Search Results - subject:"(Convolutional) neural network"

A deep convolutional neural network for vibration-based health-monitoring of rotating machinery

Ong, Pauline; Tan Yean Keong; Lai Kee Huong; Chee Kiong Sia - In: Decision analytics journal 7 (2023), pp. 1-9

neural network (1D-DCNN) to learn features directly from the vibrational signals and identify the gear fault under different … of the entire mechanical system is of imperative importance. This study proposes a one-dimensional deep convolutional …

Persistent link: https://www.econbiz.de/10014436400

An integrated convolutional neural network and sorting algorithm for image classification for efficient flood disaster management

Islam, Md Azharul; Rashid, Shawkh Ibne; Hossain, Niamat … - In: Decision analytics journal 7 (2023), pp. 1-13

system uses a combined convolutional neural network (CNN) and sorting algorithm. The Inception v3 and DenseNet CNN approach …

Persistent link: https://www.econbiz.de/10014436566

An optimized deep convolutional neural network for adaptive learning using feature fusion in multimodal data

Gupta, Swadha; Bhatia, Parteek; Tekchandani, Rajkumar - In: Decision analytics journal 8 (2023), pp. 1-15

The outbreak of COVID-19 has caused an unprecedented increase in the usage of e-Learning platforms. The closure of educational institutions globally has significantly impacted the traditional education system. Without physical interaction, engaging students in an e-Learning environment has...

Persistent link: https://www.econbiz.de/10014516967

Integrated digital image processing techniques and deep learning approaches for wheat stripe rust disease detection and grading

Mumtaz, Rafia; Maqsood, Muhammad Hassan; Ul Haq, Ihsan; … - In: Decision analytics journal 8 (2023), pp. 1-14

This study proposes integrated image processing and deep learning approaches for wheat rust disease detection and grading. Wheat stripe rust is one of the diseases affecting the crop in nearly all wheat-growing countries, where humidity and high temperatures characterize the growing season. The...

Persistent link: https://www.econbiz.de/10014517346

Employee attrition prediction with convolutional neural network and synthetic minority over-sampling technique

Duan, Lian; Paknejad, Javad; Kim, Hak - In: Journal of business analytics 8 (2025) 1, pp. 24-35

Persistent link: https://www.econbiz.de/10015188723

"Big picture" predicts destination attractiveness : the role of physical breadth and contextual breadth

Duan, Jingyi; Liang, Xuefeng; Liao, Jiangqun; … - In: Tourism management : research, policies, practice 108 (2025), pp. 1-18

Persistent link: https://www.econbiz.de/10015337433

A novel implementation of Siamese type neural networks in predicting rare fluctuations in financial time series

Basu, Treena; Menzer, Olaf; Ward, Joshua; SenGupta, Indranil - In: Risks 10 (2022) 2, pp. 1-16

window, and then uses the feature vector of a pre-trained convolutional neural network (CNN) to leverage pre-event images and …

Persistent link: https://www.econbiz.de/10013200929

A novel tracking system for the iron foundry field based on deep convolutional neural networks

Beck, Michael; Layh, Michael; Nebauer, Markus; Pinzer, … - In: Journal of Intelligent Manufacturing 33 (2022) 7, pp. 2119-2128

handheld scanner. With a deep convolutional neural network approach of object detection and classification, a stable image …

Persistent link: https://www.econbiz.de/10015165478

Machine learning for cryptocurrency market prediction and trading

Jaquart, Patrick; Köpke, Sven; Weinhardt, Christof - In: The Journal of finance and data science : JFDS 8 (2022), pp. 331-352

We employ and analyze various machine learning models for daily cryptocurrency market prediction and trading. We train the models to predict binary relative daily market movements of the 100 largest cryptocurrencies. Our results show that all employed models make statistically viable...

Persistent link: https://www.econbiz.de/10014433737

CVaR prediction model of the investment portfolio based on the convolutional neural network facilitates the risk management of the financial market

Wu, Zheng; Qiao, Yan; Huang, Shuai; Liu, HsienChen - In: Journal of global information management 30 (2022) 7, pp. 1-19

Persistent link: https://www.econbiz.de/10012800070