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The improved algorithm of WNN based on BP was proposed in this paper. Theoretical analysis and simulation result show it avoids both the blindness of framework designs for BP neural networks and the problem of nonlinear optimizations, such as local optimization. So it can simplify the training of neural networks. It has better abilities in function learning and generalization. This algorithm was successfully...
Rice leaf diseases have occurred all over the world, including china. They have had a significant impact on rice quality and yield. Now, the control method rely mainly on artificial means.In this study, BP neural network classifiers were designed for classifying the healthy and diseased parts of rice leaves. This paper select rice brown spot as study object, the training and testing samples of the...
Energy consumption forecast is an essential component in making energy plan. In the light of the complexity and nonlinearity of energy consumption system, the gray forecast model and neural network model are respectively established by using the energy consumption historical data of certain province. Then their advantages and disadvantages are analyzed. Lastly, the method of optimal combination is...
The instability disaster prediction model of tailings dam had been established, based on system analysis of the factors that caused the instability disaster of tailings dam, by selecting 6 prediction index, medium unit weight, cohesion, internal friction angle, slope angle, slope height and pore pressure ratio and combining with using theory of the rough set and neural network. First the rough set...
It is important to detect defects in wood, when it reduce the performance. The data and signal processing technology providing researchers with more damage identification problem solution ideas and methods. This article explore the wavelet analysis and artificial neural network for the wood defects based on non-destructive testing, and build an artificial neural network model for wood non-destructive...
Supply chain is a complicated, open system, for the constant development, and fierce degree of market competition of the society increase day by day, the discrimination and management of risk of Supply chain are more essential. Kinds of risk factors of Supply chain are analyzed in the text, according to the influence degree of each risk factor, a method combined BP neural network and fuzzy evaluation...
On the basis of analyzing the significance of assessing operation capability in SMB, the Appraisal-index system of operation capability for SMB is built, and appraisal model is established using BP neural network. The conjunction weights of the neural network are continuously modified layer by layer from output layer to input layer in the process of neural network training to reduce the errors between...
In order to predict gas content of coal seam accurately in binchang mining, we use core data to build the BP neural network. We select the important controlling factors which impacted gas content of coal seam, coal bed thickness, ash and max vitrinite reflectance as the basic features of the BP neural network model, and establish the BP neural network prediction model between coal bed methane content...
Combining with genetic algorithm, the improved estimation of distribution algorithm (EDA) is provided. The crossover and mutation operations are added and the "elite" individuals are retained, which can keep the excellent evolution mode. The selection based on energy entropy is added, which can explore the solution space sufficiently and keep the population diversity. A neural network with...
Based on chaotic characteristic of high frequency ground-wave radar (HFGWR) sea clutter, a new adaptive artificial neural networks ensemble method for sea clutter predicting is presented in this paper. In phase space reconstructed, when one sea clutter sample is to be predicted, some artificial neural networks are choosed adaptively by evaluating their performance and error correlation in neighborhood...
Focusing on BPNN model application and GIS spatial analysis, Hangzhou construction land geology environment suitability evaluation is studied in this article. BPNN model set up, evaluation indices system set up, samples selection, data process, etc., are studied deeply based on BPNN and GIS based quantitative and spatial analysis. For Hangzhou case, factors including topography features, engineering...
The traditional fault diagnosis expert system is dependent on knowledge acquisition of the experts. Knowledge acquisition is recognized as the "bottleneck" problem of expert system. In addition, there are also some limitations of adaptive capacity, learning ability and real-time. And artificial neural network with good fault-tolerance and associative memory function, as well as very strong...
In order to realize safety prediction of workface stray current, it's important to confirm the characteristic indexes of workface stray current so as to insure the time margin and reliability of prediction. By analyzing the resistance distribution network of the system, the paper confirms the four parameters as follows to be the characteristic indexes of coalface stray current safety prediction: the...
In distributed virtual environment many methods of data distribution management (DDM) are presented to efficiently improve network traffic situation and save system resources, these technologies are based on virtual environment partition. The grid size of the partition affects the data distribution results. This paper aims to present a neural-network based study mechanism, which adjusts the grid size...
This paper presents a short-term load forecasting method based on wavelet neural network (WNN) and monkey-king genetic algorithm (MK). Parameters of WNN are mostly selected artificially or obtained through experiment time after time. A certain and effective method has not been found. Aiming at solving this problems, a method optimizing the WNN parameters with monkey-king genetic algorithm (MKWNN)...
Choosing the kernel and error penalty parameters for support vector machine (SVM) is very important for the performance of classifiers. An improved grid-search algorithm is proposed to choose the optimal parameters of SVM. The battlefield multi-target SVM classifier is designed using this algorithm. Also three classifiers including k-nearest neighborhood classifier, improved BP neural network classifier...
This paper proposes an Assembling Learning Approach (ALA) for multi classification concerned with weighted-voting label assignment strategy. This weighted-voting idea is reflected in two components of ALA: a Weighted SVMs method (WSVM) that identifies regular data label and a Locally Adaptive ANN (LAANN) that addresses the rejected case. Basic SVM of WSVM is equipped with confidence coefficient to...
This paper presents a new method to recognize machine-printed traditional Mongolian characters by using back-propagation (BP) neural networks. First, the set of traditional Mongolian characters is divided into five subsets according to each character's position (initial, medial or final) within a word and some steady structural features. Then, each subset is trained and recognized by using a BP neural...
One major problem in the management of the current large networks is the complexity and the enormous amount of operations required to satisfy user demands while using resources efficiently. In this study, we propose a network traffic forecasting strategy based on BP neural network (BP-NTF). First, we analyse the characteristics of network traffic and establish traffic forecasting methods based on...
This study proposes an algorithm integrated with a neural network method to simulating 3D cloth dynamics. The model built by an element finite method, is possibly improved and optimized by the neural network method. The finite element mesh generation has to be continuously controlled to meet the continuously changing geometric model in dynamic simulation. The neural network method is applied to dynamically...
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