ArticleScientific reports2024
Advanced hybrid LSTM-transformer architecture for real-time multi-task prediction in engineering systems.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
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- Research on deep well drilling rate of penetration prediction method based on TCN-transformer model.Scientific reports · 2026Article
- Deep learning-based battery health prediction for enhancing electric vehicle performance.Scientific reports · 2026Article
- A hybrid TimeGAN-xLSTM-Transformer framework for photovoltaic power forecasting under complex environmental conditions.Scientific reports · 2026Article
- Digital Twin Cognition: AI-Biomarker Integration in Biomimetic Neuropsychology.Biomimetics (Basel, Switzerland) · 2025Review
- A hybrid self attentive linearized phrase structured transformer based RNN for financial sentence analysis with sentence level explainability.Scientific reports · 2025Article
- A deep learning framework for virtual continuous glucose monitoring and glucose prediction based on life-log data.Scientific reports · 2025Article
- Evaluating Machine Learning-Based Soft Sensors for Effluent Quality Prediction in Wastewater Treatment Under Variable Weather Conditions.Sensors (Basel, Switzerland) · 2025Article
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- Application of Convolutional Neural Networks and Recurrent Neural Networks in Food Safety.Foods (Basel, Switzerland) · 2025Review
- Attention-based Transformer-LSTM architecture for early diagnosis and staging of early-stage Parkinson's disease using fNIRS data.Frontiers in aging neuroscience · 2025Article
- An enhanced BERT model with improved local feature extraction and long-range dependency capture in promoter prediction for hearing loss.PeerJ. Computer science · 2025Article
- Transformers in RNA structure prediction: A review.Computational and structural biotechnology journal · 2025Review
- A new strong convective precipitation forecasting method based on attention mechanism and spatio-temporal reasoning.Scientific reports · 2024Article
- Reconstruction of OFDM Signals Using a Dual Discriminator CGAN with BiLSTM and Transformer.Sensors (Basel, Switzerland) · 2024Article
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3 authors.
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Abstract
In the field of engineering systems-particularly in underground drilling and green stormwater management-real-time predictions are vital for enhancing operational performance, ensuring safety, and increasing efficiency. Addressing this niche, our study introduces a novel LSTM-transformer hybrid architecture, uniquely specialized for multi-task real-time predictions. Building on advancements in attention mechanisms and sequence modeling, our model integrates the core strengths of LSTM and Transformer architectures, offering a superior alternative to traditional predictive models. Further enriched with online learning, our architecture dynamically adapts to variable operational conditions and continuously incorporates new field data. Utilizing knowledge distillation techniques, we efficiently transfer insights from larger, pretrained networks, thereby achieving high predictive accuracy without sacrificing computational resources. Rigorous experiments on sector-specific engineering datasets validate the robustness and effectiveness of our approach. Notably, our model exhibits clear advantages over existing methods in terms of predictive accuracy, real-time adaptability, and computational efficiency. This work contributes a pioneering predictive framework for targeted engineering applications, offering actionable insights into.
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