SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
GA-LSTM: Performance Optimization of LSTM driven Time Series Forecasting
11 references·0 citing·49 second hop
GA-LSTM: Performance Optimization of LSTM driven Time Series Forecasting (2024)GA-LSTM: Performance Optimization of LSTM…Bitcoin Price Prediction Using Sentiment Analysis and Empirical Mode Decomposition (2024)Bitcoin Price Prediction Usin…Time Series Forecasting with Statistical, Machine Learning, and Deep Learning Methods: Past, Present, and Future (2023)Time Series Forecasting with …Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)Generación de series de tiemp…Short-term stock market price trend prediction using a comprehensive deep learning system (2020)Short-term stock market price…A CNN-LSTM-Based Model to Forecast Stock Prices (2020)A CNN-LSTM-Based Model to For…The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)The Performance of LSTM and B…Stock Market Behaviour Prediction using Stacked LSTM Networks (2019)Stock Market Behaviour Predic…Genetic algorithms for hyperparameter optimization in predictive business process monitoring (2018)Genetic algorithms for hyperp…Data quality: “Garbage in – garbage out” (2018)Data quality: “Garbage in – g…Evolutionary computation algorithms for feature selection of EEG-based emotion recognition using mobile sensors (2017)Evolutionary computation algo…Computational Intelligence and Financial Markets: A Survey and Future Directions (2016)Computational Intelligence an…PORTFOLIO SELECTION* (1952)The Behavior of Stock-Market Prices (1965)Application of support vector machines in financial time series forecasting (2001)A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications (2010)A Multimodal Database for Affect Recognition and Implicit Tagging (2011)DEAP: A Database for Emotion Analysis ;Using Physiological Signals (2011)A Review on Automatic Facial Expression Recognition Systems Assisted by Multimodal Sensor Data (2019)A survey of machine learning techniques in physiology based mental stress detection systems (2019)Emotion recognition based on EEG feature maps through deep learning network (2021)Time prediction based on process mining (2010)Predicting process behaviour using deep learning (2017)Predictive Business Process Monitoring with LSTM Neural Networks (2017)From knowledge-driven to data-driven inter-case feature encoding in predictive process monitoring (2019)A Multi-View Deep Learning Approach for Predictive Business Process Monitoring (2021)Predictive process monitoring: concepts, challenges, and future research directions (2024)A Stochastic Approximation Method (1951)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)Deep learning with long short-term memory networks for financial market predictions (2017)Deep learning for financial applications : A survey (2020)Applications of deep learning in stock market prediction: Recent progress (2021)Financial time series forecasting with multi-modality graph neural network (2021)Time Series Analysis Forecasting and Control. (1971)Book Review: Time Series Analysis: Forecasting and Control (1977)Forecasting principles and practice (2018)Stock price prediction using deep learning and frequency decomposition (2020)Forecasting gold price using a novel hybrid model with ICEEMDAN and LSTM-CNN-CBAM (2022)Long-term traffic flow forecasting using a hybrid CNN-BiLSTM model (2023)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)A Hybrid Prediction Method for Stock Price Using LSTM and Ensemble EMD (2020)Analysis and forecasting of Time-Series data using S-ARIMA, CNN and LSTM (2021)Research on a hybrid prediction model for stock price based on long short-term memory and variational mode decomposition (2021)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Stock Price Prediction Using the ARIMA Model (2014)Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process (2021)Machine learning techniques and data for stock market forecasting: A literature review (2022)Forecasting Stock Market Prices Using Machine Learning and Deep Learning Models: A Systematic Review, Performance Analysis and Discussion of Implications (2023)Time series forecasting using a hybrid ARIMA and neural network model (2003)Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models (2018)The applications of artificial neural networks, support vector machines, and long–short term memory for stock market prediction (2021)Cryptocurrency trading: a comprehensive survey (2022)The Combination of Forecasts (1969)Forecasting with artificial neural networks: (1998)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Data Quality—Concepts and Problems (2022)Eleven quick tips for data cleaning and feature engineering (2022)Responsible AI in Marketing: AI Booing and AI Washing Cycle of AI Mistrust (2025)
this work references cited by second hop

References

  • 2019The Performance of LSTM and BiLSTM in Forecasting Time Series1,767 cited
  • 2021Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN)1,559 cited
  • 2016Computational Intelligence and Financial Markets: A Survey and Future Directions610 cited
  • 2020A CNN-LSTM-Based Model to Forecast Stock Prices595 cited
  • 2020Short-term stock market price trend prediction using a comprehensive deep learning system431 cited
  • 2017Evolutionary computation algorithms for feature selection of EEG-based emotion recognition using mobile sensors233 cited
  • 2018Data quality: “Garbage in – garbage out”200 cited
  • 2018Genetic algorithms for hyperparameter optimization in predictive business process monitoring111 cited
  • 2019Stock Market Behaviour Prediction using Stacked LSTM Networks61 cited
  • 2023Time Series Forecasting with Statistical, Machine Learning, and Deep Learning Methods: Past, Present, and Future27 cited
  • 2024Bitcoin Price Prediction Using Sentiment Analysis and Empirical Mode Decomposition26 cited

Cited by

No citing works inside the corpus for this window.

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work