Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
The paper presents selected properties of the adaptive speed neural controller trained online for direct drive during mechanical changes of the object parameters. In the article was compared different algorithms for learning neural networks such as: backpropagation algorithm BP, momentum backpropagation MBP, Quickprop and RPROP. The authors proposed an effective method of supervision of learning neural...
Decision making tasks that involve processing of sequential stimuli with long delays pose a significant challenge to modeling using current methods in neural networks. However, decision making in animals involves storage of salient stimuli over long periods of time, robust maintenance of this information in the presence of noisy input, and subsequent recall and processing at the time of final decision...
This paper presents the use of artificial neural networks (ANN) to determine the solution one of the classic applications of differential equations, the mixing tank problem. An artificial neural network with feed-forward backpropagation is designed to predict the concentration of substance in the tank at any time t. The network has three layers of structure 5 - 10 - 2 and used the Levenberg-Marquadt...
Feed forward Multilayer Perceptron (MLP) Neural Networks are universal approximators. Weight adjustment of the connectionist model is crucial to architectures that model systems behavior. This paper developed a neural network for hydrological purposes. Two architectures were developed, investigated, and tested for forecasting rainfall in the rain-fed Sectors in Sudan. A monthly architecture and a...
The operation principles of proton exchange membrane (PEM) fuel cell system relate to thermodynamics, electrochemistry, hydrodynamics, mass transfer theory, which form a complex nonlinear system, and it is different to establish its mathematical model. This paper utilizes the approach and self-study ability of artificial neural network to build a model of nonlinear system, and adapts the modified...
In order to study the impact of drivers' distance cognition difference on traffic safety in dynamic environment of daytime and night-time, a real road tests was carried out by asking 19 drivers randomly selected to percept the distances of obstacles with different distances and velocities on daytime and nighttime. The values of cognition are obtained by statistical methods. The distance cognition...
Gas filow-volume controlled by many factors, the trend is complex, the accurate mathematical model to predict, in view of this situation, the paper attempts to grey dynamic model based on artificial neural network, organic combination of intelligent analysis method, structural gray neural network combination forecast model, based on Visual Basic 6.0, meanwhile, corresponding calculation program is...
In order to simulate a nonlinear system, A BP neural network can be used. First the question is analyzed, we can know what we use to input to the system, the dimensions of the input vectors will be the number of the input layer neurons, The number of the output layer neurons depends on the output parameters, The numbers of the hidden layer neurons depends both on the input layer number and the output...
With the economic development of the emerging market countries, bankruptcy and financial crisis occur more and more frequently in business, credit and savings institutions, and thus the demand for enterprise financial crisis prewarning is rapidly growing. The main purpose of this paper to build a business financial crisis prewarning model based on BP neural network to conduct empirical analysis of...
This paper discussed the framework of forecast model of BP neural network, represented a method for short-term passenger flow forecast of urban rail transit based on this model, which used the Matlab Neural Network Toolbox, took the influence of weather, date and other factors into account to forecast the passenger flow of Beijing urban rail transit. Through the experiment, we analyzed the results...
As a type of artificial intelligence model derived from the human brain system, the neural network has the function to simulate the human brain. The paper is intended to introduce the neural network into the measurements and calculations of space object orbits, thereby giving fuller play to its advantages in dealing with the non-linear issues, and thus making it possible to design the prediction algorithm...
Construction of intelligent transportation system is a necessary requirement for the development of transport, and LPR(License Plate Recognition) is an important part of construction of intelligent transportation system, Therefore, the research of license plate recognition method is of importance. The license plate character is recognized by building BP artificial neural network in this paper, it...
The temperature, the smoke density and the density of CO are selected as the main parameters of road tunnel fire detection, analyzing the environment and the characteristics of road tunnel fire. Based on BP neural network, the mathematical model is set up. Studying the algorithm of BP neural network, the model can identify road tunnel fire. The simulation result of road tunnel fire shows that the...
For the situation that urban emergency system needs to handle a large number of implicit and vague knowledge, this paper applies BP Neural Network to urban Emergency System, presents the system architecture of urban Emergency System which included neural network, and implements a specific application that determining the public emergency rank based on BP neural network. The method brings some new...
Based on the substance of university science research capability (USRC) and the highly self-organized, self-adapted and self-learned characteristics of back propagation (BP) neural network, the paper conducts a research on evaluation of USRC, in which an evaluation index system of USRC is constructed and a 15-7-1-typed BP neural network with three layers is presented to evaluate USRC, which provides...
This paper proposed a hybrid training algorithm by combining the Ant Colony System and BP algorithm. The Ant Colony System is used optimize the initial of the BP neural networks structure, connection between neurons and connection weights. The yield structure has trained using BP algorithms. This method can cope with trapping local minimum problem of the BP algorithm. The proposed method and the standard...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.