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adv-alstm

Code for paper "Enhancing Stock Movement Prediction with Adversarial Training" IJCAI 2019

cnn-lstm-for-ghi-forecasting

eneryconsumptionforecast

use LSTM，Transformer ，RNN,Transformer-Lstm to predict electricity

expenseprediction_model

SARIMA model for Time Series Forecasting on Expenses

fdd-scheme-for-ahus-considering-undefined-faults

FDD Scheme is developed with Deep neural network, undefined faults are identified with Supervised Auto-encoders.

fdd-with-decision-tree

In this project, fault detection and diagnosis model with decision tree is developed based on ASHRAE RP 1312 data. Rules generated by decision tree can be verified with domain expertise.

informer2020

The GitHub repository for the paper "Informer" accepted by AAAI 2021.

itransformer

Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight), https://openreview.net/forum?id=JePfAI8fah

pvodataset

pv_predict_unet-lstm

code for "Intra-hour Photovoltaic Generation Forecasting based on Multi-source Data and Deep Learning Methods." IEEE Transactions on Sustainable Energy

stoch-predict-with-tranformer-lstm

stock predict with MLP,CNN,RNN,LSTM,Transformer and Transformer-LSTM

stock-price-forecasting-using-convolutional-neural-networks

This major project aims to develop and evaluate a novel CNN-LSTM-based model for forecasting stock prices. The proposed model leverages the strengths of both CNNs and LSTMs to effectively capture the underlying patterns and trends present in historical stock price data.

time-series-library

A Library for Advanced Deep Time Series Models.