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chinese_sentiment

用tensorflow进行中文自然语言处理的情感分析

covid-19

An adaptive model that quantitatively analyzes and predicts vaccination and other control measures on COVID-19

covid-19-nlp-vis

使用 flask + pyecharts 搭建的新冠肺炎疫情数据可视化交互分析网站平台，包含疫情数据获取、每日疫情地图、曲线图展示，数据统计分析、态势感知、确诊人数预测分析算法设计、NLP舆情监测等任务（数据更新到 6.19 ）

covid19_agentbasedsimulation

COVID-ABS: An Agent-Based Model of COVID-19 Epidemic to Simulate Health and Economic Effects of Social Distancing Interventions

echarts-map-data

Echarts 地图数据：世界地图、世界各国地图、**地图、**省份地图、**城市地图。

freebaiduvectordownload

免费的百度地图矢量下载工具，提供学校、道路、小区、POI矢量数据下载

matricesdecontactomdp

model_covid19_dynamics_luxembourg_austria_sweden

This repository contains the codes associated with the study "Modelling COVID-19 dynamics and potential for herd immunity by vaccination in Austria, Luxembourg and Sweden", published in 2021 in Journal of Theoretical Biology: https://doi.org/10.1016/j.jtbi.2021.110874. The main authors of this code are Françoise Kemp (https://www.researchgate.net/profile/Francoise-Kemp) and Stefano Magni (https://www.researchgate.net/profile/Stefano-Magni-3). If you use our work please cite our journal publication, e.g. as "Françoise Kemp, Daniele Proverbio, Atte Aalto, Laurent Mombaerts, Aymeric Fouquier d’Hérouël, Andreas Husch, Christophe Ley, Jorge Gonçalves, Alexander Skupin, Stefano Magni, Modelling COVID-19 dynamics and potential for herd immunity by vaccination in Austria, Luxembourg and Sweden, Journal of Theoretical Biology, Volume 530, 2021, 110874, ISSN 0022-5193, https://doi.org/10.1016/j.jtbi.2021.110874". This model represents an extension of the epidemiological SEIR model to represent the spread of COVID-19 within a population. It has been extended to include 1) social interaction, 2) undetected cases, 3) disease progression through hospitalization, ICU and death and 4) vaccination. It is fit to time series public data of detected cases, hospital and ICU occupations and death, trough a literature-based parameter set cross validated by means of Bayesian inference and Markov Chain Monte Carlo methods. The model is separately fit to three countries: Luxembourg, Austria and Sweden, thus the repository contains 3 independent python codes, in the form of Jupyther notebooks. Also the time series data to which the model is fit are provided as 3 separate files in the repository, one for each country. The model is employed to investigate a number of topics through simulations, including the impact of social interaction on the epidemic dynamics, estimate of the effective reproduction number Reff(t), the impact of vaccination and the interplay of vaccines rollout speeds and social interaction in the pursuit of herd immunity. The first version of this work appeared as a preprint and is available at https://doi.org/10.1101/2020.12.31.20249088).

seir

Generalized SEIR Epidemic Model (fitting and computation)

travelplan

根据旅游景点的人流量，指定我们的出行计划

two-strain-covid-19-mathematical-model-in-the-us

wuhan-data-analysis

该系列资源是Python疫情大数据分析，涉及网络爬虫、可视化分析、GIS地图、情感分析、舆情分析、主题挖掘、威胁情报溯源、知识图谱、预测预警及AI和NLP应用等。推荐大家结合作者CSDN博客阅读，武汉必胜、湖北必胜、**必胜！

zotero-javascripts

Some JavaScripts used in Zotero to batch process