From 0d449d08350f2837977a0d5836b2abc9487a6790 Mon Sep 17 00:00:00 2001 From: Karim Mache <k.mache@fz-juelich.de> Date: Fri, 28 Mar 2025 22:20:31 +0100 Subject: [PATCH] Add image --- .history/README_20250328221727.md | 3 +++ .history/README_20250328221948.md | 3 +++ .history/README_20250328221958.md | 3 +++ .history/README_20250328222004.md | 4 ++++ .history/README_20250328222021.md | 4 ++++ README.md | 4 +++- 6 files changed, 20 insertions(+), 1 deletion(-) create mode 100644 .history/README_20250328221727.md create mode 100644 .history/README_20250328221948.md create mode 100644 .history/README_20250328221958.md create mode 100644 .history/README_20250328222004.md create mode 100644 .history/README_20250328222021.md diff --git a/.history/README_20250328221727.md b/.history/README_20250328221727.md new file mode 100644 index 0000000..96a095a --- /dev/null +++ b/.history/README_20250328221727.md @@ -0,0 +1,3 @@ +## TOAR-classifier v2: A data-driven classification tool for global air quality stations + +<img src="./figures/toar_classifier_v2.png" alt="My image" with="100"> diff --git a/.history/README_20250328221948.md b/.history/README_20250328221948.md new file mode 100644 index 0000000..00262ee --- /dev/null +++ b/.history/README_20250328221948.md @@ -0,0 +1,3 @@ +## TOAR-classifier v2: A data-driven classification tool for global air quality stations +This study develops a machine learning approach to classify 23,974 air quality monitoring stations in the TOAR database as urban, suburban, or rural using K-means clustering and an ensemble of supervised classifiers. The proposed method outperforms existing classifications, improving suburban accuracy and providing a more reliable foundation for air quality assessments. +<img src="./figures/toar_classifier_v2.png" alt="My image" with="100"> diff --git a/.history/README_20250328221958.md b/.history/README_20250328221958.md new file mode 100644 index 0000000..00262ee --- /dev/null +++ b/.history/README_20250328221958.md @@ -0,0 +1,3 @@ +## TOAR-classifier v2: A data-driven classification tool for global air quality stations +This study develops a machine learning approach to classify 23,974 air quality monitoring stations in the TOAR database as urban, suburban, or rural using K-means clustering and an ensemble of supervised classifiers. The proposed method outperforms existing classifications, improving suburban accuracy and providing a more reliable foundation for air quality assessments. +<img src="./figures/toar_classifier_v2.png" alt="My image" with="100"> diff --git a/.history/README_20250328222004.md b/.history/README_20250328222004.md new file mode 100644 index 0000000..e5ed8e9 --- /dev/null +++ b/.history/README_20250328222004.md @@ -0,0 +1,4 @@ +## TOAR-classifier v2: A data-driven classification tool for global air quality stations +This study develops a machine learning approach to classify 23,974 air quality monitoring stations in the TOAR database as urban, suburban, or rural using K-means clustering and an ensemble of supervised classifiers. The proposed method outperforms existing classifications, improving suburban accuracy and providing a more reliable foundation for air quality assessments. +<img src="./figures/toar_classifier_v2.png" alt="My image" with="100"> + diff --git a/.history/README_20250328222021.md b/.history/README_20250328222021.md new file mode 100644 index 0000000..10ccc5d --- /dev/null +++ b/.history/README_20250328222021.md @@ -0,0 +1,4 @@ +## TOAR-classifier v2: A data-driven classification tool for global air quality stations +This study develops a machine learning approach to classify 23,974 air quality monitoring stations in the TOAR database as urban, suburban, or rural using K-means clustering and an ensemble of supervised classifiers. The proposed method outperforms existing classifications, improving suburban accuracy and providing a more reliable foundation for air quality assessments. +<img src="./figures/toar_classifier_v2.png" alt="My image" with=100> + diff --git a/README.md b/README.md index ae43e66..10ccc5d 100644 --- a/README.md +++ b/README.md @@ -1,2 +1,4 @@ ## TOAR-classifier v2: A data-driven classification tool for global air quality stations -<img src="./figures/toar_classifier_v2.png" alt="My image" with="100"> +This study develops a machine learning approach to classify 23,974 air quality monitoring stations in the TOAR database as urban, suburban, or rural using K-means clustering and an ensemble of supervised classifiers. The proposed method outperforms existing classifications, improving suburban accuracy and providing a more reliable foundation for air quality assessments. +<img src="./figures/toar_classifier_v2.png" alt="My image" with=100> + -- GitLab