Deep learning-based method for weather forecasting: A case study in
  Itoshima
Yuzhong Cheng Linh Thi Hoai Nguyen Akinori Ozaki Ton Viet Ta
Accurate weather forecasting is of paramount importance for a wide range of
practical applications, drawing substantial scientific and societal interest.
However, the intricacies of weather systems pose substantial challenges to
accurate predictions. This research introduces a multilayer perceptron model
tailored for weather forecasting in Itoshima, Kyushu, Japan. Our meticulously
designed architecture demonstrates superior performance compared to existing
models, surpassing benchmarks such as Long Short-Term Memory and Recurrent
Neural Networks.