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HyperAI Super Neural
HyperAI Super Neural
Mar 18, 2026 · Artificial Intelligence

How Google’s Gemini Extracted 2.6 Million Flood Events from 150 Countries’ News

Google Research released the open‑source Groundsource flood dataset, built by automatically processing more than 5 million news articles from over 150 countries with the Gemini large‑language model, yielding over 2.6 million verified flood event records that are evaluated against GDACS and DFO for precision, recall, and spatial resolution.

AI extractionGoogleGroundsource
0 likes · 13 min read
How Google’s Gemini Extracted 2.6 Million Flood Events from 150 Countries’ News
Python Programming Learning Circle
Python Programming Learning Circle
Apr 24, 2024 · Big Data

Using the TransBigData Python Library for Mobile Signaling Data Processing, Analysis, and Visualization

This article introduces the TransBigData Python package, explains how to install it, read mobile signaling data with pandas, preprocess and grid the data, identify stay and move events, determine home and work locations, and visualize individual user activity using built‑in functions.

Big DataData visualizationPython
0 likes · 7 min read
Using the TransBigData Python Library for Mobile Signaling Data Processing, Analysis, and Visualization
Python Programming Learning Circle
Python Programming Learning Circle
Apr 17, 2024 · Big Data

Comparative Analysis of Starbucks and Luckin Coffee Store Distribution in China Using Python Data Visualization

Using Python data visualization and geospatial analysis, this article compares the nationwide distribution of Starbucks and Luckin Coffee stores in China, revealing differences in regional concentration, proximity patterns, and statistical insights such as average Luckin stores within 500 m of each Starbucks location.

Big DataPythonStore Distribution
0 likes · 11 min read
Comparative Analysis of Starbucks and Luckin Coffee Store Distribution in China Using Python Data Visualization
Python Programming Learning Circle
Python Programming Learning Circle
Feb 1, 2024 · Big Data

Analyzing the Distribution and Competition Between Starbucks and Luckin Coffee Using Python Data Visualization

Using Python and the Shapely library, this article visualizes and compares the nationwide store distribution of Starbucks and Luckin Coffee, revealing that Starbucks concentrates in coastal first‑tier cities while Luckin is more dispersed, with an average of 0.6 Luckin stores within 500 m of each Starbucks location.

Luckin CoffeePythonShapely
0 likes · 10 min read
Analyzing the Distribution and Competition Between Starbucks and Luckin Coffee Using Python Data Visualization
Qunar Tech Salon
Qunar Tech Salon
Jan 23, 2018 · Artificial Intelligence

Intelligent Business Zone Planning for Super Bus Service Using DBSCAN Clustering and Convex Hull

The article describes how the Super Bus platform leverages unsupervised DBSCAN clustering and a Graham‑scan convex‑hull algorithm, combined with a data‑center and distributed processing framework, to automatically generate compliant service zones that match user demand while improving efficiency and scalability.

DBSCANUnsupervised Learningclustering
0 likes · 8 min read
Intelligent Business Zone Planning for Super Bus Service Using DBSCAN Clustering and Convex Hull
21CTO
21CTO
Aug 27, 2017 · Big Data

Uncovering Ghost Bikes: How to Crawl and Analyze Mobike Data in Chengdu

This article details the process of capturing Mobike's public API data, building a high‑performance Python crawler with proxy rotation, storing the results in databases, and performing large‑scale analysis to reveal stationary bikes, travel distances, usage frequency, and urban development patterns in Chengdu.

Big DataBike SharingMobike
0 likes · 13 min read
Uncovering Ghost Bikes: How to Crawl and Analyze Mobike Data in Chengdu