The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Intelligent techniques (AI) have been successfully used in machines for fault diagnosis. In this paper a diagnostics approach based on discrete wavelet transform (DWT) and Neural network (NN) for stator winding inter-turn and open phase faults is presented. Simulink/Matlab is used to simulate a phase variable model of the BLDC motor with trapezoidal back - electric motive force (B-emf) under both...
Fuel cells are electrochemically complex, nonlinear, and dynamic energy conversion systems. Due to the dynamic characteristics of the fuel cell electrical performance models are used for system evaluation. In this study, Artificial Neural Network (ANN) technique is used as the modeling tool for internal structures of the fuel cells complex electrochemical reactions. The proton exchange membrane fuel...
Base on the situation analysis of copper matte smelting in P-S converter in the slag stage, this paper use modern BP neural network algorithm to realize the intelligent prediction of optimal flux addition through C programming. The module which is proved by the neural network toolbox of MATLAB can meet the demand of practical application. And the algorithm training time is greatly shortened in engineering...
In this paper, the global asymptotic stability is investigated for a class of stochastic neural networks with time-varying delay and generalized activation functions. By constructing appropriate Lyapunov-Krasovskii functional, and employing the free-weighting matrix method and stochastic analysis technique, a delay-dependent criterion for checking the global asymptotic stability of the addressed neural...
Genetic algorithm (GA) is applied to select main affecting factors of coal and gas outburst to solve the over-fitting problem of BP neural network (NN) in predicting coal and gas outburst, and a modified BP NN predictor is established, which input variables are the factors selected. In our GA, chromosome is a binary encoding which each gene corresponds to a variable, penalty function is introduced...
Vibration faults frequently occurring to the feed water pump in large-scale power plants are diagnosed by the integrated neural network based on MATLAB. The integrated neural network for fault diagnosis is established from individual neural network and on the basis of information fusion. The strategies and principles for the realization and formation of integrated neural network are analyzed and a...
Depression is a common but ominous psychological disorder that threatens one's quality of life. The screening and grading of depression is still a manual process and grades are often determined in ranges, e.g., "mild to moderate' and "moderate to severe' instead of making them more specific as "mild', "moderate', and "severe'. Such grading is confusing and affects the management...
Solar energy is a green energy which is not only perennial but also accessible to every strata of the world. An easy way to convert solar energy into electric energy is to use Solar Photovoltaic (SPV) system. Solar panel is a power source having nonlinear internal resistance. As the intensity of light falling on the panel varies, its voltage as well as its internal resistance varies. To extract maximum...
This paper proposes a new algorithm for localizing phase to ground faults in an electric power distribution system. Fault-originated traveling waves propagate along the distribution paths in both directions away from the fault point and are reflected at line terminations, junctions between feeders, laterals, and the fault location. Depending on the paths which traveling waves reciprocate through,...
This paper deals with analysis of power signals using complex wavelet transform. In the first step power signals containing sag, swell, harmonic, sag-harmonic, swell harmonic, transient and spike were generated using Matlab. Various features like energy, kurtosis, entropy, skewness etc. were extracted using `db4' and complex wavelet decomposition up to 11 levels. Next, an extensive database of these...
This paper investigates the use of neural networks to provide a challenging environment to motivate students of mathematics in further investigation of mathematical concepts. The research focuses on areas of shape, but similar methods could be used for a variety of mathematical topics. The paper presents a game in which a back-propagation neural network is trained by the player to compare areas of...
Based on the artificial neural networks and grey correlation analyze, this paper presents a model forecasting the infection rate of computer viruses according to the number of vulnerabilities, the percentage of viruses infecting via web browsing and downloading and the percentage of viruses infecting via portable storage media. The prediction is realized precisely by MATLAB. The three factors are...
Evaluating road safety is essential in identifying the potential road safety hazard which could result in casualties and property losses. in this paper, a BP neural network was built by using neural network toolkit in "Matlab", Two similar roadways are used in calibrating and validating the network. The high level of predictability provided that the application of BP neural network model...
According to the Characteristics of complex object system, a comprehensive evaluation model for complex object system is established based on fuzzy theory and artificial neural network. To realize the intelligence and the visualization of the evaluation process, an intelligent comprehensive evaluation software system with the help of Visual Basic, database technique and MATLAB toolbox is designed...
Spiking Neural Networks are the last generation of neural models. Because the model is recent, very few dedicated simulation frameworks exist. This paper proposes a simulation framework developed in MATLAB that can be useful at: designing the network, uploading input stimuli, simulating the network, processing and displaying the results. The framework can be run on a network of computers by exploiting...
The drilling of hard-to-cut high manganese steel materials is a difficulty in the field of machining. Research method for drilling temperature which has been commonly used is experimental method. The method has long-time and the high-cost drawbacks. Adopting error back neural network technology and using Matlab and C language programming method, in this paper neural network prediction model of drilling...
This paper presents an efficient wavelet and neural network (WNN) based algorithm for fault classification in single circuit transmission line. The first level discrete wavelet transform is applied to decompose the post fault current signals of the transmission line into a series of coefficient components (approximation and detail). The values of the approximation coefficients obtained can accurately...
With financial globalization, the rapid development of financial derivatives and the complexity of banks management, operational risk measurement and management in commercial bank management is becoming increasingly important. How to effectively predict, control and prevent operational risk in commercial banks have become an important issue. Using BP neural network model to predict the risk has its...
A pulmonary nodule is the most common sign of lung cancer. The proposed system efficiently predicts lung tumor from Computed Tomography (CT) images through image processing techniques coupled with neural network classification as either benign or malignant. The lung CT image is denoised using non-linear total variation algorithm to remove random noise prevalent in CT images. Optimal thresholding is...
The appliance of ERP System is a project with high risk and high investment, and there are various risks in the whole process of implementation. Firstly, this paper proposed and analyzed eight types of risks of ERP system implementation, namely, implementation purpose, need analysis, process reorganization, software selection, basic data, implementation organization, external environment and system...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.