Results 51 to 60 of about 18,244,857 (290)

HUTFormer: Hierarchical U-Net transformer for long-term traffic forecasting

Communications in Transportation Research
Traffic forecasting, which aims to predict traffic conditions based on historical observations, has been an enduring research topic and is widely recognized as an essential component of intelligent transportation.
Zezhi Shao, Fei Wang, Tao Sun, Chengqing Yu, Yuchen Fang, Guangyin Jin, Zhulin An, Yang Liu, Xiaobo Qu, Yongjun Xu   +9 more
doaj   +1 more source

Volatility forecasting [PDF]

, 2005
Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical ...
Tim Bollerslev, Diebold, Francis X., Torben G. Andersen, Francis X. Diebold, Andersen, Torben G., Peter F. Christoffersen, Bollerslev, Tim, Christoffersen, Peter F.   +7 more
core  

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Inverse Design of Nanoparticulate Materials

Advanced Materials, EarlyView.
Inverse design shifts nanomaterial development from empirical trial‐and‐error to predictive model‐driven strategies. It can rely on knowledge‐based, data‐based, or hybrid process and property functions. This perspective article provides a practical framework for applying inverse design based on instructive examples. It discusses which modeling approach
Nabi Etienne Traoré, Annika Mauch, Michelle Berthold, Lukas Pflug, Wolfgang Peukert, Nicolas Vogel   +5 more
wiley   +1 more source

DEformer: Dual Embedded Transformer for Multivariate Time Series Forecasting

IEEE Access
Deep learning models have significantly addressed the challenges of multivariate time series forecasting. Recently, Transformer-based models which have primarily focused on either temporal or inter-variate (spatial) dependencies have demonstrated ...
Minje Kim, Suwon Lee, Sang-Min Choi
doaj   +1 more source

Stationarity Exploration for Multivariate Time Series Forecasting

CoRR
Deep learning-based time series forecasting has found widespread applications. Recently, converting time series data into the frequency domain for forecasting has become popular for accurately exploring periodic patterns. However, existing methods often cannot effectively explore stationary information from complex intertwined frequency components.
Hao Liu, Chun Yang, Zhang xiaoxing, Rui Ma, Xiaobin Zhu 0001   +4 more
openaire   +3 more sources

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

Integrative Multi‐Omics Analysis Reveals a Mitochondrial–Immune Axis Associated With Neoadjuvant Chemotherapy Response in High‐Grade Serous Ovarian Cancer

Advanced Science, EarlyView.
Integrative multi‐omics analysis delineates a mitochondrial–immune axis governing neoadjuvant chemotherapy response in high‐grade serous ovarian cancer. Immune‐active tumors exhibit enhanced B‐cell infiltration and favorable sensitivity, whereas metabolically rewired tumors display oxidative phosphorylation dependency and resistance.
Wei Jiang, Yi Wang, Xiaohang Lu, Qianlan Yao, Libing Xiang, Xu Cai, Xiaoyu Tu, Shaoxian Tang, Ying Xu, Yufan Cheng, Liming Shen, Huijuan Yang   +11 more
wiley   +1 more source

Volatility Forecasting [PDF]

Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical ...
Tim Bollerslev, Torben G. Andersen, Francis X. Diebold, Peter F. Christoffersen   +3 more
core   +4 more sources

Forecasting Inflation Using Univariate and Multivariate Time Series

JISR Management and Social Sciences & Economics, 2009
The purpose of the study is to forecast inflation in Pakistan from January to June 2008. This study set out to redress the deficiency and explicitly use of time series techniques solely for forecasting purposes.
Azam Ali, S.M. Husnain Bokhari
doaj