Pinned Repositories
-Python---------2--
APSIM-VarDecomp
Decompose the variance contribution of different G*E*M factors on multiple APSIM model outputs
Apsimx
jupter script for Apsimx
awesome-agriculture
Open source technology for agriculture, farming, and gardening
CNN-RNN-Yield-Prediction
This repository contains codes for the paper entitled "A CNN-RNN Framework for Crop Yield Prediction"
CPlantBox
Crop-Yield-Prediction-Comparison-using-ML-DL-Techniques
In this project, we compare and predict the yield of five crops (wheat, barley, jowar, rapeseed & mustard, and bajra) in Rajasthan (district-wise) using three machine learning techniques: random forest, lasso regression and SVM, and two deep learning techniques: gradient descent and RNN LSTM. To apply the models to our data, we divided it into training and testing datasets. Each model is tested twice: once with only "area" and "production" in mind, and then again with additional factors (rainfall and soil type) in mind to predict crop yield. To find the model that most accurately predicts the yield, R2 score, Root Mean Squared Error (RMSE) and Mean Average Error (MAE) are calculated for each model.
crop_yield_prediction
Crop Yield Prediction with Deep Learning
CropPredict
Prediction of crop yields using machine learning.
PCSE
YanZongzheng's Repositories
YanZongzheng/PCSE
YanZongzheng/-Python---------2--
YanZongzheng/APSIM-VarDecomp
Decompose the variance contribution of different G*E*M factors on multiple APSIM model outputs
YanZongzheng/Apsimx
jupter script for Apsimx
YanZongzheng/awesome-agriculture
Open source technology for agriculture, farming, and gardening
YanZongzheng/CNN-RNN-Yield-Prediction
This repository contains codes for the paper entitled "A CNN-RNN Framework for Crop Yield Prediction"
YanZongzheng/CPlantBox
YanZongzheng/Crop-Yield-Prediction-Comparison-using-ML-DL-Techniques
In this project, we compare and predict the yield of five crops (wheat, barley, jowar, rapeseed & mustard, and bajra) in Rajasthan (district-wise) using three machine learning techniques: random forest, lasso regression and SVM, and two deep learning techniques: gradient descent and RNN LSTM. To apply the models to our data, we divided it into training and testing datasets. Each model is tested twice: once with only "area" and "production" in mind, and then again with additional factors (rainfall and soil type) in mind to predict crop yield. To find the model that most accurately predicts the yield, R2 score, Root Mean Squared Error (RMSE) and Mean Average Error (MAE) are calculated for each model.
YanZongzheng/crop_yield_prediction
Crop Yield Prediction with Deep Learning
YanZongzheng/DataAnalysis
气象数据分析代码和部分数据
YanZongzheng/github-slideshow
A robot powered training repository :robot:
YanZongzheng/gitskills
YanZongzheng/Google-Earth-Engine-Python-Examples
Various examples for Google Earth Engine in Python using Jupyter Notebook
YanZongzheng/HyperDL-Tutorial
深度学习教程整理 | 干货
YanZongzheng/jupyter
Jupyter metapackage for installation, docs and chat
YanZongzheng/learngit
learn git practice
YanZongzheng/my-fire
YanZongzheng/pcse-1
Repository for the Python Crop Simulation Environment
YanZongzheng/PPDssat
Pre- Post- process python for DSSAT
YanZongzheng/projectone
this is just a test repository
YanZongzheng/pycrop-yield-prediction
A PyTorch Implementation of Jiaxuan You's Deep Gaussian Process for Crop Yield Prediction
YanZongzheng/PyCrop2ML
CropML Python library
YanZongzheng/PyWaterBal
Unsaturated soil water flow model
YanZongzheng/SICPmatanalysis
this is a for my study storage
YanZongzheng/starter-academic
YanZongzheng/USTC-Course
:heart:**科学技术大学课程资源
YanZongzheng/Utility-Functions
Contains handy functions that get used often
YanZongzheng/waqip
waqip is to download air quality data from aqicn.org (http://aqicn.org).
YanZongzheng/webpage
this is my personal webpage
YanZongzheng/WoDeLunWen
Just writting papers