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tsp_collection

TSP算法全复现：遗传(GA)、粒子群(PSO)、模拟退火(SA)、禁忌搜索(ST)、蚁群算法(ACO)、自自组织神经网络(SOM)

tsp_quantumannealing

Solving Traveling Saleperson Problem using Quantum Annealing

tsp_solver

Python code for visualizations of algorithms that provide approximate solutions to TSP along with two lower bound approximations

tstables

A Python package to store time series data in HDF5 files using PyTables

tstools-online

Visualize time series obtained from Google Earth Engine and run pyccd on them.

tugofwaroptimization

Tug of War Optimization Algorithm code in matlab and Advances in Metaheuristic Algorithms for Optimal Design of Structures

tutorial-icesat2

tutorial_contents

Geohackweek Tutorial Contents

tutorial_dev

sandbox for developing tutorial codes for 2019 hackweek

twg_idealized_glacier_response

tws_inversion

Generating terrestrial water storage estimates from GPS displacement data.

twsc_recon

Fupeng Li's code for reconstructing total water storage content

tyde

C# code for predicting oceanic tides

typhoon_prediction

# typhoon Analysis satellite images of typhoons by deep-learning (CNN), based on PyTorch. This CNN learns to map the satellite images of typhoons to their max wind speed from. The labeled train set is obtained from agora/JMA. ## Requirements * BeautifulSoup * PIL * Pytorch ## Usage 1. Run `download.py`, download the satellite images of typhoons to folder `tys_raw`. 2. Run `create_samples.py`, convert raw data into the legal samples for our CNN, create two new forlder `train_set` and `test_set`. 3. Train CNN using `train_net.py`, the trained CNN will be saved as a disk file `net_relu.pt`. 4. Run `test_net.py`, analysis the test set. After 10 epoches training the CNN regressor reached mean loss about 8 (knots) in train set and about 10 (knots) in test set.  Here is what this CNN thinks of the top 20 typhoons sorted by max wind. ``` 1 ('197920', 130.27679443359375) 2 ('200914', 127.7662582397461) 3 ('199019', 122.92172241210938) 4 ('200918', 122.84004211425781) 5 ('201614', 122.66597747802734) 6 ('201601', 122.03250885009766) 7 ('201513', 121.75947570800781) 8 ('200922', 121.35771942138672) 9 ('201013', 120.0194091796875) 10 ('201330', 118.92587280273438) 11 ('201419', 117.6025390625) 12 ('198305', 117.10270690917969) 13 ('201422', 116.77259063720703) 14 ('198522', 116.46116638183594) 15 ('201327', 116.42304992675781) 16 ('201216', 116.36921691894531) 17 ('198221', 116.18096923828125) 18 ('199230', 115.96656799316406) 19 ('198210', 115.96611022949219) 20 ('201328', 115.57132720947266) ``` ## Tips * Memory should be at least 1.5G . * This project is written without `cuda()`, while you can use `cuda()` to transfer the CNN onto GPU and speedup the training. * The images and labels are crawled from agora.ax.nii.ac.jp/digital-typhoon , and the labels are refered to JMA(Japan Meteorological agency).

u-blox_gnss

u-blox GNSS receiver library light weight for low power tracking application

uamitgcm

Coupling scripts for Ua and MITgcm

uav-processing-toolbox

Codes, documentation and discussion for the use of single stationary cameras and small drones for Argus-like sampling.

uav_ebal

Distributed energy balance model using SfM data and AWS data

uav_eti

uavproduct

处理无人机影像的代码，使用了OpenMVG，openMVS以及GDAL库等，实现影像几何校正，影像拼接，点云生成等功能

ubx

Arduino Library for u-blox/ublox GNSS/GPS receiver, using I2C or Softserial interface to receive multiple messages

ucl_dwave_summer_school

Using the D-Wave 2000Q to error correct ASCII messages sent over a noisy channel, and understand the physics of quantum annealing. Repo to be used with the Leap IDE.

ucla-hydro

um-fdm

UM Firn Densification Model

umd_etc

Repository containing the UMD_Etc code

umsba

UnifiedMultiSensorBundleAdjustment

unfolded-metaheuristics-preliminary

This repository contains the resulting dataset of the preliminary study on unfolded metaheuristics presented in CEC21

university-gnss_tool

univiewgrace

A module to show the GRACE satellite data

unscented-kalman-filter-ins-mms