Results 141 to 150 of about 53,937 (302)
Machine Learning‐Driven Multi‐Objective Optimization of Microchannel Reactors for CO₂ Conversion
Advanced Sustainable Systems, EarlyView.This study introduces a novel method that combines CFD, RSM, and ML to improve a microreactor's performance utilizing the Sabatier reaction. A range of ML models is assessed, and the best one is selected to predict optimal reactor conditions. ML shows the ability to predict performance in just milliseconds, leading to a decrease in computational time ...
Sandeep Kumar +2 more
wiley +1 more source
STC-ViT: Spatio Temporal Continuous Vision Transformer for Weather Forecasting [PDF]
arXivOperational weather forecasting system relies on computationally expensive physics-based models. Recently, transformer based models have shown remarkable potential in weather forecasting achieving state-of-the-art results. However, transformers are discrete and physics-agnostic models which limit their ability to learn the continuous spatio-temporal ...
arxiv
Advanced Theory and Simulations, EarlyView.Increasing half‐cycles intensifies turbulence due to enhanced vortex interactions and flow separation at the diverged‐outlets. Longer wavy ducts are shown to increase flow acceleration, resulting in greater output velocities and more turbulent‐kinetic‐energy production. Wave‐period plays a crucial role in determining turbulent intensity, with amplitude
I. L. Animasaun +2 more
wiley +1 more source
Advanced Theory and Simulations, EarlyView.FMint is introduced as a multi‐modal foundation model that integrates human‐designed solvers and data‐driven methods for fast, accurate simulation of dynamical systems. FMint leverages in‐context learning within a transformer‐based framework to refine coarse numerical solutions.
Zezheng Song, Jiaxin Yuan, Haizhao Yang
wiley +1 more source
Seamless short- to mid-term probabilistic wind power forecasting [PDF]
arXivThis paper presents a method for probabilistic wind power forecasting that quantifies and integrates uncertainties from weather forecasts and weather-to-power conversion. By addressing both uncertainty sources, the method achieves state-of-the-art results for lead times of 6 to 162 hours, eliminating the need for separate models for short- and mid-term
arxiv
USING WEATHER FORECASTS FOR PREDICTING FOREST-FIRE DANGER
, 1925 H. T. Gisborne
openalex +1 more source
Advanced Science, EarlyView.Solution‐processed approach for integration of Fe2O3/WS2 nano‐hybrid composite memristor devices. Remarkable switching characteristics and excellent durability for up to 105 cycles. The device shows ultra‐low energy consumption of 0.072 pJ and excellent environmental stability.
Faisal Ghafoor +11 more
wiley +1 more source
FuXi Weather: A data-to-forecast machine learning system for global weather [PDF]
arXivWeather forecasting traditionally relies on numerical weather prediction (NWP) systems that integrates global observational systems, data assimilation (DA), and forecasting models. Despite steady improvements in forecast accuracy over recent decades, further advances are increasingly constrained by high computational costs, the underutilization of vast
arxiv
Advancements in Biochar as a Sustainable Adsorbent for Water Pollution Mitigation
Advanced Science, EarlyView.Biochar, obtained through pyrolysis of organic waste, serves as a sustainable solution for wastewater treatment due to its adaptability and low‐cost nature. This review comprehensively examines recent advancements in biochar production, functional modifications, and applications, highlighting the integration of machine learning and artificial ...
Devika Laishram +3 more
wiley +1 more source