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In this paper, we construct the financial risk early warning model based on BP neural network, make an empirical analysis of the data between January 2004 and October 2015, proves the reliability of the model prediction results through the training and test of the financial risk early warning model and finally put forward the following suggestions for preventing China's financial risks under the new...
Tax audit has vital influence on improving professional quality of tax team, impartial law enforcement and construction of a clean government. View of the complexity of performance evaluation of tax audit, this paper established the performance evaluation model of tax audit to select the various influential factors via gray-relation analysis. Based on artificial neural network, it built the performance...
On the basis of analyzing the significance of assessing production and operation ability in small and medium enterprise (shorter form SMB), the assessment-index system of production and operation ability for small and medium enterprise is built and assessment model is established using BP neural network. The conjunction weights of the neural network are continuously modified layer by layer from output...
Based on the analysis of driving forces of urban land expansion by Principal component analysis (PCA), this paper established a predicting model of urban built-up area for future by using socio-economical data. Being good at the performance of nonlinear approximation, artificial neural network (ANN), especially the back propagation algorithm (BP), is applied in the prediction of bulit-up land and...
The paper has analyzed the characters of TPL service provider selection based on online trading platform and constructed evaluation index system following the principle of real-time, simplification, uniformity and efficiency. Simultaneously, this paper has proposed intelligent decision-making method of the TPL service provider selection based on online trading platform and BP artificial neural network...
To get the quantified indexes of comprehensive capacity about project manager, based on the modal on artificial neural network theory, different influence factors about choice of project manager for building curtain wall construction were analyzed, identified, quantified and evaluated, then comprehensive capacity of the manager were analyzed. Such procedure provided a new method for choice of project...
The generalization ability of neural network is an important aspect affecting its application. Meanwhile, the selection of training samples has a great impact on this ability. In order to improve the completeness of training samples, a method of samples self-learning of BP neural network based on clustering is put forward in this paper. By using the method of clustering, new samples can be collected...
This paper proposes a composite method for short-term load forecasting, which is based on fuzzy clustering wavelet decomposition and BP neural network. Firstly, the similar-day's load is selected as the input load based on the fuzzy clustering method; secondly, the wavelet method is applied to decompose the similar-day load into the low frequency and high frequency components, from which the feature...
Three indicators (R, I30, P), and all four indicators (R, I30, P, I) of erosive rainfall in Jia Zhaichuan small watershed of Song county are chosen respectively as the input vector to predict sedimentation volume with the two neural network of RBF and BP, and fit with the actual values. The results testify the fitting and predicted effects of RBF neural network are all better than BP network, as well...
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...
The low-carbon economy has become the mainstream of social development, but the energy use will inevitably produce high pollution and high emissions of gas with the high speed economic growth of manufacturing companies. Here, this network is introduced into the BP Energy Consumption of manufacturing companies. By description of the BP algorithm characteristics and analysis of the factors influencing...
Flood disaster management is an important part of flood risk assessment. A regional flood disaster risk assessment index system is established in this paper. Then principal component analysis (PCA) method and BP neural network are combined, and a regional flood disaster risk assessment of PCA-BP neural network model is established. PCA-BP neural network model analyze the loss of flood disaster about...
Aiming at the shortages of the existing data-mining model for forecasting the industry security, a classification model based on rough sets and BP neural network (BPNN) is put forward in this paper. First, the theory of rough set is applied to pick up and reduce the index attributes. Then, the training samples are sent to the BPNN to train and learn. After that, the sorts of the coal industry security...
The network course evaluation indicator system are established in the paper. The large number of representative uniformly distributed samples are designed for training the nearest neighbor- clustering RBF neural network (RBFNN) and solving the problem of RBFNN model's poor generalization ability. The experiments show the result of nearest neighbor- clustering RBFNN evaluation is very close to the...
To the goal of multiple degree of freedom (M-DOF) prosthetic hand control by characterizing events in surface electromyograms (sEMG), a system of sEMG acquisition, detection and recognition is built. It can classify commonly used eighteen kinds of hand gestures with six channels. The dynamic cumulative sum (DCS) is applied for on-line detection. Energy changes are detected with this approach, corresponding...
Based on the experience of operations and support, the criticality class of spare parts (SPs) is usually uncertain and may result in excess or insufficient inventory. So it's an urgent issue to devise a way to evaluate the criticality class of SPs accurately. The investigation applied back-propagation network (BPN) to evaluate the criticality class (i, II, III, IV) of spare parts. By using group-discussing...
In this paper, six thermal-wet comfort objective evaluation indexes of 36 kinds of knitted fabrics such as air permeability rate, moisture transmission rate, wicking height, moisture regain rate, moisture diffusion rate and thermal resistance were tested and analyzed. And then the 36 kinds of knitted fabrics were made into the same style clothes. Four thermal-wet comfort subjective evaluation indexes...
Combined with the characteristics of enterprise logistics system, the evaluation index system of enterprise supply logistics system was established using systematic evaluation method. The BP neural network for appraising the performance of enterprise supply logistics system was built. Through the training and simulation of neural network, it is indicated that this evaluation method proves feasible...
Mechanism type selection is a critical problem often encountered in conceptual design stage of mechanical system. A BP neural network based approach to mechanism type selection is proposed, which capitalizes on the features of nonlinearity, self-organization, and fault tolerance of a neural network to implement classification and selection. By using appropriate data sets to train the neural network...
According to the complexity of financial system, the model of credit risk assessment based on PSO algorithm and BP neural network integrated is proposed, which in order to improve the accuracy and reliability of risk assessment. First the neural network model of a credit risk evaluation is created, and then PSO algorithm is introduced to optimize the weight and threshold of the neural network, at...
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