WhyGIST

WhyGIST's Stars

• svc-develop-team/so-vits-svc

  SoftVC VITS Singing Voice Conversion

  Language:Python25.3k4.8k

• zotero-chinese/styles

  中文 CSL 样式

  Language:XML5k821

• jlechn01/Shanghai-Flood-ABM

  Climate change intensifies the frequency and severity of floods - the most devastating and costly climate-induced hazard. Government adaptations such as dikes or beach nourishments are important, yet insufficient in the face of worsening hazards. They reduce the hazard probability, but the local actions at the household level determine the extent of damages and inequalities in its distributional impacts on various societal groups. To design effective policies and risk reduction strategies it is critical to understand the factors that motivate household adaptive actions. Quantifying the cumulative impacts of these factors on in terms of the speed and scope of household adaptation enables insights into the adaptation behaviour and risk exposure of different social groups. This fosters the design of multi-actor cross-scale flood adaptation strategies which reduce aggregate risks and address “within-country inequalities” of climate change. This paper presents a spatially explicit agent-based model for the case of Shanghai, China to understand the impacts of household climate change adaptation to coastal floods and to draw new insights for policymakers. Specifically, we combine geolocation data of residential buildings with inundation data under various climate change scenarios to model the exposure of households in Shanghai. We further parameterize the households using context-specific micro-level survey data from Shanghai and depict household adaptation decisions using an extended version of the Protection Motivation Theory.

  Language:NetLogo21

• abmgis/abmgis

  Accompanying resources for the book 'Agent-Based Modelling and Geographical Information Systems: A Practical Primer'.

  Language:HTML12064

• nclwater/mesacat

  Mesa Model of Flood Evacuation using OpenStreetMap

  Language:Python32

• nghuyong/weibo-cov

  Weibo-COV: A Large-Scale COVID-19 Social Media Dataset from Weibo

  57396

• fxsjy/jieba

  结巴中文分词

  Language:Python33.1k6.7k

• LMFrank/CrawlerProject

  爬虫项目：链家网（普通/scrapy）、虎扑、维基百科、百度地图api、房天下（分布式爬虫）、微信公众号（代理池爬取）

  Language:Python21063

• apachecn/stanford-game-theory-notes-zh

  📖斯坦福博弈论中文笔记

  Language:Shell18332

• hahaha108/meituanAppSpider

  美团APP爬虫，可获取指定城市范围内所有美食店铺信息，包含店铺名称、类别、评分、所属片区、经纬度、详细地址、优惠套餐情况、营业时间、联系电话、累计售出份数、餐厅简介、特色菜......

  Language:Python342115

• jonbakerfish/TweetScraper

  TweetScraper is a simple crawler/spider for Twitter Search without using API

  Language:Python998311

• Jiamei-Wang/Sentiment-Analysis-Topic-Modeling-for-Hotel-Reviews

  Web Scraping, Sentiment Analysi, Latent Dirichlet Allocation (LDA) topic modelling

  Language:Jupyter Notebook86

• fiduswriter/biblatex-csl-converter

  A set of JavaScript converters: bib(la)tex => json, json => csl, and json => biblatex

  Language:TypeScript3410

• andy123t/shnuthesis

  上海师范大学研究生毕业论文 LaTeX 模板 LaTeX Thesis Template for SHNU

  Language:TeX155

• breakstring/eInkCalendarOfToxicSoul

  毒鸡汤墨水屏日历

  Language:C58994

• latexstudio/GMCMthesis

  2020 年研究生数学建模 LaTeX 模板

  Language:TeX19680

• fo40225/tensorflow-windows-wheel

  Tensorflow prebuilt binary for Windows

  Language:Python3.7k1.5k

• Vincent131499/TextClassifier_Transformer

  个人基于谷歌开源的BERT编写的文本分类器（基于微调方式），可自由加载NLP领域知名的预训练语言模型BERT、Bert-wwm、Roberta、ALBert以及ERNIE1.0

  Language:Python16046

• ymcui/Chinese-BERT-wwm

  Pre-Training with Whole Word Masking for Chinese BERT（中文BERT-wwm系列模型）

  Language:Python9.6k1.4k

• pengming617/bert_classification

  利用bert预训练的中文模型进行文本分类 数据集中文情感分析语料chnsenticorp

  Language:Python30274

• heoijin/Bilibili-Rnak

  Bilibili排行榜-爬虫和数据分析实战

  Language:Python394

• ageitgey/face_recognition

  The world's simplest facial recognition api for Python and the command line

  Language:Python52.9k13.4k

• shenghuo87/vpn

  小明VPN

  15258