Jan 23, 2024 · Dive into a comprehensive guide of long-term time series forecasting methods. Gain valuable insights that empower you to predict future trends.

Jul 14, 2024 · Our findings suggest that refined recurrent architectures can offer competitive alternatives to transformer-based models in LTSF tasks, po-tentially redefining ...

Sep 17, 2023 · The realm of long-term time series forecasting is fraught with challenges. It's an essential endeavor across numerous industries, from predicting stock prices ...

Jan 19, 2024 · We design a STL-2DTCDN model for long-term multivariate time series forecasting in this paper. STL-2DTCDN utilizes STL to decompose the original time sequence ...

Dec 11, 2023 · Abstract:Long-term time series forecasting (LTSF) aims to predict future values of a time series given the past values. The current state-of-the-art (SOTA) ...

Jul 16, 2024 · Economic/financial data tends to have straightforward seasonality with complex trends, so deep learning tends to do quite poorly. I do agree with this paper - ...

Nov 21, 2023 · In this section, the fuzzy inference-based LSTM (FLSTM) for time series forecasting is proposed. The proposed method incorporates the fuzzy prediction fusion, ...

Oct 6, 2023 · [D] What's the SOTA model in Time Series Long term forecasting? Discussion. I read https://arxiv.org/abs/2205.13504 which compare different transformer models.

Oct 19, 2023 · In this work, we provide a Multivariate Time Series Forecasting model that emphasizes Relationships between and within sequences (MTSFR). Use the BERT model to ...

Aug 17, 2023 · Long-term time-series forecasting (LTTF) has become a pressing demand in many applications, such as wind power supply planning. Transformer models have been ...