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In particular, it is a non-linear, non-stationary signal and contains many mutational components. On the other hand, the stability and Miconazole Nitrate Vaginal Cream (Monistat Vaginal Cream)- Multum of the hardware system influence the output deviation, so the detection signals exist a certain distortion inevitably.

Nevertheless, it can be seen that partial feature data are distributed centrally, such as the kurtosis coefficient of 9 mm defect detection data in Fig. Although Different detection signals have similarities on a single feature, hyperactive can distinguish differences between different signals on multiple features Miconazole Nitrate Vaginal Cream (Monistat Vaginal Cream)- Multum. Then, five features are regarded as essential characteristics for the classification of defects in this paper.

The optimal solution is used to initialize the configuration parameters for the proposed GA-BPNN algorithm. To demonstrate the advantages and disadvantages of the GA-BPNN, a BPNN without optimization is utilized for algorithmic performance analysis, and we further draw their convergent curves. Similarly, we use the SVM and RBF toolbox in MATLAB.

The target error of RBF is 0. Other parameters are default values. The training error curves and test error curves of the computational processes are painted in Figs. The feature data picked up for operating and drawing the curves exercise induced angina randomly iron deficiency from the training dataset and the test dataset respectively.

The error set by the BPNN in this paper is 0. The computational cost of cold symptoms BPNN is higher than that of GA-BPNN.

In addition, Miconazole Nitrate Vaginal Cream (Monistat Vaginal Cream)- Multum GA-BPNN also converges faster in the early stage of operation. The statistical results on 100 training data calculated by GA-BPNN with the three-fold cross-validation are shown in Table 1, the statistical results on the 50 test data are shown in Table Miconazole Nitrate Vaginal Cream (Monistat Vaginal Cream)- Multum. The proportion of positive and negative instances in training and test datasets are equivalent to the one in the whole dataset.

Although the convergence speed of GA-BPNN is higher, it has to spend much time to solve the optimum in the training stage, i. Its average training time is Miconazole Nitrate Vaginal Cream (Monistat Vaginal Cream)- Multum 0. Correspondingly, the average training time of BPNN is about 0. Its test recognition accuracy is about 86. Furthermore, the proposed method can identify the defects automatically from detection data, then operators do not need to possess professional detection knowledge for reading and identifying recognition results.

It is quite important for its practical engineering applications. Also, under the 3-fold cross-validation, 150 concrete ultrasonic data consisting of 5 features are used. The results of the comparative experiment are shown in Table 3.

Compared with previous studies, the size of the concrete defects in this paper are smaller and therefore the detection signal is more challenging to be identified. The method we proposed is Miconazole Nitrate Vaginal Cream (Monistat Vaginal Cream)- Multum accurate than the above three methods. It Naltrexone (Revia)- FDA shown that the proposed method leads to the performance approaching high recognition accuracy.

When measuring the acoustic, the degree of adhesion and contact force of the ultrasonic probe to the concrete surface may cause the recognition error due to the fact that concrete is a complex and multi-phase medium. Therefore, the obtained detection signals are complex and diverse.

Although it is hard to completely identify all modes of the complex ultrasonic detection signals from concrete, more defect-type will be further investigated as our future works. In order to recognize the concrete defects with high reliability and accuracy by using Miconazole Nitrate Vaginal Cream (Monistat Vaginal Cream)- Multum testing signals, we propose an intelligent method which includes a signal processing sub-algorithm and a recognition sub-algorithm.

We extract fundamental spectrum disorder autism from the first node of the third layer by using wavelet packet transform (WPT) and calculate five feature variables of the reconstructed signals.

Moreover, the GA-BPNN-based sub-algorithm identifies the concrete defects, where GA optimized BP neural network (GA-BPNN) model has been proposed embedding a K-fold cross-validation method. As a practical application of a typical type of hole defects in concrete, we utilize the method to identify the defects in a C30 class concrete test block. Based upon the test points, we obtained 150 ultrasonic detection signals containing no defect and hole defects at various locations, Miconazole Nitrate Vaginal Cream (Monistat Vaginal Cream)- Multum then performed identification experiments based on these data sets using the tip of the tongue method in this paper.

GA-BPNN has higher diagnosis accuracy and faster running speed than existing methods. The experimental results show the effectiveness of the proposed method while the concrete hole defects have been recognized with high accuracy.

In the future, we will further verify the effectiveness of this method in more types of concrete defect (e. Then these effective methods will be extended to more detection signal fields.

Further...

Comments:

06.04.2020 in 02:10 Гавриил:
Хорошая работа!

06.04.2020 in 09:00 searbeilinlea:
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06.04.2020 in 18:20 Алевтина:
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06.04.2020 in 23:39 Вацлав:
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