Results 31 to 40 of about 911,793 (268)
Comparisons of different deep learning-based methods on fault diagnosis for geared system
International Journal of Distributed Sensor Networks, 2019 The running state of a geared transmission system affects the stability and reliability of the whole mechanical system. It will greatly reduce the maintenance cost of a mechanical system to identify the faulty state of the geared transmission system ...
Bing Han +3 more
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Deep Sequential Neural Network
, 2014 Neural Networks sequentially build high-level features through their successive layers. We propose here a new neural network model where each layer is associated with a set of candidate mappings. When an input is processed, at each layer, one mapping among these candidates is selected according to a sequential decision process.
Denoyer, Ludovic, Gallinari, Patrick
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Prediction of Shear Strength of Ultra High Performance Reinforced Concrete Deep Beams without Stirrups by Neural Network [PDF]
Eurasian Journal of Science and Engineering, 2017 : Shear strength of ultra high performance reinforced concrete deep beams without stirrups predicted by neural network models. The neural network model based on 233 beams from literatures considering different parameters such as span to depth ratio ...
Sinan Abdulkhaleq Yaseen +2 more
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Parallel orthogonal deep neural network
Neural Networks, 2021 Ensemble learning methods combine multiple models to improve performance by exploiting their diversity. The success of these approaches relies heavily on the dissimilarity of the base models forming the ensemble. This diversity can be achieved in many ways, with well-known examples including bagging and boosting.
Peyman Sheikholharam Mashhadi +2 more
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Intuitionistic Fuzzy Deep Neural Network
Mathematics, 2023 The concept of an intuitionistic fuzzy deep neural network (IFDNN) is introduced here as a demonstration of a combined use of artificial neural networks and intuitionistic fuzzy sets, aiming to benefit from the advantages of both methods.
Krassimir Atanassov +2 more
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Needle-based deep-neural-network camera [PDF]
Applied Optics, 2021 We experimentally demonstrate a camera whose primary optic is a cannula/needle ( d i a m e t e r = 0.22 m m and l e n g t h = 12.5 m m ) that acts as a ...
Ruipeng Guo, Soren Nelson, Rajesh Menon
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A deep learning-based method for predicting the low-cycle fatigue life of austenitic stainless steel
Materials Research Express, 2023 In modern engineering, predicting the fatigue life of materials is crucial for safety assessment. The relationship between fatigue life and its influencing factors is difficult to predict by traditional methods, and deep learning can achieve great power ...
Hongyan Duan +5 more
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Deep Petri nets of unsupervised and supervised learning
Measurement + Control, 2020 Artificial intelligence is one of the hottest research topics in computer science. In general, when it comes to the needs to perform deep learning, the most intuitive and unique implementation method is to use neural network.
Yi-Nan Lin +5 more
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Design of an Intelligent Educational Evaluation System Using Deep Learning
IEEE Access, 2023 Nowadays, online education has been a more general demand in context of COVID-19 epidemic. The intelligent educational evaluation systems assisted by intelligent techniques are in urgent demand.
Yan Pei, Genshu Lu
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Deep neural networks in psychiatry [PDF]
Molecular Psychiatry, 2019 Machine and deep learning methods, today's core of artificial intelligence, have been applied with increasing success and impact in many commercial and research settings. They are powerful tools for large scale data analysis, prediction and classification, especially in very data-rich environments ("big data"), and have started to find their way into ...
Daniel, Durstewitz +2 more
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