Results 141 to 150 of about 208,635 (216)
Hybrid attention-based temporal convolutional bidirectional LSTM approach for wind speed interval prediction. [PDF]
Bommidi BS +3 more
europepmc +1 more source
Named Entity Recognition Menggunakan Metode Bidirectional Lstm-Crf Pada Teks Bahasa Indonesia
Named Entity Recognition (NER) atau pengenalan entitas bernama adalah salah satu bagian atau tugas dari natural language processing (nlp). Tujuan dari NER adalah untuk mengidentifikasi atau mengklasifikasi sebuah entitas misalnya nama orang, organisasi ...
Permana, Hadi
core
Through a PRISMA‐guided review of 42 studies, this work compares deep learning, ensemble machine learning, and statistical/econometric models for long‐term energy demand forecasting, showing that model choice should balance accuracy, interpretability, data availability, and policy relevance.
Nor Afiza Mohd Noor +4 more
wiley +1 more source
Splice-site identification for exon prediction using bidirectional LSTM-RNN approach. [PDF]
Singh N, Nath R, Singh DB.
europepmc +1 more source
A Critical Analysis of Optimization Algorithms for Cultural Heritage Conservation and Management
Methodological framework and decision‐support roadmap for optimization algorithms in cultural heritage conservation and management. ABSTRACT Heritage buildings symbolize cultural identity, architectural character, and historical epitome of communities.
Eslam Mohammed Abdelkader +6 more
wiley +1 more source
Spatial feature recognition and layout method based on improved CenterNet and LSTM frameworks
Existing spatial feature recognition and layout methods primarily identify spatial components manually, which is time-consuming and inefficient, and the constraint relationship between objects in space can be difficult to observe.
Yuxuan Gu +4 more
doaj +1 more source
Vehicle Destination Prediction Using Bidirectional LSTM with Attention Mechanism. [PDF]
Casabianca P +3 more
europepmc +1 more source
A Nadam‐optimized Bi‐LSTM framework integrates multi‐level student and institutional data to predict academic performance with 92.5% accuracy. The approach captures bidirectional temporal patterns and enables scalable, data‐driven early warning systems and targeted interventions in higher education. ABSTRACT Student performance prediction is a critical
Sudhindra B. Deshpande +5 more
wiley +1 more source
Time-Frequency Mask-Aware Bidirectional LSTM: A Deep Learning Approach for Underwater Acoustic Signal Separation. [PDF]
Chen J, Liu C, Xie J, An J, Huang N.
europepmc +1 more source
This paper reviews recent advances in hybrid deep learning for intelligent fault diagnosis of rotating machinery, focusing on GAN‐ and CNN‐based architectures and their specialized variants. Hybrid GAN‐CNN methods are categorized into three groups: (1) optimized original GANs with CNN variants, (2) improved GAN architectures integrated with CNNs, and ...
Temesgen Tadesse Feisa +7 more
wiley +1 more source

