Results 11 to 20 of about 262,770 (218)
The use of adversaries for optimal neural network training [PDF]
EPJ Web of Conferences, 2019 B-decay data from the Belle experiment at the KEKB collider have a substantial background from e+e- -h> qq¯ events. To suppress this we employ deep neural network algorithms. These provide improved signal from background discrimination. However, the deep
Hawthorne-Gonzalvez Anton, Sevior Martin
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A survey of efficient deep neural network
Dianxin kexue, 2020 Recently,deep neural network (DNN) has achieved great success in the field of AI such as computer vision and natural language processing.Thanks to a deeper and larger network structure,DNN’s performance is rapidly increasing.However,deeper and lager deep
Rui MIN
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Adam Optimization Algorithm for Wide and Deep Neural Network
Knowledge Engineering and Data Science, 2019 The objective of this research is to evaluate the effects of Adam when used together with a wide and deep neural network. The dataset used was a diagnostic breast cancer dataset taken from UCI Machine Learning.
Imran Khan Mohd Jais +2 more
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A greenhouse modeling and control using deep neural networks
Applied Artificial Intelligence, 2021 Deep learning approaches have attracted a lot of interest and competition in a variety of fields. The major goal is to design an effective deep learning process in automatic modeling and control field.
Latifa Belhaj Salah, Fathi Fourati
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Tunnel Geology Prediction Using a Neural Network Based on Instrumented Drilling Test
Applied Sciences, 2020 Reliable geology prediction is of great importance in ensuring the stability and safety of tunnels and other underground engineering projects. This paper presents basic neural network and deep neural network models using a genetic algorithm (GA) to ...
Yuwei Fang +4 more
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A research on underwater target recognition neural network for small samples
Xibei Gongye Daxue Xuebao, 2022 In the face of the challenges in the field of marine engineering applications in the new era, the goal of automation, high efficiency and accuracy can be achieved by using deep learning-based neural networks in hydroacoustic engineering.
WU Yanchen, WANG Yingmin
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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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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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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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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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