Feature selection is an essential step in the data preprocessing phase of machine learning that involves selecting a subset of relevant features (variables) from a larger set. In weather …

Mar 29, 2024 · By providing computers with a systematic way to describe and analyze data, feature vectors empower machines to uncover hidden patterns and make informed decisions …

Dec 15, 2016 · Neural networks seem to be the popular machine learn-ing model choice for weather forecasting because of the ability to capture the non-linear dependencies of past …

Temperature prediction plays a crucial role in various domains, and machine learning has emerged as a powerful tool for achieving accurate predictions.

Nov 14, 2023 · Machine learning (ML) is increasing in popularity in the field of weather and climate modelling. Applications range from improved solvers and preconditioners, to …

Aug 22, 2019 · Reported results exhibit that MLP and LSTM models using the proposed feature vector, they show promising results for univariate forecasting. We tested our method on a real …

May 15, 2025 · Artificial intelligence-based models for global weather forecasting have advanced rapidly, but research on high-resolution data-driven limited area models remains scarce. Here …

Jan 3, 2025 · Traditional numerical weather prediction (NWP) methods are being outpaced by cutting-edge AI models like GraphCast by Google Deepmind, offering faster and more reliable …

May 7, 2019 · This paper explores three machine learning models for weather prediction namely Support Vector Machine (SVM), Artificial Neural Network (ANN) and a Time Series based …

Based on the above analysis, a new weather prediction model based on the improved quantum genetic algorithm (IQGA) [22] and support vector machines (SVMs) [23 – 25] is proposed to …