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ML | RNN Recurrent Neural Network

ML | RNN Recurrent Neural Network

循環神經網路(recurrent neural network,RNN) RNN是一種特殊的神經網路結構,它透過在時間上的展開來處理序列資料中的依賴關係。在每個時間步(time step),RNN都會接收一個輸入(例如句子中的一個單字),並輸出一個結果(例如下一個單字的預測)。與傳統的前饋神經網路(Feedforward Neural Network, FNN)不同,RNN在每個時間步都會保留一個
2025-01-28
ML
#NWP #ML #AI #RNN
WRF | Vertical Levels and Heights

WRF | Vertical Levels and Heights

WRF Users Guide documentation !!Development Team Announcements > Frequently Asked Questions Hybrid Vertical Coordinate WRF is a hybrid vertical coordinate (HVC) and at the s
2025-01-27
WRF
#WRF #NWP #MPAS #HPC #UCM
WRF | MPAS | UCM and LCZs

WRF | MPAS | UCM and LCZs

WRF-UCM WRF-UCM refers to the Weather Research and Forecasting model (WRF) integrated with an Urban Canopy Model (UCM). This framework is designed to enhance the simulation of urban environments withi
2025-01-27
WRF
#WRF #NWP #MPAS #HPC #UCM #LCZs
ML | ResNet

ML | ResNet

殘差網路概述 殘差神經網路(Residual Neural Network,簡稱 ResNet ) 是一種深度學習模型,旨在解決傳統深度神經網路中常見的梯度消失和梯度爆炸問題。這種網路的核心理念是讓每一層學習與輸入之間的殘差,而非直接學習預期的輸出。這樣的設計使得訓練更深層的模型變得更為有效,並且在增加層數時能保持甚至提高準確率。 ResNet 透過 殘差學習解決了深度網路的退化問題,讓我們可以訓
2025-01-26
ML
#NWP #ML #AI #ResNet
ML | VAE Variational Auto-Encoder

ML | VAE Variational Auto-Encoder

基礎知識回顧 Latent Variable Variations Gaussian Mixture Model Gaussian Mixture Model,即高斯混合模型。生成模型比較主流的三個模型為:隱馬可夫模型HMM、樸素貝葉斯模型NB、高斯混合模型GMM。這裡我們主要為大家介紹GMM。 混合模型是一個可以用來表示在總體分佈中含有N個子分佈的機率模型,它表示了觀測資料在總體中的機率分
2025-01-26
ML
#NWP #ML #AI #VAE #Auto-Encoder #Generative AI
ML | ECMWF | Anemoi

ML | ECMWF | Anemoi

Anemoi Anemoi is a collaborative and open-source framework for developing machine learning weather forecasting models. Named after the Greek gods of the winds, the goal of Anemoi is to provide the key
2025-01-25
ML
#NWP #ML #AI #ECMWF #Anemoi
WRF | MPAS | README.physics_files

WRF | MPAS | README.physics_files

While browsing the WRF repository, I came across an introduction file in version 4.6.1, located at WRF/run/README.physics_files. This file provides a list of external files used by various physical sc
2025-01-24
WRF
#WRF #NWP #MPAS #HPC #MPI
ML | set CUDA_HOME in a conda environment

ML | set CUDA_HOME in a conda environment

set CUDA_HOME in a conda environment 123456micromamba install -c conda-forge cudatoolkit-devwhich nvccnvcc --versionecho $CUDA_HOMEexport CUDA_HOME=$CONDA_PREFIXecho $CUDA_HOME References How to set
2025-01-22
ML
#ML #AI #pytorch #NVIDIA #CUDA
NWP | Clear-sky vs. All-sky Approaches in NWP and DA

NWP | Clear-sky vs. All-sky Approaches in NWP and DA

Clear-sky vs. All-sky Approaches in NWP and DA In the field of Numerical Weather Prediction (NWP) and Data Assimilation (DA), the clear-sky and all-sky approaches represent two different methodologies
2025-01-21
NWP
#WRF #NWP #MPAS #DA
MPAS | UXarray

MPAS | UXarray

UXarray Xarray extension for unstructured climate and global weather data analysis and visualization written around the UGRID conventions. Why? UXarray aims to address the geoscience community need fo
2025-01-17
MPAS
#MPAS #UXarray
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