- 시계열 예측에 사용되는 것은 주로 conv1D-LSTM-CNN-LSTM과 다름-마지막 reference인 전력량 예측 특히 참고
[케라스/머신러닝] 암호화폐 가격예측 개발(2) : CNN과 LSTM활용 : 네이버 블로그 – http://m.blog.naver.com/PostView.naver?blogId=kyy0810&logNo=221525955109&proxyReferer=https:%2F%2Fm.search.naver.com%2Fsearch.naver%3Fpage%3D8%26query%3Dconv%2Blstm%26sm%3Dmtb_pge%26start%3D91%26where%3Dm_web
21.06.07) 비트코인 차트 tensorflow에서 예측함 (Conv1D->LSTM에서 시계열 차트 분석) : 네이버 블로그 – http://m.blog.naver.com/comparkwb/222389067334
Convolutional LSTM Network : A Machine Learning Approach for Precipitation Nowcasting – Data Rabbit-https://flonelin.wordpress.com/2019/09/12/convolutional-lstm-network-a-machine-learning-approach-for-precipitation-nowcasting/
Ch5-CNN-LSTM.ipynb-Colaboratory-https://colab.research.google.com/github/Pseudo-Lab/Tutorial-Book/blob/master/book/chapters/time-series/Ch5-CNN-LSTM.ipynb
[Paper Review]ConvLSTM 시계열 기계학습을 이용한 예측모델 – https://jiwon-lee-it.tistory.com/93
예제가 있는 ConvLSTM 및 ConvGRU 모듈의 Pytorch 구현 – wenyanet-https://www.wenyanet.com/opensource/ko/6121c73d069de31ce94857da.html
Multi-Step LSTM Time Series Forecasting Models for Power Usage – https://machinelearningmastery.com/how-to-develop-lstm-models-for-multi-step-time-series-forecasting-of-household-power-consumption/