scholarly journals Analysis and Recognition Method of Internet Image Public Opinion Based on Partial Differential Equation

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yang Zhang
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Diffusion Coefficient ◽  
Public Opinion ◽  
Image Recognition ◽  
Opinion Mining ◽  
Diffusion Method ◽  
Partial Differential ◽  
Recognition Model ◽  
Model Based

This article comprehensively and systematically expounds the development trends and basic theory of partial differential methods, analyzes the characteristics of sampling multiscale transformation in detail, and deeply studies the network image denoising and network image restoration methods that perform partial differential diffusion in the pixel domain and the transform domain. An adaptive diffusion method of partial differential equations is proposed. Among them, the key parameters can be adaptively changed according to the curvature and gradient of the local geometric information of the network image, and the diffusion direction and intensity of the diffusion can be controlled. First, using the principle of variation, we derive the Euler equation corresponding to the diffusion method of partial differential equations and analyze its diffusion ability using the local orthogonal coordinate system of the network image. Based on the theoretical analysis of public opinion, this article applies opinion mining technology to the online public opinion early warning system to achieve the purpose of grasping the opinions of netizens in time and guiding the trend of public opinion. Opinion mining is the use of natural language processing technology to automatically extract the emotional tendencies and evaluation objects contained in the subjective text. In the edge area of the network image, the diffusion along the edge direction should have a large diffusion coefficient, and the diffusion along the vertical edge direction should have a small diffusion coefficient; in the flat area of the network image, it diffuses to the surrounding with equal intensity, and the diffusion intensity value is relatively high. Secondly, based on the analysis of the adaptive partial differential equation diffusion method, using the half-point difference format, a numerical method for network image recognition is designed. Both theoretical analysis and experimental results show that the network image recognition model based on adaptive partial differential equation diffusion is more effective than the model based on partial differential equation recognition; at the same time, experiments show that the network image recognition model based on adaptive partial differential equation diffusion is more effective than the network image recognition model based on ordinary diffusion. The network image recognition model based on constant partial differential equation diffusion is more effective in improving the quality of network image recognition.

scholarly journals Barcode Location in Financial Statement System Based on the Partial Differential Equation Image Recognition Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jinghua Ning ◽  
Song Yu
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Information Sharing ◽  
Image Recognition ◽  
Resource Sharing ◽  
Financial Analysis ◽  
Financial Statements ◽  
Recognition Algorithm ◽  
Financial Statement ◽  
Partial Differential

Financial statements are the basis of financial analysis. Most of them are still using traditional financial statement software, and financial data cannot achieve better information sharing. Using a barcode to improve the efficiency of data sharing is undoubtedly the most convenient and fast way to realize financial statement information sharing. This paper studies the problem of the barcode image location and recognition in the financial statement system and tries to apply the partial differential equation image recognition algorithm to the barcode location in the financial statement system. In this paper, image technology is used to preprocess the code 39 barcode label image in the captured image, including color space conversion, image enhancement, threshold segmentation, binarization, and edge detection. The barcode position location is realized by using the method based on integral projection peak analysis and Hough transform line detection. It is proved that the positioning function of the barcode makes the data in financial statements realize resource sharing. Then, the performance of the completed barcode positioning and recognition algorithm is tested. The reliability and effectiveness of the algorithm are verified on the manually made test set.

scholarly journals Video Recognition of Government Community Management Cases Based on Partial Differential Equation Method

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yumeng Sun
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Image Segmentation ◽  
Image Recognition ◽  
Community Management ◽  
Main Function ◽  
Partial Differential ◽  
Traditional Algorithm ◽  
Video Recognition ◽  
The Government

With the development of urban economic construction and urban planning, higher requirements are put forward for the government community in the corresponding community management, community service, and other related things. As an important technical means to assist the government and community in management, video recognition technology plays an important role in the accurate management and service of the government and community. Traditional algorithms based on partial differential equations will destroy image edges and image details in video recognition. Based on this, this paper improves the traditional partial differential equation algorithm of image recognition, selects the GAC model based on image segmentation in the main function, and innovatively optimizes the stop function of its equation function, so as to improve the effect of community case image segmentation. In the image smoothing layer, this paper innovatively selects the second derivative based on image processing as the inherent feature of image recognition, so as to solve the rough problem of image edge and improve the processing efficiency of the algorithm. In order to further maintain the details of the relevant images of community cases, this paper integrates the Gaussian curvature driving function on the improved partial differential equation algorithm, so as to protect the details of the smooth region of the relevant recognition video and solve the disadvantages of the traditional algorithm. The experimental results show that the improved partial differential equation algorithm proposed in this paper improves the accuracy of video recognition by about 5% compared with the traditional algorithm. At the same time, the new algorithm can well ensure the detail integrity of the recognized video.

scholarly journals Variations of Moisture Content in The Presence of Combined Flux

2018 ◽  
Vol 14 (1) ◽  
pp. 7624-7630
Author(s):  
Alpna Mishra ◽  
Sanjeev Kumar
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Diffusion Coefficient ◽  
Moisture Content ◽  
Pressure Gradient ◽  
Moisture Removal ◽  
Drying Process ◽  
Partial Differential ◽  
Latent Energy ◽  
Mechanical Methods

A model for diffusion in grains, through the drying process in the form of moisture removal, discussed through this work. While in drying, the moisture leaves the product as vapour or gas. This is achieved by impairing energy to the moisture molecule or changing the environment, so that the molecule will have sufficient latent energy to leave the product. Hence it is the process, which is intended to remove moisture from a feed substance so that the feed becomes dry as final product. Moisture reduction can also be achieved by mechanical methods. Using the pressure gradient as the deriving force with combined flux, we get a system of partial differential equation which will be then solved with the help of MATLAB 7.0 and finally the graphs shows the variation of moisture with respect to diffusion coefficient at different temperature and as well as variation of moisture with the time.

scholarly journals Research on Image Recognition of Building Wall Design Defects Based on Partial Differential Equation

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiwen Yu ◽  
Kai Wang ◽  
Shaoxuan Wang
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Image Recognition ◽  
Surface Defects ◽  
Feature Space ◽  
Inner Product ◽  
High Dimensional ◽  
Order Partial Differential Equation ◽  
Partial Differential ◽  
Building Wall

The detection of building wall surface defects is of great significance to eliminate potential safety hazards. In this paper, a research on building wall design defect image recognition based on partial differential equation is proposed. Collect the image data of building surface defects, sample and quantify the collected images, and preprocess the defect images such as digital threshold segmentation, filtering, and enhancement. Then, the improved partial differential equation is used to recognize the image as a whole. The second-order partial differential diffusion equation and the fourth-order partial differential equation are used to recognize the high-frequency and low-frequency bands of the image, respectively. The kernel principal component analysis algorithm is used to transfer the overall image input space to the high-dimensional feature space. The kernel function is used to calculate the inner product in different subband images of the high-dimensional feature space to reduce the dimension of the overall image. The processed coefficients are inversely transformed by nondownsampling contour wave to realize the overall image recognition and ensure that the edge information of the source image does not disappear. Experimental results show that compared with other algorithms, the proposed algorithm has better effect and better stability.

scholarly journals Pricing Parisian Option under a Stochastic Volatility Model

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Min-Ku Lee ◽  
Kyu-Hwan Jang
Keyword(s):  
Differential Equation ◽  
Partial Differential Equation ◽  
Stochastic Volatility ◽  
Stochastic Volatility Model ◽  
Barrier Options ◽  
Barrier Option ◽  
Partial Differential ◽  
Model Based ◽  
Volatility Model ◽  
Black Scholes

We study the pricing of a Parisian option under a stochastic volatility model. Based on the manipulation problem that barrier options might create near barriers, the Parisian option has been designed as an extended barrier option. A stochastic volatility correction to the Black-Scholes price of the Parisian option is obtained in a partial differential equation form and the solution is characterized numerically.

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