Results 31 to 40 of about 18,004 (194)

Hybrid Decomposition ICEEMDAN-EWT Deep Learning Framework for Wind Speed Forecasting

Journal of Applied Informatics and Computing
Accurate wind speed forecasting plays a crucial role in supporting early warning systems for extreme wind events. However, the inherent non-linearity and non-stationarity of wind speed data pose significant challenges.
Dedi Arman Alif Hidayat, Muhamad Hilmil Muchtar Aditya Pradana, Ahmad Saikhu   +2 more
doaj   +1 more source

Classification of Final Project Titles Using Bidirectional Long Short Term Memory at the Faculty of Engineering Nurul Jadid University

Jurnal Sisfokom, 2023
Every year, the Faculty of Engineering at Nurul Jadid University forms a committee to manage the process of students' final projects from the title selection stage to the final examination process until graduation.
Faridatul Warda, Fathorazi Nur Fajri, Abu Tholib   +2 more
doaj   +1 more source

Massively Multiplexed Photonic Chip With Cross‐Channel Fusion For Harmonized Biosensing

Advanced Science, EarlyView.
We introduce a transformative sensing platform integrating photonic multiplexing with over 10 000 sensors and a deep‐learning framework that combines domain adaptation and cross‐channel fusion for harmonized operation across heterogeneous chips. The platform achieves 99.3% identification accuracy and relative prediction errors of 10−4$^{-4}$ for ...
Ivan Saetchnikov, Elina Tcherniavskaia, Andreas Ostendorf, Anton Saetchnikov   +3 more
wiley   +1 more source

Improving algorithms for predicting electric vehicle energy consumption to accurately estimate power reserve based on real terrain parameters and current meteorological factors

Transportation and Information Technologies in Russia
Background. Accurate forecasting of the energy consumption of electric vehicles is a critically important task for improving the efficiency of vehicle operation and reducing drivers' anxiety about power reserve.
Vladislav V. Matviyuk
doaj   +1 more source

A Multimodal Intelligent System for Human Digital Twin Simulation with Continuous Kinematic Data Tracking, Biometric Prognosis, and Cognitive State Feedback in Industrial Environments

Advanced Intelligent Discovery, EarlyView.
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury, Sebastian Gratz‐Kelly, Eric Wagner, Paul Motzki, Martina Lehser   +4 more
wiley   +1 more source

Atmospheric Temperature Prediction Based on a BiLSTM-Attention Model

, 2022
To address the problem that traditional models are not effective in predicting atmospheric temperature, this paper proposes an atmospheric temperature prediction model based on symmetric BiLSTM (bidirectional long short-term memory)-Attention model ...
Lili Pei, Yaohui Du, Ying Liu, Wei Li, Xueli Hao   +4 more
core   +1 more source

Deep attention based Proto-oncogene prediction and Oncogene transition possibility detection using moments and position based amino acid features

Научно-технический вестник информационных технологий, механики и оптики
The loss of the regulatory function of tumor suppression genes and mutations in Proto-oncogene are the common underlying mechanisms for uncontrolled tumor growth in the varied complex of disorders known as cancer.
M. Vijayalakshmi, M. Vallinayagi
doaj   +1 more source

A High‐Precision Dynamic Movement Recognition Algorithm Using Multimodal Biological Signals for Human–Machine Interaction

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article describes a multimodal fusion data acquisition and processing system about electromyography for dynamic movement recognition and bioelectrical impedance for key posture recognition. In addition, a new dynamic–static fusion algorithm strategy is designed.
Chenhao Cao, Gang Ma, Zelin Chen, Yiming Ouyang, Hu Jin, Shiwu Zhang   +5 more
wiley   +1 more source

SOH estimation for lithium-ion batteries based on SAO-BiLSTM-KAN

Zhejiang dianli
To improve the estimation accuracy of the state of health （SOH） for lithium-ion batteries， a novel estimation method based on snow ablation optimization， bidirectional long short-term memory network and Kolmogorov-Arnold networks （SAO-BiLSTM-KAN） is ...
ZHANG Binqiao, ZOU Lin, WAN Gang
doaj   +1 more source

Interpretable Short‐Term Electric Load Forecasting

Advanced Intelligent Systems, EarlyView.
A temporal fusion transformer is implemented to generate day‐ahead forecasts of the hourly electrical load of a departmentbuilding at an Italian university. A forecasting performance improvement of more than 25% compared with established benchmark models and a provision of inherent robust interpretability insights reveal the potential of this model for
Alessandro Nicola, Giorgia Ghione, Vincenzo Randazzo, Vincenzo Franzitta, Marco Badami, Eros Pasero, Giansalvo Cirrincione   +6 more
wiley   +1 more source