Results 21 to 30 of about 639,551 (228)

DEVELOPMENT OF AN ALGORITHM FOR OPTIMIZING NEURAL NETWORK TRAINING WHEN DETERMINING THE NUMBER OF NEURONS IN A HIDDEN LAYER IN ORDER TO INCREASE THE PROBABILITY OF RECOGNIZING IMAGES OF A GROUND TARGET

Надежность и качество сложных систем, 2022
Background. High accuracy of recognition of typical ground objects by optoelectronic tracking systems can be achieved by optimizing the parameters of an artificial neural network (INS) such as: the dimension and structure of the INS input signal ...
A.I. Godunov, S.V. Shishkov, S.T. Balanyan, F.Kh. Al' Saftli   +3 more
doaj   +1 more source

Multilayer neural networks with extensively many hidden units [PDF]

, 2001
The information processing abilities of a multilayer neural network with a number of hidden units scaling as the input dimension are studied using statistical mechanics methods. The mapping from the input layer to the hidden units is performed by general
A. Bethge, A. Engel, A. Engel, A. Priel, Andreas Engel, B. Schottky, C. Van den Broeck, E. Barkai, E. Barkai, E. Gardner, E. Gardner, G. Cybenko, G. Györgyi, G. J. Mitchison, H. Gutfreund, H. Schwarze, I. Kanter, Ido Kanter, M. Biehl, M. Mezard, M. Opper, Michal Rosen-Zvi, R. Monasson, R. Urbanczik, R. Urbanczik, T. M. Cover, W. Krauth   +26 more
core   +1 more source

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 
doaj   +1 more source

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
doaj   +1 more source

Stalagmite Layers Reveal Hidden Climate Stories

Eos, 2021
A global investigation discovers where annually laminated stalagmites are found, analyzes their growth properties, and explains how they can be best used in Earth science research.
Andy Baker, Gregoire Mariethoz, Laia Comas-Bru, Andreas Hartmann, Silvia Frisia, Andrea Borsato, Pauline Treble, Asfawossen Asrat   +7 more
openaire   +1 more source

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
doaj   +1 more source

Research on the Prediction Method of Centrifugal Pump Performance Based on a Double Hidden Layer BP Neural Network

Energies, 2019
With the aim of improving the shortcomings of the traditional single hidden layer back propagation (BP) neural network structure and learning algorithm, this paper proposes a centrifugal pump performance prediction method based on the combination of the ...
Wei Han, Lingbo Nan, Min Su, Yu Chen, Rennian Li, Xuejing Zhang   +5 more
doaj   +1 more source

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, Mao Jianlin, Xiang Fenghong, Liu Lian, Zhang Maoxing   +4 more
doaj   +1 more source

DDLSTM: Dual-Domain LSTM for Cross-Dataset Action Recognition [PDF]

, 2019
Domain alignment in convolutional networks aims to learn the degree of layer-specific feature alignment beneficial to the joint learning of source and target datasets.
Damen, Dima, Perrett, Toby
core   +4 more sources

GP-ELM-RNN: Garson-pruned extreme learning machine based replicator neural network for anomaly detection

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
doaj   +1 more source