Results 1 to 10 of about 24,203 (119)

Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification. [PDF]

Artif Intell Med, 2019
Banerjee I, Ling Y, Chen MC, Hasan SA, Langlotz CP, Moradzadeh N, Chapman B, Amrhein T, Mong D, Rubin DL, Farri O, Lungren MP.   +11 more
europepmc   +2 more sources

Energy Consumption Prediction of Office Buildings Based on CNN-RNN Combined Model

Shanghai Jiaotong Daxue xuebao, 2022
In order to accurately reflect the operation characteristics of office buildings, a convolutional neural network(CNN)-recurrent neural network(RNN)combined model for energy consumption prediction of office buildings is proposed by using the good feature ...
ZENG Guozhi, WEI Ziqing, YUE Bao, DING Yunxiao, ZHENG Chunyuan, ZHAI Xiaoqiang
doaj   +1 more source

A model for multi-attack classification to improve intrusion detection performance using deep learning approaches

Measurement: Sensors, 2023
This proposed model introduces novel deep learning methodologies. The objective here is to create a reliable intrusion detection mechanism to help identify malicious attacks.
Arun Kumar Silivery, Ram Mohan Rao Kovvur, Ramana Solleti, LK Suresh Kumar, Bhukya Madhu   +4 more
doaj   +1 more source

Triple-Stage Attention-Based Multiple Parallel Connection Hybrid Neural Network Model for Conditional Time Series Forecasting

IEEE Access, 2021
The attention-based SeriesNet (A-SeriesNet) combined augmented attention residual learning module-based convolutional neural network (augmented ARLM-CNN) subnetwork with hidden state attention module-based recurrent neural network (HSAM-RNN) subnetwork ...
Yepeng Cheng, Yasuhiko Morimoto
doaj   +1 more source

Landslide Risk Prediction Model Using an Attention-Based Temporal Convolutional Network Connected to a Recurrent Neural Network

IEEE Access, 2022
Landslide risk assessment is an important component of the landslide research field. For the problem of landslide assessment indicators, we utilize the TOPSIS-Entropy method to assess the risk situation of landslide occurrences, which is easy to obtain ...
Di Zhang, Jiacheng Yang, Fenglin Li, Shuai Han, Lei Qin, Qing Li   +5 more
doaj   +1 more source

Instant Gated Recurrent Neural Network Behavioral Model for Digital Predistortion of RF Power Amplifiers

IEEE Access, 2020
This article presents two novel neural network models based on recurrent neural network (RNN) for radio frequency power amplifiers (RF PAs): instant gated recurrent neural network (IGRNN) model and instant gated implict recurrent neural network (IGIRNN ...
Gang Li, Yikang Zhang, Hongmin Li, Wen Qiao, Falin Liu   +4 more
doaj   +1 more source

Landslide Susceptibility Mapping Based on Deep Learning Algorithms Using Information Value Analysis Optimization

Land, 2023
Selecting samples with non-landslide attributes significantly impacts the deep-learning modeling of landslide susceptibility mapping. This study presents a method of information value analysis in order to optimize the selection of negative samples used ...
Junjie Ji, Yongzhang Zhou, Qiuming Cheng, Shoujun Jiang, Shiting Liu   +4 more
doaj   +1 more source

A Deep Neural Network Model for Speaker Identification

Applied Sciences, 2021
Speaker identification is a classification task which aims to identify a subject from a given time-series sequential data. Since the speech signal is a continuous one-dimensional time series, most of the current research methods are based on ...
Feng Ye, Jun Yang
doaj   +1 more source

CDS risk premia forecasting with multi-featured deep RNNs: An application on BR[I]CS countries

Borsa Istanbul Review, 2023
Using state-of-the-art recurrent neural network architectures, this study attempts to predict credit default swap risk premia for BR[I]CS countries as accurately as possible.
Yasin Kutuk
doaj   +1 more source

Prediction of PCR amplification from primer and template sequences using recurrent neural network

Scientific Reports, 2021
We have developed a novel method to predict the success of PCR amplification for a specific primer set and DNA template based on the relationship between the primer sequence and the template.
Kotetsu Kayama, Miyuki Kanno, Naoto Chisaki, Misaki Tanaka, Reika Yao, Kiwamu Hanazono, Gerry Amor Camer, Daiji Endoh   +7 more
doaj   +1 more source