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

Intelligent machine fault diagnosis with effective denoising using EEMD-ICA- FuzzyEn and CNN

Zhou, Hanting; Chen, Wenhe; Shen, Changqing; Cheng, … - In: International journal of production research 61 (2023) 23, pp. 8252-8264

Persistent link: https://www.econbiz.de/10014452638

A hybrid convolutional neural network with long short-term memory for statistical arbitrage

Eggebrecht, P.; Lütkebohmert, Eva - In: Quantitative finance 23 (2023) 4, pp. 595-613

Persistent link: https://www.econbiz.de/10014304278

A hybrid learning method for distinguishing lung adenocarcinoma and squamous cell carcinoma

Swain, Anil Kumar; Swetapadma, Aleena; Rout, Jitendra Kumar - In: Data Technologies and Applications 58 (2023) 1, pp. 113-131

Purpose The objective of the proposed work is to identify the most commonly occurring non–small cell carcinoma types, such as adenocarcinoma and squamous cell carcinoma, within the human population. Another objective of the work is to reduce the false positive rate during the classification....

Persistent link: https://www.econbiz.de/10015342726

A convolutional neural network to identify the change point of a multistage process profile with cascade property

Atashgar, Karim; Boush, Mahnaz - In: International Journal of Quality & Reliability Management 41 (2023) 9, pp. 2232-2248

multilayer perceptron (MLP) and convolutional neural network (CNN) approaches are proposed for identifying the change point of … of a multistage process. (2) A convolutional neural network is modeled for identifying the change point of an out …

Persistent link: https://www.econbiz.de/10015347098

Parameter identification of PEMFC based on Convolutional neural network optimized by balanced deer hunting optimization algorithm

Yuan, Zhi; Wang, Weiqing; Wang, Haiyun; Ashourian, Mohsen - In: Energy Reports 6 (2020), pp. 1572-1580

algorithm (DHOA) is applied to the Convolutional neural network for the PEMFC parameters identification purpose. Indeed, the …

Persistent link: https://www.econbiz.de/10012652508

Parameter identification of PEMFC based on Convolutional neural network optimized by balanced deer hunting optimization algorithm

Yuan, Zhi; Wang, Weiqing; Wang, Haiyun; Ashourian, Mohsen - In: Energy reports 6 (2020), pp. 1572-1580

algorithm (DHOA) is applied to the Convolutional neural network for the PEMFC parameters identification purpose. Indeed, the …

Persistent link: https://www.econbiz.de/10012266173

Classification of ice crystal habits observed from airborne Cloud Particle Imager by deep transfer learning

Xiao, Haixia; Zhang, Feng; He, Qianshan; Liu, Pu; Yan, Fei - In: Earth and Space Science 6 (2019) 10, pp. 1877-1886

deep convolutional neural network based on the newly developed method of transfer learning. The results show that the TL …

Persistent link: https://www.econbiz.de/10012140657

End-to-end learning via a convolutional neural network for cancer cell line classification

Akogo, Darlington A.; Palmer, Xavier-Lewis - In: Journal of industry - university collaboration : JIUC 1 (2019) 1, pp. 17-23

explore and demonstrate the ability of a Convolutional Neural Network (CNN) to classify cells pictured via brightfield … Neural Network in distinguishing between two cancer lines. In their approach, they trained, validated and tested their 6 … identification. Design/methodology/approach The methodology involved a quantitative measure of the performance of a Convolutional …

Persistent link: https://www.econbiz.de/10012257640

Integrated explainable deep learning prediction of harmful algal blooms

Lee, Donghyun; Kim, Mingyu; Lee, Beomhui; Chae, Sangwon; … - In: Technological forecasting & social change : an … 185 (2022), pp. 1-11

Persistent link: https://www.econbiz.de/10014233744

Deep learning in the Chinese stock market : the role of technical indicators

Ma, Chenyao; Yan, Sheng - In: Finance research letters 49 (2022), pp. 1-9

Persistent link: https://www.econbiz.de/10013478616