Chaotic time series prediction of nonlinear systems based on various neural network models
Y Sun, L Zhang, M Yao - Chaos, Solitons & Fractals, 2023 - Elsevier
This paper discusses the chaos prediction of nonlinear systems using various neural
networks based on the modified substructure data-driven modeling architecture. In the …
networks based on the modified substructure data-driven modeling architecture. In the …
Anomaly detection in videos using optical flow and convolutional autoencoder
Today, public areas, such as airports, hospitals, city centers are monitored by surveillance
systems. The widespread use of surveillance systems reduces security concerns while …
systems. The widespread use of surveillance systems reduces security concerns while …
Prediction of glioma grades using deep learning with wavelet radiomic features
G Çinarer, BG Emiroğlu, AH Yurttakal - Applied Sciences, 2020 - mdpi.com
Gliomas are the most common primary brain tumors. They are classified into 4 grades
(Grade I–II-III–IV) according to the guidelines of the World Health Organization (WHO). The …
(Grade I–II-III–IV) according to the guidelines of the World Health Organization (WHO). The …
Artificial intelligence and cognitive computing: Methods, technologies, systems, applications and policy making
Artificial intelligence (AI) and cognitive computing (CC) are subject of increased attention of
both academia and industry today [1] The understanding is that AI-and CC-enhanced …
both academia and industry today [1] The understanding is that AI-and CC-enhanced …
LSTM-based multi-task method for remaining useful life prediction under corrupted sensor data
K Zhang, R Liu - Machines, 2023 - mdpi.com
Data-driven remaining useful life (RUL) prediction plays a vital role in modern industries.
However, unpredictable corruption may occur in the collected sensor data due to various …
However, unpredictable corruption may occur in the collected sensor data due to various …
[HTML][HTML] Soil and Water Assessment Tool (SWAT)-informed deep learning for streamflow forecasting with remote sensing and in situ precipitation and discharge …
In order to anticipate residual errors and improve accuracy while reducing uncertainties, this
work integrates the long short-term memory (LSTM) with the Soil and Water Assessment …
work integrates the long short-term memory (LSTM) with the Soil and Water Assessment …
[Retracted] Innovative Application of Sensor Combined with Speech Recognition Technology in College English Education in the Context of Artificial Intelligence
J Guo - Journal of Sensors, 2023 - Wiley Online Library
English listening is an effective way to improve students' English expression ability and use
oral communication. However, from the current situation of English teaching, the current …
oral communication. However, from the current situation of English teaching, the current …
English Speech Emotion Classification Based on Multi-Objective Differential Evolution
Speech signals involve speakers' emotional states and language information, which is very
important for human–computer interaction that recognizes speakers' emotions. Feature …
important for human–computer interaction that recognizes speakers' emotions. Feature …
A hybrid spam detection framework for social networks
The widespread use of social networks has caused these platforms to become the target of
malicious people. Although social networks have their own spam detection systems, these …
malicious people. Although social networks have their own spam detection systems, these …
Singer identification model using data augmentation and enhanced feature conversion with hybrid feature vector and machine learning
S Hizlisoy, RS Arslan, E Çolakoğlu - … Journal on Audio, Speech, and Music …, 2024 - Springer
Analyzing songs is a problem that is being investigated to aid various operations on music
access platforms. At the beginning of these problems is the identification of the person who …
access platforms. At the beginning of these problems is the identification of the person who …