Air Pollution Prediction
7 papers with code • 0 benchmarks • 1 datasets
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Latest papers
Genetic algorithm-based hyperparameter optimization of deep learning models for PM2.5 time-series prediction
The prediction results of deep learning algorithms are compared with default hyperparameters and random search algorithms to confirm the efficacy of the genetic algorithm approach.
Air Pollution Prediction in Mass Rallies With a New Temporally-Weighted Sample-Based Multitask Learner
Then, we construct a temporal support vector regressor (TSVR), which puts more emphasis on the adjacent samples by considering the fact that the crowd usually flows promptly and disorderly in mass rallies.
PCACE: A Statistical Approach to Ranking Neurons for CNN Interpretability
In this paper we introduce a new problem within the growing literature of interpretability for convolution neural networks (CNNs).
Deciphering Environmental Air Pollution with Large Scale City Data
Air pollution poses a serious threat to sustainable environmental conditions in the 21st century.
MSSTN: Multi-Scale Spatial Temporal Network for Air Pollution Prediction
We further present a novel deep convolutional neural network model, named Multi-Scale Spatial Temporal Network (MSSTN), for the learning task on this data structure.
Multi-task Learning for Aggregated Data using Gaussian Processes
Our model represents each task as the linear combination of the realizations of latent processes that are integrated at a different scale per task.
Real-time Air Pollution prediction model based on Spatiotemporal Big data
In this paper, based on this spatiotemporal Big data, we propose a real-time air pollution prediction model based on Convolutional Neural Network (CNN) algorithm for image-like Spatial distribution of air pollution.