Hybrid models by integrating the traditional mathematical formulations and data driven methods are being developed in different parts of world. This paper discusses the methodology of development of an innovative hybrid mathematical-artificial neural network model. In mathematical model, the most important ...
An ANN model is so simple and natural that it can handle very complex real-life problems in a nonparallel and distributive way like a biological neural network. The mathematical description of ANN can be understood by the following equation: (1)Y(t)=F(∑i=1n(Xi(t)Wi(t)+c)) where Xi...
This study presents an artificial neural network (ANN) visible mathematical model for real-time multiphase FBHP prediction in wellbores. A total of 1001 normalized real-time field data points were first used in developing an ANN black-box model. The data points were randomly divided into three ...
aThe artificial neural network referred to as the neural network, is an imitation of biological neural network structure and function of the mathematical model and calculation model. The neural network provides a new solution for solving optimization problems. In the past few decades, the neural ...
aAn artificial neural network (ANN) is a mathematical system, which can model the ability of biological neural network by interconnecting many simple neurons. The back-propagation neural network (BPN) is the most prevalent in supervised learning models of the ANN. The procedure of the BPN repeated...
The research method uses in this paper is an artificial neural network, which was a mathematical model that simulates biological neural network for information processing (Zhang et al., 2021). It was developed based on M-P neuron model (McCulloch and Pitts, 1943). M-P neuron model was the...
Here we explore the possibility that a model of physical objects is created by a computational system that is equivalent to an artificial neural network. Since it is believed that human thought is created in the brain's neural networks the mystery disappears due to similarities between neural ...
identifyingmathematicalmodelofshipmovementusingartificialneuralnetwork 系统标签: 船舶辨识神经网络模型运动 第30卷第2期 2000年3月 东南大学学报 (自然科学版) JOURNALOFSOUTHEASTUNIVERSITY(Natura ScienceEditi n) V .30N .2 Mar 2000 基于人工神经网络的船舶运动数学模型的辨识 林莉万德钧李滋刚 (东南大学仪器科学与...
Basically, ANNs are the mathematical algorithms, generated by computers. ANNs learn from standard data and capture the knowledge contained in the data. Trained ANNs approach the functionality of small biological neural cluster in a very fundamental manner. They are the digitized model of biological ...
33、networks,Bayesian learning: the distribution of the neural network parameters is learnt Support vector learning: the minimal representative subset of the available data is used to calculate the synaptic weights of the neurons,04/09/2020,Artificial Neural Networks - I,49,Reinforcement Learning,Seque...