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docs/_posts/2023-01-15-ANNs-for-Air-Quality-Sameeha.md

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+---
+title: "ANNs for Air Quality Assessment and Pollution Forecasting "
+header:
+  image: /assets/images/unsplash-sameeha-ANNs.jpg
+  # caption: Photo credit: Ella Ivanescu on [**Unsplash**](https://unsplash.com/photos/JbfhNrpQ_dw)
+tags: 
+  - blog
+  - ANNs
+  - projects
+  - SameehaAfrulbasha
+  - medium
+---
+
+Using Artificial Neural Networks for Air Quality Assessment and Pollution Forecasting
+
+## Read it [here](https://medium.com/purdue-sigai/anns-for-air-quality-assessment-and-pollution-forecasting-paper-overview-296019720be3)!
+
+## Key Takeaways from this Article
+  * Artificial neural networks (ANNs) are a type of machine learning model that can be used for air quality assessment and pollution forecasting.
+  * There are several types of ANNs, including feedforward networks, convolutional neural networks, recurrent neural networks, and long short-term memory networks.
+  * MLP and LSTM models were used to predict PM10 concentrations one hour in advance.
+  * Deep learning neural networks like the LSTM have the potential in aiding public policies that prioritize improving air quality and building more sustainable cities.
+  * While both the MLP and LSTM models predicted accurately, the study found that the LSTM model with the BNCV method would be better adapted to data from monitoring stations in the cases of extreme values.
+
+## Like what you see? 
+  Read more about Sameeha and her work here:
+  * [Website](https://sameehaafr.super.site/)    
+  * [GitHub](https://github.com/sameehaafr)
+  * [LinkedIn](https://www.linkedin.com/in/sameeha-afrulbasha/)
+<!-- [^1]: Texture image courtesty of [Lovetextures](http://www.lovetextures.com/) -->