scholarly journals Calculating university education model based on finite element fractional differential equations and macro-control analysis

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Caijuan Li ◽  
Nawaf Alhebaishi ◽  
Mohammed Alaa Alhamami
Keyword(s):  
Differential Equation ◽  
College Education ◽  
University Education ◽  
Control Analysis ◽  
Basic Model ◽  
Theory Of Education ◽  
Differential Equation Models ◽  
Basic Differential Equation ◽  
Fractional Differential ◽  
Education Model

Abstract Firstly, based on the charging theory of ‘education cost-sharing,’ under appropriate assumptions, two basic differential equation models are proposed to describe the problem of college education charges; secondly, through qualitative analysis of the basic model, it is concluded that colleges and universities maintain or impose several conditions for stabilising its education fees; finally, through the analysis of two basic models in three unique models under three situations, some new conclusions and suggestions on the macro-control of college education fees and enrolment scale are given. Also, three extended differential equation models are proposed.

scholarly journals Differential Equation Models for Education Charges of Universities in China and the Applications

2020 ◽  
Vol 2020 ◽  
pp. 1-5
Author(s):  
Minhang Liu ◽  
Hua Su
Keyword(s):  
Higher Education ◽  
Differential Equation ◽  
Qualitative Analysis ◽  
University Education ◽  
Social Concern ◽  
Differential Equation Models ◽  
Basic Differential Equation ◽  
State Investment ◽  
The Cost ◽  
The University

In recent years, with the expansion of university enrollment in China, the cost of running a school is getting higher and higher. Under the circumstance of insufficient state investment in higher education, the education charge paid by students has become an important source of the university income. It has become a hot topic of social concern to formulate a reasonable charging model to enable more students to enter higher education institutions. In this paper, we mainly put forward the basic differential equation models describing the problem of higher education charges in China. Through the qualitative analysis of these two basic models, we draw several conditions for universities to maintain or stabilize their education charges and give some suggestions on macrocontrol of university education charges in China.

scholarly journals Educational reform informatisation based on fractional differential equation

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Shuai Man ◽  
Rongjie Yang
Keyword(s):  
Differential Equation ◽  
Image Processing ◽  
Fractional Differential Equation ◽  
Processing Time ◽  
College Education ◽  
Original Method ◽  
University Education ◽  
Power Method ◽  
Information Power ◽  
Fractional Differential

Abstract In order to solve the problem that the image processing time is too long in the use of the original college education information power method, therefore, the design of the fractional differential equation of higher education information power method was created. According to the information source, a combination of various methods is set to complete the data collection. Compared with the content of fractional differential equation, the fractional differential equation is selected to complete the image information processing, develop the processing process and select the appropriate equipment to complete the image processing, set up the experimental equipment, and select the experimental samples to obtain the experimental results. Compared with the original method, the image processing time of this method is significantly shorter than that of the original method. Therefore, this method is more efficient for image processing and has a more obvious effect on the informatisation of university education.

Overview of Gene Regulatory Network Inference Based on Differential Equation Models

2020 ◽  
Vol 21 (11) ◽  
pp. 1054-1059
Author(s):  
Bin Yang ◽  
Yuehui Chen
Keyword(s):  
Differential Equation ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Network Inference ◽  
New Drugs ◽  
Gene Regulatory Network Inference ◽  
Ode Models ◽  
Differential Equation Models ◽  
Linear Ode ◽  
Gene Regulatory

: Reconstruction of gene regulatory networks (GRN) plays an important role in understanding the complexity, functionality and pathways of biological systems, which could support the design of new drugs for diseases. Because differential equation models are flexible androbust, these models have been utilized to identify biochemical reactions and gene regulatory networks. This paper investigates the differential equation models for reverse engineering gene regulatory networks. We introduce three kinds of differential equation models, including ordinary differential equation (ODE), time-delayed differential equation (TDDE) and stochastic differential equation (SDE). ODE models include linear ODE, nonlinear ODE and S-system model. We also discuss the evolutionary algorithms, which are utilized to search the optimal structures and parameters of differential equation models. This investigation could provide a comprehensive understanding of differential equation models, and lead to the discovery of novel differential equation models.

scholarly journals Fractional Differential Equation-Based Instantaneous Frequency Estimation for Signal Reconstruction

2021 ◽  
Vol 5 (3) ◽  
pp. 83
Author(s):  
Bilgi Görkem Yazgaç ◽  
Mürvet Kırcı
Keyword(s):  
Differential Equation ◽  
Fractional Differential Equation ◽  
Frequency Estimation ◽  
Signal Reconstruction ◽  
Reconstruction Method ◽  
Reconstruction Algorithms ◽  
Instantaneous Frequency Estimation ◽  
Proposed Model ◽  
Fractional Differential ◽  
Instantaneous Frequencies

In this paper, we propose a fractional differential equation (FDE)-based approach for the estimation of instantaneous frequencies for windowed signals as a part of signal reconstruction. This approach is based on modeling bandpass filter results around the peaks of a windowed signal as fractional differential equations and linking differ-integrator parameters, thereby determining the long-range dependence on estimated instantaneous frequencies. We investigated the performance of the proposed approach with two evaluation measures and compared it to a benchmark noniterative signal reconstruction method (SPSI). The comparison was provided with different overlap parameters to investigate the performance of the proposed model concerning resolution. An additional comparison was provided by applying the proposed method and benchmark method outputs to iterative signal reconstruction algorithms. The proposed FDE method received better evaluation results in high resolution for the noniterative case and comparable results with SPSI with an increasing iteration number of iterative methods, regardless of the overlap parameter.

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