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ZhaoMY93's Projects

dapper icon dapper

Data Assimilation with Python: a Package for Experimental Research

dpcnn-textcnn-pytorch-inception icon dpcnn-textcnn-pytorch-inception

本项目主要为针对DPCNN(Deep Pyramid Convolutional Neural Networks for Text Categorization )文本分类(Text Classification)的论文复现以及基于知乎看山杯Inception的修改和复现,后者效果略优。

easy-rl icon easy-rl

强化学习中文教程(蘑菇书),在线阅读地址:https://datawhalechina.github.io/easy-rl/

flowdyn icon flowdyn

python based Finite Volume Solver for 1D hyperbolic equations

glofrim icon glofrim

Globally Applicable Framework for Integrated Hydrological-Hydrodynamic Modelling (GLOFRIM)

lhmp icon lhmp

Lumped Hydrological Models Playgroud

pixel_level_land_classification icon pixel_level_land_classification

Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.

pyrtc icon pyrtc

Codes to implement system-level RTC algorithms based on the PySWMM and Pystorms benchmarking gamma model

pytorch_classification icon pytorch_classification

利用pytorch实现图像分类的一个完整的代码,训练,预测,TTA,模型融合,模型部署,cnn提取特征,svm或者随机森林等进行分类,模型蒸馏,一个完整的代码

sphy icon sphy

Spatial Processes in HYdrology hydrological model

stockpredictionai icon stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

swe icon swe

The Shallow Water Equations teaching code.

swmm-2dca icon swmm-2dca

This code name the Storm Water Management Model Two-Dimensional Cellular Automata (SWMM-2DCA) to simulate inundation characteristics and flow interaction between urban drainage system and surface runoff. For more information please see https://ascelibrary.org/doi/10.1061/%28ASCE%29HE.1943-5584.0002036

swmmio icon swmmio

Python tools for interacting with, editing, and visualizing EPA SWMM5 models

toroexact icon toroexact

Python implementation of the exact Riemann solver of Toro (1999).

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