Universal Journal of Applied Mathematics最新文献_第2页

Confounding and Effect Modification in Biostatistics: An Overview 生物统计学中的混淆和效应修正:综述

Universal Journal of Applied Mathematics Pub Date : 2023-04-01 DOI: 10.13189/ujam.2023.110102

Mário Basto, Teresa Abreu, R. Gonçalves, J. M. Pereira

引用次数: 0

Numerical Approaches of Pricing European Options in the Cox-Ross-Rubinstein Models Cox-Ross-Rubinstein模型下欧式期权定价的数值方法

Universal Journal of Applied Mathematics Pub Date : 2022-12-01 DOI: 10.13189/ujam.2022.100301

H. Phan, Seonguk Kim

引用次数: 0

Supervised Regularized Multidimensional Scaling Using Weighted Stress Measure 基于加权应力测量的监督正则化多维标度

Universal Journal of Applied Mathematics Pub Date : 2022-09-01 DOI: 10.13189/ujam.2022.100202

Md. Tohidul Islam, Md. Anwarul Islam Bhuiyan, S. Jahan

引用次数: 0

Modelling J-Curve by Using Differential Equations: Studies in Finances and Entrepreneurship 用微分方程建模j曲线:财务与创业研究

Universal Journal of Applied Mathematics Pub Date : 2022-09-01 DOI: 10.13189/ujms.2022.100203

Madhusudan V Atre, Hrvoje Volarević

引用次数: 0

An Open-Source Simulation Model for Solving Scheduling Problems 求解调度问题的开源仿真模型

Universal Journal of Applied Mathematics Pub Date : 2022-09-01 DOI: 10.13189/ujam.2022.100201

Aydin Teymourifar, Jie Li, Dan Li, Taicheng Zheng

引用次数: 0

New Normal Destination Development in the Tourism Industry 旅游目的地发展新常态

Universal Journal of Applied Mathematics Pub Date : 2022-03-01 DOI: 10.13189/ujam.2022.100101

M. S. Sinaga, H. D. M. Hutabarat, Y. Rangkuti

引用次数: 0

A Comparison Between Two Approaches to Optimize Weights of Connections in Artificial Neural Networks 人工神经网络中两种连接权优化方法的比较

Universal Journal of Applied Mathematics Pub Date : 2021-07-01 DOI: 10.13189/ujam.2021.090201

Aydin Teymourifar

{"title":"A Comparison Between Two Approaches to Optimize Weights of Connections in Artificial Neural Networks","authors":"Aydin Teymourifar","doi":"10.13189/ujam.2021.090201","DOIUrl":"https://doi.org/10.13189/ujam.2021.090201","url":null,"abstract":"Artificial neural networks (ANNs) have been used for estimation in numerous areas. Raising the accuracy of ANNs is always one of the important challenges, which is generally defined as a non-linear optimization problem. The aim of this optimization is to find better values for the weights of the connections and biases in ANN because they seriously affect the efficiency. This study uses two approaches to do such optimization in an ANN. For this aim, we create a feed-forward backpropagation ANN using the functions of MATLAB's deep learning toolbox. To improve its accuracy, in the first approach, we use the Levenberg - Marquardt algorithm (LMA) for training, which is available in MATLAB's deep learning toolbox. In the second approach, we optimize the values of weights and biases of ANN with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), available in MATLAB's global optimization toolbox. Then, we assess the accuracy of estimation for the trained ANNs. In this way, for the first time in the literature, we compare these methods for the optimization of an ANN. The used data sets are also available in MATLAB. Based on the acquired results, in some data sets, training with LMA, and for some others training with PSO cause the best results, however, training with LMA is faster, significantly. Although the used approaches and the obtained conclusions are beneficial for researchers that work in this field, they have some limitations. For instance, since only the functions and data sets from MATLAB are used, it can only serve as an example for researchers.","PeriodicalId":372283,"journal":{"name":"Universal Journal of Applied Mathematics","volume":"18 Suppl 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125735605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A SEIRD Model for Analysing the Dynamics of Coronavirus (COVID-19) Pandemic in Nigeria 尼日利亚冠状病毒(COVID-19)大流行动态分析的SEIRD模型

Universal Journal of Applied Mathematics Pub Date : 2021-03-01 DOI: 10.13189/UJAM.2021.090102

A. Wusu, O. Olabanjo, Benjamin S. Aribisala

{"title":"A SEIRD Model for Analysing the Dynamics of Coronavirus (COVID-19) Pandemic in Nigeria","authors":"A. Wusu, O. Olabanjo, Benjamin S. Aribisala","doi":"10.13189/UJAM.2021.090102","DOIUrl":"https://doi.org/10.13189/UJAM.2021.090102","url":null,"abstract":"The first case of the novel coronavirus (COVID–19) in sub–Saharan Africa was confirmed by Nigeria and the figure has since then been on the rise. Current global efforts are geared towards getting effective vaccine for the cure of the disease. The hope of accessing the relieve offered by the arrival of such vaccine will obviously take significant amount of t ime. In the face of the resurgence of the disease, the need to slow the spread and flatten the curves is currently a priority of both governmental and non–governmental organisations in Nigeria. If the dynamics of the disease can be determined, then it becomes easier to strategize and make suitable preventive policies that will slow the spread and ultimately flatten the c urves. Here, the goal is to develop a compartmental–based model for analysing the dynamics of the pandemic in Nigeria. Considering the control policies currently in place social distancing, mask usage, personal hygiene and quarantine, and using data provided by Nigeria Centre for Disease Control (NCDC), World Health Organization (WHO) and Wolfram Data Repository on COVID–19, the proposed model is fitted to the available data using the Quasi-Newton algorithm. The infection rate, average latent time, average infective time and average mortality rate are estimated. Also, the overall effectiveness of the current control policies is measured. Predictions on the turning points and possible vanishing time of the virus in Nigeria are made. Recommendations on how to manage the resurgence of the disease in Nigeria are also suggested.","PeriodicalId":372283,"journal":{"name":"Universal Journal of Applied Mathematics","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124107954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Equal Sums of Quartics (In Context with the Richmond Equation) (ax4+by4+cz4+dw4=0) 四分位数的等和(在里士满方程中)(ax4+by4+cz4+dw4=0)

Universal Journal of Applied Mathematics Pub Date : 2020-10-01 DOI: 10.13189/ujam.2020.080201

S. Tomita, Oliver Couto

引用次数: 0

Some Inequalities for N-Times Differentiable s-Convex and tgs-Convex Functions n次可微s-凸和tgs-凸函数的若干不等式

Universal Journal of Applied Mathematics Pub Date : 2020-04-01 DOI: 10.13189/ujam.2020.080101

D. Demir, Gülsüm Şanal

引用次数: 1