Results 111 to 120 of about 208,635 (216)

Weibull Variational Autoencoder for Remaining Useful Life Prediction

Quality and Reliability Engineering International, EarlyView.
ABSTRACT Remaining useful life (RUL) prediction is a critical technology for preventing unexpected failures and reducing maintenance costs in modern industrial systems. However, traditional model‐based approaches are limited by the need for explicit mathematical modeling of degradation mechanisms, while data‐driven methods often require large‐scale ...
JunWoo Yu, Yoojin Jang, Kwanghui Shin, Jinsoo Jeong, Yong Soo Kim   +4 more
wiley   +1 more source

Integrating multimodal data and machine learning for entrepreneurship research

Strategic Entrepreneurship Journal, EarlyView.
Abstract Research Summary Extant research in neuroscience suggests that human perception is multimodal in nature—we model the world integrating diverse data sources such as sound, images, taste, and smell. Working in a dynamic environment, entrepreneurs are expected to draw on multimodal inputs in their decision making.
Yash Raj Shrestha, Vivianna Fang He
wiley   +1 more source

Artificial intelligence empowers targeted protein degradation: Core technological innovations, multi‐scenario applications, and translational prospects

Smart Molecules, EarlyView.
AI is transforming TPD by improving the design, prediction, and optimization of degraders such as PROTACs, molecular glues, and LYTACs. This review summarizes key AI‐driven advances, highlights applications across drug discovery stages, and discusses remaining challenges and future directions for accelerating the development of therapies against ...
Shuanglin Qin, Rui Peng, Guangshuai Zhang, Si Yan, Jin Xiao, Zishu Liu, Ziyu Tan, Qingqing Xie, Shangjie Li, Wei Luo, Xiaohe Xiao   +10 more
wiley   +1 more source

A Spatio‐Temporal Dynamics Model for Indoor Environmental Forecasting

IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.
Accurate forecasting of indoor environmental conditions is essential for intelligent building operations and comfort‐oriented controls. However, reliable prediction remains challenging due to spatial heterogeneity across sensing locations, complex multi‐modal interactions, and nonstationary temporal dynamics.
Goro Terumichi, Jiarui Li, Tatsuji Kimura, Hiroaki Nishi   +3 more
wiley   +1 more source

Spatial-Temporal Analysis of Earthquakes in Indonesia with Deep Learning Models: Performance Evaluation of CNN, LSTM, and Hybrid CNN-GRU

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Indonesia, located along the Pacific Ring of Fire, experiences high seismic activity with over 6,000 earthquakes annually. Accurate earthquake prediction remains a major challenge because of the complexity of geological dynamics and limitations of ...
Susandri Susandri, Fajrizal Fajrizal, Feldiansyah Bakri Nasution   +2 more
doaj   +1 more source

Short‐Term Multi‐Horizon Line Loss Rate Forecasting of a Distribution Network Using Attention‐GCN‐LSTM

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Accurately predicting line loss rates is crucial for effective management in distribution networks, particularly for short‐term multihorizon forecasts ranging from 1 hour to 1 week. In this study, we propose attention‐GCN–LSTM, a novel method that integrates graph convolutional networks (GCN), long short‐term memory (LSTM) and a three‐level ...
Jie Liu, Yijia Cao, Yong Li, Yixiu Guo, Wei Deng   +4 more
wiley   +1 more source

An Integrated Framework with ADD-LSTM and DeepLabCut for Dolphin Behavior Classification

Journal of Marine Science and Engineering
Caring for dolphins is a delicate process that requires experienced caretakers to pay close attention to their behavioral characteristics. However, caretakers may sometimes lack experience or not be able to give their full attention, which can lead to ...
Shih-Pang Tseng, Shao-En Hsu, Jhing-Fa Wang, I-Fan Jen   +3 more
doaj   +1 more source

RES‐AD: An AutoML‐Driven Robust Ensemble Framework for Real‐Time Anomaly Detection and Energy Forecasting in Smart Grids

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Accurate load forecasting and reliable anomaly detection are critical for the stable operation of modern smart grids (SGs), which increasingly rely on cyber‐connected infrastructures. However, the integration of smart metres and two‐way communication exposes SGs to data integrity attacks that can manipulate consumption measurements, degrade ...
Murad Ali Khan, Naeem Iqbal, Syed Shehryar Ali Naqvi, Muhammad Faseeh, Do‐Hyeun Kim   +4 more
wiley   +1 more source

A Novel Single‐Encounter‐Emphasise‐Attention Neural Network for Predictive Maintenance in Urban Infrastructure

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT The Riyadh Metro represents a significant project in Saudi Arabia, designed to transform urban transportation and reduce traffic congestion within the city. With six metro lines and 85 stations, the network is expected to serve millions of passengers daily, necessitating innovative digitally driven maintenance approaches to ensure reliable ...
Tawfeeq Shawly, Ahmed A. Alsheikhy
wiley   +1 more source

Developing Predictive and Explainable Models for Cryptocurrency Delistings: A Case Study of Binance Exchange

Asia-Pacific Journal of Financial Studies, EarlyView.
Abstract This study develops an explainable machine learning model to predict cryptocurrency delistings using Binance data. It combines quantitative indicators (price, volume) with qualitative data from real‐time news and Reddit. Latent Dirichlet Allocation (LDA) is used to extract topic trends and community reactions, which are transformed into time ...
Sungju Yang, Hunyeong Kwon
wiley   +1 more source