# 1/26 Study papers for water project
## Real time series
[Machine learning for real-time aggregated prediction of hospital admission for emergency patients](https://www.nature.com/articles/s41746-022-00649-y)

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[Real-time Forecasting of Time Series in Financial Markets Using Sequentially Trained Many-to-one LSTMs](https://arxiv.org/pdf/2205.04678.pdf)


They use **sequential training**
- It helps generate more data from a given limited time series and then thorough training of the ANN.
- It makes the data heterogeneous so that the overfitting issue of the ANN can be reduced; and
- It facilitates the learning of patterns of the data not only for the entire time series but also for short segments of sequential data.

They apply this approach to a diverse set of financial time series data and show that it can be used to make accurate predictions across different markets.

[MLP implementaiton](https://machinelearningmastery.com/how-to-develop-multilayer-perceptron-models-for-time-series-forecasting/)

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## Cross validation
[A Consolidated Cross-Validation Algorithm for Support Vector Machines via Data Reduction](https://papers.nips.cc/paper_files/paper/2022/file/026aff87942ce636ada884d934cde0ae-Paper-Conference.pdf)

https://neptune.ai/blog/cross-validation-in-machine-learning-how-to-do-it-right

https://medium.com/@poudelsushmita878/cross-validation-in-time-series-forecasting-db2bc7601875

[Challenges of machine learning model validation using correlated behaviour data: Evaluation of cross-validation strategies and accuracy measures](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0236092)

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## LSTM with water quality
[Short-term water quality variable prediction using a hybrid CNN–LSTM deep learning model](https://link.springer.com/article/10.1007/s00477-020-01776-2)

[Water Quality Predictions Based on Grey Relation Analysis Enhanced LSTM Algorithms](https://www.mdpi.com/2073-4441/14/23/3851)

[Water Quality Prediction Method Based on LSTM Neural Network](https://ieeexplore.ieee.org/document/8258814)

## hyp-tuning
[Algorithms for Hyperparameter Tuning of LSTMs for Time Series Forecasting](https://www.mdpi.com/2072-4292/15/8/2076)
[Optimizing LSTM for time series prediction in Indian stock market](https://www.sciencedirect.com/science/article/pii/S1877050920307237)

## LSTM with air quality
[An LSTM-based aggregated model for air pollution forecasting](https://www.sciencedirect.com/science/article/pii/S1309104220301215)


## LSTM + attention head
[Improving time series forecasting using LSTM and attention models](https://link.springer.com/article/10.1007/s12652-020-02761-x)

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## How to implement to our project