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Improving stock market predictions: an equity forecasting scanner using long short-term memory method with dynamic indicators for Malaysia stock market
Stock market predictions are a challenging problem due to the dynamic and complex nature
of financial data. This study proposes an approach that integrates the domain knowledge of …
of financial data. This study proposes an approach that integrates the domain knowledge of …
Data enrichment as a method of data preprocessing to enhance short-term wind power forecasting
Y Zhou, L Ma, W Ni, C Yu - Energies, 2023 - mdpi.com
Wind power forecasting involves data preprocessing and modeling. In pursuit of better
forecasting performance, most previous studies focused on creating various wind power …
forecasting performance, most previous studies focused on creating various wind power …
Prediction of US 30‐years‐treasury‐bonds movement and trading entry point using the robust 1DCNN‐BiLSTM‐XGBoost algorithm
A El Zaar, N Benaya, T Bakir, A Mansouri… - Expert …, 2024 - Wiley Online Library
This article presents a novel algorithm that accurately predicts market trends and identifies
trading entry points for US 30‐year Treasury bonds. The proposed method employs a hybrid …
trading entry points for US 30‐year Treasury bonds. The proposed method employs a hybrid …
An intelligent chatbot for evaluating the emotional colouring of a message and responding accordingly
VR Kobchenko, VM Shymkovysh… - PROBLEMS IN …, 2024 - pp.isofts.kiev.ua
A recurrent neural network model, a database designed for neural network training, and a
software tool for interacting with a bot have all been created. A large dataset (50 thousand …
software tool for interacting with a bot have all been created. A large dataset (50 thousand …
Prediction and History Matching of Observed Production Rate and Bottomhole Pressure Data Sets From in Situ Cross-linked Polymer Gel Conformance Treatments …
The objective of this study is to develop a computationally efficient methodology for the
prediction of oil rate, water rate, and injection bottomhole pressure (BHP), and history …
prediction of oil rate, water rate, and injection bottomhole pressure (BHP), and history …
[ספר][B] Computation of Artificial Intelligence and Machine Learning: First International Conference, ICCAIML 2024, Jaipur, India, January 18–19, 2024, Proceedings …
AK Bairwa - 2025 - books.google.com
The two-volume set, CCIS 2184-2185, constitutes the refereed proceedings of the First
International Conference on Computation of Artificial Intelligence and Machine Learning …
International Conference on Computation of Artificial Intelligence and Machine Learning …
[HTML][HTML] A Novel Hypersonic Target Trajectory Estimation Method Based on Long Short-Term Memory and a Multi-Head Attention Mechanism
Y Xu, Q Pan, Z Wang, B Hu - Entropy, 2024 - pmc.ncbi.nlm.nih.gov
To address the complex maneuvering characteristics of hypersonic targets in adjacent
space, this paper proposes an LSTM trajectory estimation method combined with the …
space, this paper proposes an LSTM trajectory estimation method combined with the …
[HTML][HTML] Enhancing Geomagnetic Disturbance Predictions with Neural Networks: A Case Study on K-Index Classification
A Altaibek, B Zhumabayev, A Sarsembayeva, M Nurtas… - Atmosphere, 2025 - mdpi.com
To explore the application of neural networks for estimating geomagnetic field disturbances,
this study pays particular attention to K-index classification. The primary goal is to develop a …
this study pays particular attention to K-index classification. The primary goal is to develop a …
Towards a Data-Driven Predictive Framework: A Comparison of Artificial Neural
R Benabbou - … Research Trends in Sustainable Solutions, Data …, 2025 - books.google.com
There's a pressing need to democratise DL algorithms while leveraging their performance.
This chapter proposes a customisable and efficient Automated Machine Learning (AutoML) …
This chapter proposes a customisable and efficient Automated Machine Learning (AutoML) …
A Contribution to Time Series Analysis and Forecasting Using Deep Learning Approaches
A El Zaar, A Mansouri, N Benaya… - 2024 International …, 2024 - ieeexplore.ieee.org
In the dynamic realm of time series analysis and forecasting, the pursuit of more precise and
efficient models persists as a fundamental objective. This research contributes by presenting …
efficient models persists as a fundamental objective. This research contributes by presenting …