Buchumschlag

Crowd Flow Prediction: An Integrated Approach Using Dynamic Spatial–Temporal Adaptive Modeling for Pattern Flow Relationships

Fuente: Wiley Open Access

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Zain Ul Abideen, Xiaodong Sun, Chao Sun
Format:	Artículo Open Access
Veröffentlicht:	Wiley 2024
Schlagworte:	Journal of Forecasting
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Temporal Patterns in Migration Flows Evidence from South Sudan
von: Thomas Schincariol, et al.
Veröffentlicht: (2024)

Forecasting European Union Electronic Trading Systems Phase 4 Spot Prices Using Data‐Driven Hybrid Deep Learning Models: Integrating Energy and Market Activity as Controls
von: Noman Arshed, et al.
Veröffentlicht: (2026)

Spatial–Temporal based Crowd Flow Prediction Using Multiscale Dynamic Residual Learning
von: Zain Ul Abideen, et al.
Veröffentlicht: (2025)

A New Multivariate Decomposition–Ensemble Approach With Multisource Heterogeneous Data for Crude Oil Price Forecasting
von: Zhengling Zhao, et al.
Veröffentlicht: (2026)

Adaptive Model Integration for Stock Price Forecasting With CNN‐ATTN‐BiLSTM
von: Yi Xiao, et al.
Veröffentlicht: (2026)

A Matrix‐Based Hidden Markov Model for Consumer Credit Analysis
von: Borui Qi, et al.
Veröffentlicht: (2026)

A Quantification Approach of Changes in Firms' Financial Situation Using Neural Networks for Predicting Bankruptcy
von: Philippe du Jardin
Veröffentlicht: (2024)

Revisiting the Volatility Dynamics of REITs Amid Uncertainty and Investor Sentiment: A Predictive Approach in GARCH‐MIDAS
von: Xu Xiangxin, et al.
Veröffentlicht: (2025)

Innovative Techniques to Predict Churn in the French Insurance Industry: Integration of Machine Learning With the Grabit Model
von: Christophe Schalck, et al.
Veröffentlicht: (2025)

Leveraging Machine Learning to Predict Food Waste Quantity: Focusing on Military Dining Facilities as Large‐Scale Food Service Operations
von: YongSun Kim, et al.
Veröffentlicht: (2026)

Image‐Based Deep Learning Models for Stock Predictions: Combining Line, Candlestick, and Bar Charts
von: Wei‐Chao Lin, et al.
Veröffentlicht: (2026)

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models
von: Saptarshi Ganguly, et al.
Veröffentlicht: (2026)

A Dynamic Fuzzy Modeling Method for Interval Time Series and Applications in Range‐Based Volatility Prediction
von: Leandro Maciel, et al.
Veröffentlicht: (2025)

A Rich‐Spatial and Multiscaled Transformer‐Based Approach for Long‐Term Multivariate Time‐Series Forecasting Problem
von: Linh Nguyen Thi My, et al.
Veröffentlicht: (2025)

Enhancing Neural Network Volatility Forecasting: Decomposed Volatility Modeling
von: Xuzheng Ren, et al.
Veröffentlicht: (2026)

Robust Prediction Intervals for Time Series Forecasting: A Bootstrap and Bayesian Approach
von: Betty X.Y. Chu, et al.
Veröffentlicht: (2026)

Enhancing Volatility Prediction: A Wavelet‐Based Hierarchical Forecast Reconciliation Approach
von: Adam Clements, et al.
Veröffentlicht: (2026)

A Comparison of Realized Measures of Integrated Volatility: Price Duration‐ vs. Return‐Based Approaches
von: Björn Schulte‐Tillmann, et al.
Veröffentlicht: (2026)

Enhancing the Potential of Random Forest Technique With an Adaptive Horse Herd Optimization Framework for Electric Load Prediction
von: Manvi Mishra, et al.
Veröffentlicht: (2026)

Forecasting of S&P 500 ESG Index by Using CEEMDAN and LSTM Approach
von: Divya Aggarwal, et al.
Veröffentlicht: (2024)

Leveraging an Integrated First and Second Moments Modeling Approach for Optimal Trading Strategies: Evidence From the Indian Pharma Sector in the Pre‐ and Post‐COVID‐19 Era
von: Himanshu Kautkar, et al.
Veröffentlicht: (2025)

Data Quality Improvement for Financial Distress Prediction: Feature Selection, Data Re‐Sampling, and Their Combinations in Different Orders
von: Chih‐Fong Tsai, et al.
Veröffentlicht: (2025)

Ensemble Multitask Prediction of Air Pollutants Time Series: Based on Variational Inference, Data Projection, and Generative Adversarial Network
von: Kang Wang, et al.
Veröffentlicht: (2024)

Predicting Enterprise Bankruptcy With HBA‐DGNN: An Innovative Approach by Hypergraph and Bidirectional Attention‐Based Dual GNNs
von: Yuhao Zhu, et al.
Veröffentlicht: (2026)

On Capturing Multi‐Scale Market Dynamics for High‐Frequency Stock Price Forecasting Using a Hybrid Attention‐Based Deep Learning Model
von: Runze Jiang, et al.
Veröffentlicht: (2026)

Whether Uncertainty Theory Can Enhance GDP Forecasting From Energy: A New Uncertain MIDAS Model
von: Yuxin Shi, et al.
Veröffentlicht: (2025)

Modeling and Forecasting Stochastic Seasonality: Are Seasonal Autoregressive Integrated Moving Average Models Always the Best Choice?
von: Evangelos E. Ioannidis, et al.
Veröffentlicht: (2025)

Measuring the Default Risk of Small Business Loans: Improved Credit Risk Prediction Using Deep Learning
von: Yiannis Dendramis, et al.
Veröffentlicht: (2025)

Potential Demand Forecasting for Steel Products in Spot Markets Using a Hybrid SARIMA‐LSSVM Approach
von: Junting Huang, et al.
Veröffentlicht: (2025)

Threshold MIDAS Forecasting of Canadian Inflation Rate
von: Chaoyi Chen, et al.
Veröffentlicht: (2025)

Dynamic Econometric Models: A State‐Space Formulation
von: Mariane B. Alves, et al.
Veröffentlicht: (2025)

Forecasting With Dynamic Factor Models Estimated by Partial Least Squares
von: Samuel Rauhala
Veröffentlicht: (2026)

A Multiscale Transformer Model for Long Time Series Forecasting Based on Discrete Wavelet Transform and Residual Learning Modules
von: Menghan Li, et al.
Veröffentlicht: (2025)

Combined Effects of Fat‐Tail and Spread Forecasting on Pairs Trading: A Hybrid Model Based on Integrating VAR With GRU Models
von: Yuhee Kwon, et al.
Veröffentlicht: (2025)

Stock Return Prediction Based on a Functional Capital Asset Pricing Model
von: Ufuk Beyaztas, et al.
Veröffentlicht: (2025)

A Two‐Stage Interpretable Model to Explain Classifier in Credit Risk Prediction
von: Lu Wang, et al.
Veröffentlicht: (2025)

Novel Aligned Correlation Method to Estimate Lead–Lag Relationship Between Time Series
von: Kartikay Gupta, et al.
Veröffentlicht: (2025)

Modelling and Forecasting of Exchange Rate Pairs Using the Kalman Filter
von: Paresh Date, et al.
Veröffentlicht: (2024)

A Frailty Cumulative Link Model for Enhanced Prediction of Loss Given Default Distribution
von: Ruey‐Ching Hwang, et al.
Veröffentlicht: (2025)

Forecasting sovereign CDS spreads with a regime‐switching combination method
von: Jianping Li, et al.
Veröffentlicht: (2024)