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To solve the problem of fault diagnosis for engine, due to the complexity of the equipments and the particularity of the operating environments, generally speaking, there is no one-to-one correspondence between the characteristic parameters and status, so, the methods of diagnosis are very complicated. A novel fault diagnosis method based on empirical mode decomposition (EMD) and wavelet packet BP...
Through analyzing non-linear, time-varying characteristics of the economic system and summing up the basic idea of nonlinear economic model, BP neural network is used to do non-linear economic modeling methodology and specific implementation steps, by which new ideas is put forward for the existence of model, and implementation of the circumstances in Matlab is given.
It is of great significance to study the index weight that plays an important role in the system of comprehensive evaluation-signs of multimedia courseware. To eliminate the randomicity in the process of overall evaluation, this paper analyses and constructs the evaluation model of index weight based on artificial neural network back propagation (BP) algorithm as well as the method of designing and...
Image reconstruction is a key to electrical capacitance tomography system. In this paper, basic principle and image construction problem of ECT system is analyzed, and BP neural network is adopted to solve image reconstruction. To accelerate reconstruction, BP neural network is divided into several parts, and each part will be sent to different slave nodes on which Globus platform is installed. After...
Support vector machines (SVM) has been used in load forecasting field. The noise and redundancy of sample data are important factors to the generalized performance of SVM. They can cause some disadvantages of slow convergence speed and low forecasting accuracy. A SVM forecasting method for short-term load forecasting based on rough sets (RS-SVM) is developed in this paper, using rough sets algorithm...
The Algorithm UCT, proposed by Kocsys et al, which apply multi-armed bandit problem into the tree-structured search space, achieves some remarkable success in some challenging fields. For UCT algorithm, Monte-Carlo simulations are performed with the guidance of UCB1 formula, which are averaged to evaluate a specified action. We observe that, as more simulations are performed, later ones usually lead...
According to the retrieval algorithm of adjusting automatic the weight of multi-features, and which the algorithm exist some deficiency, like that have not the study mechanism and so on. The paper analyzed and studied in the BP neural network in the learning process, and has realized the image retrieval method based on the BP neural network relevance feedback technology. The experiment proved that...
Analysis and control for power quality by neural network is a new research field in electrical power system. Rapid and reliable extract the harmonic components determine the overall performance of Active Power Filter (APF). This paper presents a new three-layer feedforward neural network based on error back-propagation algorithm that the training sample without time delay, which can detecting harmonics...
An artificial neural network (ANN) model is established to recognize the drilled formations' lithologies while drilling. The styles of output and input of ANN are designed. The nerve cells in input layer are weight of bit (WOB), speed of rotary (SOR) and rate of penetration (ROP). The number of nerve cells in output layer is designed to be three. Software system for recognizing the formation lithologies...
Through the evaluation of the 31Phosphorus Magnetic Resonance Spectroscopy (31P-MRS), we can distinguish three types of diagnosis: hepatocellular carcinoma, normal and cirrhosis. 71 samples of 31P-MRS data are selected including hepatocellular carcinoma, normal and cirrhosis tissue. Back-propagation neural network (BP) and Radial Basis Function Neural Network (RBF) are applied to analyze 31P-MRS data,...
The paper combined the advantage of particle swarm optimization algorithm (PSO), the global optimizing ability of Hopfield Neural Network, and the teacher supervising features of BP neural network to construct a new equipment fault diagnosis method with higher diagnosis precision, compared with the traditional single BP neural network.
Based on the DE-BP (Back Propagation-Differential Evolution) neural network, the predicting model of concrete carbonization depth is presented. The precision of the model is checked using the monitoring data. The comparisons between the predicted results of the three models (BP model, GA-BP model and DE-BP model) and the monitoring data show that the precision of the present algorithm is higher with...
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