Precision algorithms in second-order fractional differential equations

Liu, Chunguang

doi:10.2478/amns.2021.2.00157

Cited by 11 publications

(6 citation statements)

References 12 publications

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“…It can complete the local sampling and image-sharing task using a neural network. Since the convolutional neural networks can collect the spatial and channel information of feature graphs simultaneously, it is mostly used in the backbone network of the algorithm to achieve feature extraction tasks [29][30]. CNN structure is generally divided into the following layers: convolution, pooling, activation, and full connection layer.…”

Section: Basic Structure and Characteristics Of Convolution Neural Ne...mentioning

confidence: 99%

Fabric yarn detection based on improved fast R-CNN model

Xu¹

2023

3C TIC

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With the rapid development of modern computer technology, and gradually combined with the textile industry, the application of modern computer technology in the field of textile is increasingly extensive, which makes textile production gradually move towards the road of automation development. This paper proposes an automatic detection method of simple weave fabric density based on computer image vision. Computer vision and digital image processing technology are used to analyze and identify the simple weave fabric's warp and weft yarn information and calculate the fabric density. To avoid the phenomenon of warp and weft yarn skew, a method of fabric skew correction based on the Radon transform is proposed. The optimal decomposition order of these four fabrics is k = 2, k = 5, and k = 3. The decomposition series is k. It is found that the relative error of both warp and weft density is about 1.00%. Most of the data obtained by the method of correlation coefficient curve to determine the optimal decomposition series are consistent with the results of the energy curve method. The relative error of the density test results of No. 3 fabric, No. 6 fabric, and No. 7 fabric is higher than 10%, and the relative error of No. 3 fabric is the highest, reaching 66%. This shows serious errors in these three fabrics' warp and weft density. To solve the problems of simple weave fabric density detection, the corresponding algorithm is used to solve the problems. Finally, good results are obtained, which verifies the feasibility of this method. It is significant to realize the automatic measurement of fabric density in textile factories.

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Section: Basic Structure and Characteristics Of Convolution Neural Ne...mentioning

confidence: 99%

Fabric yarn detection based on improved fast R-CNN model

Xu¹

2023

3C TIC

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“…Find the required cloud feature lines. The same-name line of the point cloud is used to analyze the inclination of the building [10]. The acquisition method and the point cloud quality are important factors affecting data accuracy.…”

Section: Comparison Of Lines With the Same Namementioning

confidence: 99%

Building Tilt Scanning Measurement Based on Binary Linear Regression Analysis

Pei

Zhu

2023

Applied Mathematics and Nonlinear Sciences

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With the development of modern surveying and mapping technology, 3D laser scanners are increasingly used for building dip scanning. Building inclination characteristics are analyzed using three-dimensional point cloud data and binary linear regression. It can easily and intuitively obtain the inclination of the building. This method extracted the building inclination Angle from the point, line, plane, surface, and other angles. Then, a matching method based on two dimensions and surfaces is proposed, with a strong anti-noise ability. An optimal matching algorithm of structural plane and surface based on quadratic linear regression is proposed. Experiments prove the anti-interference ability and accuracy of this method. It is found that the binary linear regression fitting method can effectively identify the noise signal when there is a lot of noise interference in the point cloud data. It has good anti-interference ability.

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“…In accounting, improving the quality of accounting information requires the efficient use of infrastructure consolidation and integration can achieve optimization of accounting accounts in terms of quantity and level [5][6][7]. To achieve the optimization requirements, it is necessary to optimize the system settings with the help of digital algorithmic means and to seek breakthroughs in the project data settings [8][9][10][11][12]. By setting the display information and control information of the project, information on the source channel of funds, nature of funds, budget categories, etc, is obtained [13].…”

Section: Introductionmentioning

confidence: 99%

“…Rui Mi. Applied Mathematics and Nonlinear Sciences, 9(1) (2024)[1][2][3][4][5][6][7][8][9][10][11][12][13][14][15] …”

mentioning

confidence: 99%

Integration of government accounting system reform and university infrastructure consolidation based on type two fuzzy sets

2023

Applied Mathematics and Nonlinear Sciences

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Type II fuzzy set can innovate the accounting method of infrastructure consolidation and integration work. Based on this, this paper constructs a new and feasible accounting system for the integration of government accounting systems and university infrastructure. The specific application is that any point on the financial subordination domain and its corresponding subordination interval constitutes a type two fuzzy set, and the fuzzy set is used as the object for modeling. Using the interval type-two fuzzy set for word calculation, the result of the calculation is output by the decoder and sorted, and the value of the accounting account amount can be derived. The mutual subset measure between the input interval type II fuzzy set and the rule antecedent interval type II fuzzy set is used to check the accounting bills of the rule activation interval and to verify the performance of its use in the capital consolidation work of S universities. The experimental results show that after transferring the balance of $4,982,600 for prepaid construction and $4,956,200 for prepaid provisioning to the prepaid account on the basis of ensuring the consistency of the output KM algorithm, the balance of the account becomes $9,938,800. This result shows that the type II fuzzy set saves 42% of the arithmetic cost for this transfer of university infrastructure accounts, and contributes to the realization of the government accounting system reform and the improvement of financial management of the integration of university infrastructure accounts.

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Precision algorithms in second-order fractional differential equations

Cited by 11 publications

References 12 publications

Fabric yarn detection based on improved fast R-CNN model

Fabric yarn detection based on improved fast R-CNN model

Building Tilt Scanning Measurement Based on Binary Linear Regression Analysis

Integration of government accounting system reform and university infrastructure consolidation based on type two fuzzy sets

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