Results 91 to 100 of about 13,592 (226)

Environmental Control for Edible Fungi Cultivation Based on Temporal Information and Deep Learning

Food Bioengineering, EarlyView.
ABSTRACT Currently, there are still prevalent issues in greenhouse environmental regulation, such as response lag, low control accuracy, and difficulty in coping with sudden environmental disturbances. To achieve high‐precision and dynamic control of the edible fungi cultivation environment, this study proposes an edible fungi environmental control ...
Xiangyan Wang, Shuangcheng Huang, Qingbo Lu, Xinyi Guo   +3 more
wiley   +1 more source

Urban Traffic Volume Prediction using LSTM and Bi-LSTM: Performance Evaluation on the Metro Interstate Dataset

Ilkom Jurnal Ilmiah
Urban traffic forecasting underpins the mitigation of congestion, enhancement of road safety, and reduction of emissions in intelligent transportation systems.
Andri Pranolo, Shoffan Saifullah, Agung Bella Utama Putra, Rafał Dreżewski, Aji Prasetya Wibawa   +4 more
doaj   +1 more source

Precipitation Nowcasting: Leveraging bidirectional LSTM and 1D CNN

CoRR, 2018
Short-term rainfall forecasting, also known as precipitation nowcasting has become a potentially fundamental technology impacting significant real-world applications ranging from flight safety, rainstorm alerts to farm irrigation timings. Since weather forecasting involves identifying the underlying structure in a huge amount of data, deep-learning ...
Maitreya Patel, Anery Patel, Ranendu Ghosh   +2 more
openaire   +2 more sources

Triboelectric nanogenerators for vehicle intelligent cockpits

FlexMat, EarlyView.
Converting mechanical stimuli from drivers and vehicle motion into electrical signals, triboelectric nanogenerators provide promising interfaces toward passive, flexible, distributed and intelligent sensing for next‐generation automotive cockpits to support three core functional dimensions: driver state monitoring, vehicle state monitoring, and human ...
Haiqiu Tan, Shiquan Lü, Xiangwei Meng, Huiying Zhang, Wenxing Zhang, Dongxian Sun, Xiao Lu, Lei Wang, Haodong Zhang, William W. Yu   +9 more
wiley   +1 more source

Deep Learning-Based Language Identification in English-Hindi-Bengali Code-Mixed Social Media Corpora

Journal of Intelligent Systems, 2019
This article addresses language identification at the word level in Indian social media corpora taken from Facebook, Twitter and WhatsApp posts that exhibit code-mixing between English-Hindi, English-Bengali, as well as a blend of both language pairs ...
Jamatia Anupam, Das Amitava, Gambäck Björn   +2 more
doaj   +1 more source

Reliable Intelligent Diagnostics With Uncertainty Quantification for Mechanical System Condition Assessment

Quality and Reliability Engineering International, EarlyView.
ABSTRACT Health condition assessment of mechanical systems is essential to ensure their safe and reliable operation. Although AI‐driven diagnostic techniques have advanced significantly with the development of deep learning, the reliability of such techniques is often compromised due to the lack of uncertainty quantification (UQ)—particularly the ...
Guangjun Jiang, Haotian Ouyang, Zifei Xu
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

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

Comparative Analysis of LSTM and Bi-LSTM for Classifying Indonesian New Translation Bible Texts Using Word2Vec Embedding

CommIT Journal
The research aims to compare the classification accuracy of Long Short-Term Memory (LSTM) and Bidirectional LSTM (Bi-LSTM) architectures in classifying Indonesian New Translation Bible texts with Word2Vec embedding.
Marthen Sattu Sambo, Suryasatriya Trihandaru, Didit Budi Nugroho, Hanna Arini Parhusip   +3 more
doaj   +1 more source