International Journal of Mathematical Sciences and Computing最新文献_第9页

Application of the Flow Curvature Method in Lorenz-Haken Model 流动曲率法在Lorenz-Haken模型中的应用

International Journal of Mathematical Sciences and Computing Pub Date : 2020-02-08 DOI: 10.5815/ijmsc.2020.01.04

A. Nazimuddin, Md. Showkat Ali

{"title":"Application of the Flow Curvature Method in Lorenz-Haken Model","authors":"A. Nazimuddin, Md. Showkat Ali","doi":"10.5815/ijmsc.2020.01.04","DOIUrl":"https://doi.org/10.5815/ijmsc.2020.01.04","url":null,"abstract":"We consider a recently developed new approach so-called the flow curvature method based on the differential geometry to analyze the Lorenz-Haken model. According to this method, the trajectory curve or flow of any dynamical system of dimension n considers as a curve in Euclidean space of dimension n . Then the flow curvature or the curvature of the trajectory curve may be computed analytically. The set of points where the flow curvature is null or empty defines the flow curvature manifold. This manifold connected with the dynamical system of any dimension n directly describes the analytical equation of the slow invariant manifold incorporated with the same dynamical system. In this article, we apply the flow curvature method for the first time on the three-dimensional Lorenz-Haken model to compute the analytical equation of the slow invariant manifold where we use the Darboux theorem to prove the invariance property of the slow manifold. After that, we determine the osculating plane of the dynamical system and find the relation between flow curvature manifold and osculating plane. Finally, we find the nature of the fixed point stability using flow curvature manifold.","PeriodicalId":312036,"journal":{"name":"International Journal of Mathematical Sciences and Computing","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134052102","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

Multi-Criteria Decision Making and Numerical Optimization Approaches for Optimizing Water Loss Management Strategies in Water Distribution System - A case of Urban Water Supply and Sanitation Authorities in Tanzania 配水系统失水管理策略优化的多准则决策与数值优化方法——以坦桑尼亚城市供水和卫生部门为例

International Journal of Mathematical Sciences and Computing Pub Date : 2020-02-08 DOI: 10.5815/ijmsc.2020.01.02

Maselle Joseph Kadenge, Mashaka Mkandawile, V. Masanja

{"title":"Multi-Criteria Decision Making and Numerical Optimization Approaches for Optimizing Water Loss Management Strategies in Water Distribution System - A case of Urban Water Supply and Sanitation Authorities in Tanzania","authors":"Maselle Joseph Kadenge, Mashaka Mkandawile, V. Masanja","doi":"10.5815/ijmsc.2020.01.02","DOIUrl":"https://doi.org/10.5815/ijmsc.2020.01.02","url":null,"abstract":"Water loss in water distribution systems (WDS) is a serious problem in Tanzania and the third world countries at large. A lot of water is lost on its way before reaching the consumers. This causes a shortage of water supply which leads to loss of revenues of the concerned water authorities. The control or reduction of water loss in the WDS is closely dependent on the commitment of the decision-makers and on the strategies and budget, they set for that purpose. This paper presents a combined model of Multi-Criteria Decision Making (MCDM) and Numerical optimization techniques which may help decision-makers to prioritize and select the best strategies to be used in the management of water loss in the WDS at Moshi Urban Water Supply and Sanitation Authority (MUWSA), Tanzania. The Multi-Criteria Decision Making family methods namely the Multi-Attribute Value Theory (MAVT), Simple Multi-Attribute Rating Technique Exploiting Ranks (SMARTER), and Complex Proportional Assessment (COPRAS) were used to evaluate and prioritize the strategies, whereas the Integer Linear Programming (ILP) technique a numerical optimization technique was used to select the best strategies or alternatives to be employed in water loss management. The results show that the most preferable alternative is replacement of dilapidated pipes while the least preferable alternative is network zoning. The model selects thirteen out of sixteen alternatives, which cost 97% (TZS 235.71 million) of the total budgets set by the water authority to form a portfolio of the best alternatives for water loss management. Furthermore, the model showed robustness as the selected portfolio of alternatives remained the same even when the weights of the evaluation criteria changed.","PeriodicalId":312036,"journal":{"name":"International Journal of Mathematical Sciences and Computing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133799428","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

Ferrer diagram based partitioning technique to decision tree using genetic algorithm 基于铁图的遗传算法决策树划分技术

International Journal of Mathematical Sciences and Computing Pub Date : 2020-02-08 DOI: 10.5815/ijmsc.2020.01.03

Pavan Sai Diwakar Nutheti, Narayan Hasyagar, R. Shettar, Shankru Guggari, Umadevi

引用次数: 7

An Approach of Securing Data using Combined Cryptography and Steganography 一种结合加密和隐写保护数据的方法

International Journal of Mathematical Sciences and Computing Pub Date : 2020-02-08 DOI: 10.5815/ijmsc.2020.01.01

Rosalina Nur Hadisukmana

引用次数: 8

Bayesian Parameter Inference of Explosive Yields Using Markov Chain Monte Carlo Techniques 基于马尔可夫链蒙特卡罗技术的爆炸当量贝叶斯参数推断

International Journal of Mathematical Sciences and Computing Pub Date : 2019-12-10 DOI: 10.36478/jeasci.2020.1115.1126

J. Burkhardt

{"title":"Bayesian Parameter Inference of Explosive Yields Using Markov Chain Monte Carlo Techniques","authors":"J. Burkhardt","doi":"10.36478/jeasci.2020.1115.1126","DOIUrl":"https://doi.org/10.36478/jeasci.2020.1115.1126","url":null,"abstract":"A Bayesian parameter inference problem is conducted to estimate the explosive yield of the first atomic explosion at Trinity in New Mexico. The first of its kind, the study advances understanding of fireball dynamics and provides an improved method for the determination of explosive yield. Using fireball radius-time data taken from archival film footage of the explosion and a physical model for the expansion characteristics of the resulting fireball, a yield estimate is made. Bayesian results from the Markov chain indicate that the estimated parameters are consistent with previous calculation except for the critical parameter that modifies the independent time variable. This unique result finds that this parameter deviates in a statistically significant way from previous predictions. Use of the Bayesian parameter estimates computed is found to greatly improve the ability of the fireball model to predict the observed data. In addition, parameter correlations are computed from the Markov chain and discussed. As a result, the method used increases basic understanding of fireball dynamics and provides an improved method for the determination of explosive yields.","PeriodicalId":312036,"journal":{"name":"International Journal of Mathematical Sciences and Computing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125899226","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: 5

An Application of the Two-Factor Mixed Model Design in Educational Research 双因素混合模型设计在教育研究中的应用

International Journal of Mathematical Sciences and Computing Pub Date : 2019-11-08 DOI: 10.5815/ijmsc.2019.04.03

O. A. Nuga

引用次数: 0

Comparison on Trapezoidal and Simpson’s Rule for Unequal Data Space 不等数据空间的梯形规则与辛普森规则的比较

International Journal of Mathematical Sciences and Computing Pub Date : 2019-11-08 DOI: 10.5815/ijmsc.2019.04.04

M. N. Dhali, Mohammad Farhad Bulbul, U. Sadiya

引用次数: 3

Periodic Pattern Formation Analysis Numerically in a Chemical Reaction-Diffusion System 化学反应扩散系统周期模式形成的数值分析

International Journal of Mathematical Sciences and Computing Pub Date : 2019-07-08 DOI: 10.5815/ijmsc.2019.03.02

A. Nazimuddin, Md. Showkat Ali

引用次数: 2

A Numerical Approach for Solving High-Order Boundary Value Problems 求解高阶边值问题的数值方法

International Journal of Mathematical Sciences and Computing Pub Date : 2019-07-08 DOI: 10.5815/ijmsc.2019.03.01

Falade K.I

引用次数: 1

Mining Maximal Subspace Clusters to deal with Inter-Subspace Density Divergence 挖掘最大子空间簇处理子空间间密度发散

International Journal of Mathematical Sciences and Computing Pub Date : 2019-07-08 DOI: 10.5815/ijmsc.2019.03.04

B. Lakshmi, K. Madhuri

{"title":"Mining Maximal Subspace Clusters to deal with Inter-Subspace Density Divergence","authors":"B. Lakshmi, K. Madhuri","doi":"10.5815/ijmsc.2019.03.04","DOIUrl":"https://doi.org/10.5815/ijmsc.2019.03.04","url":null,"abstract":"In general, subspace clustering algorithms identify enormously large number of subspace clusters which may possibly involve redundant clusters. This paper presents Dynamic Epsilon based Maximal Subspace Clustering Algorithm (DEMSC) that handles both redundancy and inter-subspace density divergence, a phenomenon in density based subspace clustering. The proposed algorithm aims to mine maximal and non-redundant subspace clusters. A maximal subspace cluster is defined by a group of similar data objects that share maximal number of attributes. The DEMSC algorithm consists of four steps. In the first step, data points are assigned with random unique positive integers called labels. In the second step, dense units are identified based on the density notion using proposed dynamically computed epsilon-radius specific to each subspace separately and user specified input parameter minimum points , τ. In the third step, sum of the labels of each data object forming the dense unit is calculated to compute its signature and is hashed into the hash table. Finally, if a dense unit of a particular subspace collides with that of the other subspace in the hash table, then both the dense units exists with high probability in the subspace formed by combining the colliding subspaces. With this approach efficient maximal subspace clusters which are non-redundant are identified and outperforms the existing algorithms in terms of cluster quality and number of the resulted subspace clusters when experimented on different benchmark datasets.","PeriodicalId":312036,"journal":{"name":"International Journal of Mathematical Sciences and Computing","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124226805","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