Algorithm of artificial neural network architecture and training set size configuration within approximation of dynamic object behavior [PDF]
Компьютерные исследования и моделирование, 2015 The article presents an approach to configuration of an artificial neural network architecture and a training set size. Configuration is based on parameter minimization with constraints specifying neural network model quality criteria.
Aleksandr Georgievich Shumixin +1 more
doaj +1 more source
METODE KOMPARASI ARTIFICIAL NEURAL NETWORK PADA PREDIKSI CURAH HUJAN - LITERATURE REVIEW
Jurnal Tekno Insentif, 2020 Abstrak - Penelitian untuk mencari model prediksi curah hujan yang akurat di berbagai bidang sudah banyak dilakukan, maka dilakukan di-review kembali guna membantu proses penyaliran dalam perusahaan tambang.
Herlina Jayadianti +3 more
doaj +1 more source
A geographically weighted artificial neural network
International Journal of Geographical Information Science, 2021 While recent developments have extended geographically weighted regression (GWR) in many directions, it is usually assumed that the relationships between the dependent and the independent variables are linear.
Julian Hagenauer, M. Helbich
semanticscholar +1 more source
Journal of Innovation Information Technology and Application, 2021 The number of Chronic Kidney Disease patient increased year by year while it doesn’t following by sufficient human resources and infrastructure needs the information of Chronic Kidney Disease patient prediction.
Sheren Afryan Tyastama +2 more
doaj +1 more source
Advances in Civil Engineering, 2022 Wind flow on a bluff body is a complex and nonlinear phenomenon that has been mainly studied experimentally or analytically. Several mathematical methods have been developed to predict the wind-induced pressure distribution on bluff bodies; however, most
Josué U. Rodríguez-Alcántara +2 more
doaj +1 more source
Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science [PDF]
Nature Communications, 2017 Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods. Taking inspiration from the network properties of biological neural networks (e.g.
D. Mocanu +5 more
semanticscholar +1 more source
A Review of the Artificial Neural Network Models for Water Quality Prediction
Applied Sciences, 2020 Water quality prediction plays an important role in environmental monitoring, ecosystem sustainability, and aquaculture. Traditional prediction methods cannot capture the nonlinear and non-stationarity of water quality well.
Yingyi Chen +4 more
semanticscholar +1 more source
Pricing American Put Option using RBF-NN: New Simulation of Black-Scholes
Moroccan Journal of Pure and Applied Analysis, 2022 The present work proposes an Artificial Neural Network framework for calculating the price and delta hedging of American put option. We consider a sequence of Radial Basis function Neural Network, where each network learns the difference of the price ...
Zaineb El Kharrazi +2 more
doaj +1 more source
Designing a fruit identification algorithm in orchard conditions to develop robots using video processing and majority voting based on hybrid artificial neural network [PDF]
, 2020 The first step in identifying fruits on trees is to develop garden robots for different purposes such as fruit harvesting and spatial specific spraying.
Kalantari, Davood +3 more
core +1 more source
Study on factor-state artificial neural network model for water quality prediction
浙江大学学报. 农业与生命科学版, 2000 Research on factor neural network theory led to factor-state BP artificial neural network. Combination of informative diffusion with falling shadow technique forms information diffusion falling shadow technique together with factor BP artificial neural ...
GUO Zong-lou, SHEN Wei
doaj +1 more source