
-
Artikel Jurnal
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 effective content moderation, social analysis, user modeling, and crisis detection. Although large…
-
Artikel Jurnal
Large Language Model-Enhanced Mutual Node-Edge Reinforcement for Inductive Fraud Detection in Financial Systems
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 limitations in synthesizing multi-modal features and handling unseen fraud patterns. This paper…
-
Artikel Jurnal
Improving Event-Level Financial Sentiment Analysis with Adaptive Reasoning Order Chain-of-Thought Prompting
Event-level financial sentiment analysis (EFSA), an emerging research field of considerable interest, aims to extract quintuples of sentiment elements from given financial news articles. Preliminary studies indicate that the sequential reasoning order in chain-of-thought (CoT) prompting…
-
Artikel Jurnal
ZX-Diagram T-Count Reduction Based on Proximal Policy Optimization
In fault-tolerant quantum computing systems, the T gates consume more fault-tolerant resources. In this paper, we propose an automated optimization method based on the Proximal Policy Optimization (PPO) algorithm. We first translate quantum circuits into ZX-diagrams using ZX-calculus, transforming…
-
Artikel Jurnal
L2L-ESN: A Lead-to-Lead Electrocardiogram Synthesis Network for Assisting Myocardial Infarction Diagnosis
Wearable electrocardiogram (ECG) monitoring devices, important terminals in the Internet of Medical Things (IoMT), can provide real-time and rapid myocardial infarction (MI) warning services for large populations. This enables early medical intervention and considerably improves the survival rate…
-
Artikel Jurnal
An Infrastructureless Closed-Loop Authentication Strategy Integrated with Homomorphic Aggregation and Blockchain for the Internet of Vehicles
As a rapidly developing part of the internet of things, the internet of vehicles (IoV) has extremely high security requirements for data interaction. However, the strong dependence of its existing architecture on roadside units has become a key bottleneck for applications in extreme environments…
-
Artikel Jurnal
Identification of Difficult Laryngoscopy via Double-Pose Feature Clustering Network in Patients with Cervical Spondylosis
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 accuracy in preoperative airway assessment. This study developed a deep learning algorithm, the…
-
Artikel Jurnal
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 foundations, offer a promising pathway toward more transparent machine learning (ML). However, a systematic…
-
Artikel Jurnal
FSFDLLM: Financial Statement Fraud Detection Aided by Large Language Models
Financial reporting fraud poses a considerable threat to financial market stability. Traditional detection methods predominantly rely on quantitative data analysis while neglecting the informational value of textual disclosures, and existing text analysis approaches suffer from 3 critical…