Results 11 to 20 of about 115,779 (267)
Hidden layers of human small RNAs [PDF]
BMC Genomics, 2008 Abstract Background Small RNA attracts increasing interest based on the discovery of RNA silencing and the rapid progress of our understanding of these phenomena. Although recent studies suggest the possible existence of yet undiscovered types of small RNAs in higher organisms, many studies to ...
Kawaji, Hideya +11 more
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Acta Scientiarum: Technology, 2016 Samples of automotive ethanol, marketed in the northern and eastern regions of the state of Paraná, Brazil, underwent physical and chemical tests. Rates were assessed by Multilayer Perceptron (MLP) neural network for classification. For network training,
Érica Signori Romagnoli +5 more
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Radial Basis Function Neural Network Model Based on Lasso Sparse Learning [PDF]
Jisuanji gongcheng, 2019 The traditional Radial Basis Function(RBF) neural network model uses all hidden layer nodes to construct the model.In this case,the generalization performance of traditional RBF neural network model is degraded because of the lackness of the effective ...
CUI Chen,DENG Zhaohong,WANG Shitong
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IEEE Access, 2021 In order to overcome the extremely time-consuming drawback of deep learning (DL), broad learning system (BLS) was proposed as an alternative method. This model is simple, fast, and easy to update.
Weitong Ding +3 more
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Peningkatan Deep Neural Network pada Kasus Prediksi Diabetes Menggunakan PSO
Techno.Com, 2023 Diabetes adalah ancaman utama bagi kesehatan penduduk dunia yang saat ini merupakan penyebab utama kematian pada penduduk dunia yang berusia kurang dari 60 tahun. Dengan menggunakan Machine Learning diharapkan mampu memprediksi diabetes.
Rusmal Firmansyah, Guruh Fajar Shidik
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Performance Analysis of Automatic Hidden Ligthpaths in Multi-Layer Networks
Photonics, 2023 The problem of resource provisioning in multi-layer networks is an important issue. We discuss and analyze resource provisioning in terms of the visibility of optical resources for the virtual layer in a network.
Edyta Biernacka, Jerzy Domżał
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Multiple parallel hidden layers autoencoder for denoising ECG signal
Current Directions in Biomedical Engineering, 2022 Deep learning with multiple hidden layers denoising autoencoders (MHL-DAE) is commonly used to denoise images and signals through dimension reduction. Here, we explore the potential of multiple parallel hidden layers denoising autoencoder (MPHL-DAE) to ...
Samann Fars, Schanze Thomas
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Neural network approximation: Three hidden layers are enough [PDF]
Neural Networks, 2021 A three-hidden-layer neural network with super approximation power is introduced. This network is built with the floor function ($\lfloor x\rfloor$), the exponential function ($2^x$), the step function ($1_{x\geq 0}$), or their compositions as the activation function in each neuron and hence we call such networks as Floor-Exponential-Step (FLES ...
Zuowei Shen, Haizhao Yang, Shijun Zhang
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Fault Diagnosis of Power System Based on Improved Genetic Optimized BP-NN
MATEC Web of Conferences, 2015 BP neural network (Back-Propagation Neural Network, BP-NN) is one of the most widely neural network models and is applied to fault diagnosis of power system currently.
Yuan Pu +4 more
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Journal of King Saud University: Computer and Information Sciences, 2022 Replicator Neural Network (RNN) is a popular algorithm for anomaly detection, but finding optimal number of hidden layers and then finding optimal number of neurons in each hidden layer is quite a challenging and time-consuming task.
Adeel Shiraz Hashmi, Tanvir Ahmad
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