Package: transformerForecasting Type: Package Title: Transformer Deep Learning Model for Time Series Forecasting Version: 0.1.0 Authors@R: c(person("G H", "Harish Nayak", role = c("aut", "cre"), email = "harishnayak626@gmail.com"), person("Md Wasi Alam", role = c("ths"), email = "mw.Alam@icar.gov.in"), person("B Samuel Naik", role = c("ctb"), email = "banavathsamuelnaik@gmail.com"), person("G Avinash", role = c("ctb"), email = "avinash143stat@gmail.com"), person("Kabilan", "S", role = c("ctb"), email = "kabilan151414@gmail.com"), person("Varshini B S", role = c("ctb"), email = "varshinibs29@gmail.com"), person("Mrinmoy Ray", role = c("ths"), email = "mrinmoy4848@gmail.com"),person("Rajeev Ranjan Kumar", role = c("ths"), email = "rrk.uasd@gmail.com")) Maintainer: G H Harish Nayak Description: Time series forecasting faces challenges due to the non-stationarity, nonlinearity, and chaotic nature of the data. Traditional deep learning models like Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) process data sequentially but are inefficient for long sequences. To overcome the limitations of these models, we proposed a transformer-based deep learning architecture utilizing an attention mechanism for parallel processing, enhancing prediction accuracy and efficiency. This paper presents user-friendly code for the implementation of the proposed transformer-based deep learning architecture utilizing an attention mechanism for parallel processing. References: Nayak et al. (2024) and Nayak et al. (2024) . Imports: ggplot2, keras, tensorflow, magrittr, reticulate (>= 1.20) Suggests: dplyr, knitr, lubridate, readr, rmarkdown, utils License: GPL-3 Encoding: UTF-8 RoxygenNote: 7.3.2 Author: G H Harish Nayak [aut, cre], Md Wasi Alam [ths], B Samuel Naik [ctb], G Avinash [ctb], Kabilan S [ctb], Varshini B S [ctb], Mrinmoy Ray [ths], Rajeev Ranjan Kumar [ths] Depends: R (>= 4.0.0) LazyData: true VignetteBuilder: knitr NeedsCompilation: no Packaged: 2026-07-03 08:44:04 UTC; root Config/pak/sysreqs: libpng-dev python3 Repository: https://harish11999.r-universe.dev Date/Publication: 2025-03-07 11:10:06 UTC RemoteUrl: https://github.com/cran/transformerForecasting RemoteRef: HEAD RemoteSha: 1b61751eb1131e422dd8766ec78466f283a295fb