Results 101 to 110 of about 8,962 (250)

A Novel Encoder-Decoder Model for Multivariate Time Series Forecasting. [PDF]

Comput Intell Neurosci, 2022
Zhang H, Li S, Chen Y, Dai J, Yi Y.
europepmc   +1 more source

Assessing Haitian Consumers' Willingness to Pay a Premium for Aflatoxin‐Compliant Peanut Butter in the Informal Market

Agribusiness, EarlyView.
ABSTRACT Market‐based solutions are increasingly tested to address aflatoxin issues in peanuts in developing countries. Although previous studies have found that Haitian grocery store shoppers are willing to pay a 21% premium for peanut butter with levels of aflatoxin that meet international standards, no information is available for the much larger ...
Phendy Jacques, Stevens Azima, Maurice Doyon   +2 more
wiley   +1 more source

A Spatial–Temporal Time Series Decomposition for Improving Independent Channel Forecasting

Mathematics
Forecasting multivariate time series is a pivotal task in controlling multi-sensor systems. The joint forecasting of all channels may be too complex, whereas forecasting the channels independently may cause important spatial inter-dependencies to be ...
Yue Yu, Pavel Loskot, Wenbin Zhang, Qi Zhang, Yu Gao   +4 more
doaj   +1 more source

Return and Volatility Spillovers Among Major Cotton Markets

Agribusiness, EarlyView.
ABSTRACT This study explores return and volatility transmission among major cotton markets. Several events have disrupted cotton supply and demand in recent years, leading to heightened price volatility and significant shifts in market interconnections.
Susmitha Kalli, Berna Karali, Yangxuan Liu, Munisamy Gopinath   +3 more
wiley   +1 more source

Stacked LSTM for Short-Term Wind Power Forecasting Using Multivariate Time Series Data.

International Journal of Interactive Multimedia and Artificial Intelligence
Currently, wind power is the fast growing area in the domain of renewable energy generation. Accurate prediction of wind power output in wind farms is crucial for addressing the challenges associated the power grid. This precise forecasting enables grid
Manisha Galphade, V. B. Nikam, Biplab Banerjee, Arvind W. Kiwelekar, Priyanka Sharma   +4 more
doaj   +1 more source

Time Series Foundation Models for Multivariate Financial Time Series Forecasting

66 ...
openaire   +2 more sources

Multivariate Probabilistic Time Series Forecasting with Correlated Errors

Advances in Neural Information Processing Systems 37
38th Conference on Neural Information Processing Systems (NeurIPS 2024).
Vincent Zhihao Zheng, Lijun Sun
openaire   +3 more sources

Heterogeneity in Food Price Inflation Convergence Across the EU: Evidence From Club Dynamics and Structural Breaks

Agribusiness, EarlyView.
ABSTRACT This study examines food price inflation rate convergence among EU27 Member States from 2005 to 2024, focusing on structural breaks, external shocks, and regional disparities. Using panel unit root tests and club convergence analysis, the findings reveal no overall convergence but identify multiple convergence clubs.
Tibor Bareith, Imre Fertő
wiley   +1 more source

Enhanced forecasting of shipboard electrical power demand using multivariate input and variational mode decomposition with mode selection

Scientific Reports
Accurate forecasting of shipboard electricity demand is essential for optimizing Energy Management Systems (EMSs), which are crucial for efficient and profitable operation of shipboard power grids. To address this challenge, this paper introduces a novel
Paolo Fazzini, Giuseppe La Tona, Matteo Diez, Maria Carmela Di Piazza   +3 more
doaj   +1 more source

HPMixer: Hierarchical Patching for Multivariate Time Series Forecasting

CoRR
18 pages, 5 figures, 5 tables, PAKDD ...
Jung Min Choi, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme   +2 more
openaire   +2 more sources