Zobrazeno 1 - 10
of 263
pro vyhledávání: '"multivariate time series forecasting"'
Autor:
Bubryur Kim, K. R. Sri Preethaa, Sujeen Song, R. R. Lukacs, Jinwoo An, Zengshun Chen, Euijung An, Sungho Kim
Publikováno v:
Journal of Big Data, Vol 11, Iss 1, Pp 1-37 (2024)
Abstract The construction industry substantially contributes to the economic growth of a country. However, it records a large number of workplace injuries and fatalities annually due to its hesitant adoption of automated safety monitoring systems. To
Externí odkaz:
https://doaj.org/article/81c64d9d4c39449cae3d17a37e5c47e4
Publikováno v:
IEEE Access, Vol 12, Pp 153851-153858 (2024)
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 exc
Externí odkaz:
https://doaj.org/article/c816f68e705a4bf5b6165d3b40f5a7e9
Autor:
Dilip Kumar Sharma, Ravi Prakash Varshney, Saurabh Agarwal, Amel Ali Alhussan, Hanaa A. Abdallah
Publikováno v:
Heliyon, Vol 10, Iss 7, Pp e27860- (2024)
Time series forecasting across different domains has received massive attention as it eases intelligent decision-making activities. Recurrent neural networks and various deep learning algorithms have been applied to modeling and forecasting multivari
Externí odkaz:
https://doaj.org/article/d898ba414c5e4026b4dfb898b2478757
Autor:
Sadman Sakib, Mahin K. Mahadi, Samiur R. Abir, Al-Muzadded Moon, Ahmad Shafiullah, Sanjida Ali, Fahim Faisal, Mirza M. Nishat
Publikováno v:
Heliyon, Vol 10, Iss 6, Pp e27795- (2024)
Bangladesh's subtropical climate with an abundance of sunlight throughout the greater portion of the year results in increased effectiveness of solar panels. Solar irradiance forecasting is an essential aspect of grid-connected photovoltaic systems t
Externí odkaz:
https://doaj.org/article/d9adb43744b341aba1d3300b393e3946
Publikováno v:
IEEE Access, Vol 11, Pp 142087-142099 (2023)
Multivariate time series (MTS) forecasting is a crucial aspect in many classification and regression tasks. In recent years, deep learning models have become the mainstream framework for MTS forecasting. Among these deep learning methods, the transfo
Externí odkaz:
https://doaj.org/article/fb1334a3408d4965a74f9703c3ab0119
Publikováno v:
Supply Chain Analytics, Vol 3, Iss , Pp 100024- (2023)
Inventory control aims to meet customer demands at a given service level while minimizing cost. As a result of market volatility, customer demand is generally changing, and ignoring this uncertainty could lead to under or over-estimation of inventori
Externí odkaz:
https://doaj.org/article/1d3a8b1b15a34305a3dd93b2b1a75919
Autor:
Khorasani, Arian
The focus of this study explores the adaptations of the Lag-Llama univariate time series forecasting approach [8] to handle multivariate time series, named LSTM2Lag-Llama. This extension is motivated by the increasing necessity to deal with datasets
Externí odkaz:
http://hdl.handle.net/1866/40296
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