New Orientations in Applied and Computational Mathematics
View Published Articles →01About This Special Issue
An increasing interest in analyzing and modeling high-dimensional data, both static and dynamic, and handling very large data sets in multiple scientific domains has led to an increased flow of ideas between applied mathematics, statistics, and computation. A synergy is emerging among fields such as statistical modeling of high-dimensional data, parameter estimation, optimization, machine learning, dynamical systems, numerical methods, and computational mathematics. One aspect of the development is the rapid convergence of research interests between Statistics and Computer Science. Sophisticated mathematical tools are increasingly used to develop new models, modify existing ones, and analyze system performance. Therefore, this special issue focuses on new orientations in Applied and Computational Mathematics. We invite researchers to submit original research articles on current state-of-the-art theories and techniques in this field.02Meet the Guest Editors
Our distinguished editors bring deep subject-matter expertise to curate high-quality research and ensure a rigorous peer-review process.
Lead Guest Editor
Snehanshu Saha
Department of Computer Science and Engineering, People's Education Society Institute of Technology, Bangalore South Campus, Bangalore, India
Guest Editor
Harendra Kumar
Department of Mathematics and Statistics, Gurukula Kangari University, Haridwar, India
Guest Editor
E. Alvarz Verdejo
Department of Methods for Economics and Business, University of Granada, Granada, Spain
Guest Editor
Zhaorui Li
Computational Physics and Methods Division (Ccs-2), Los Alamos National Laboratory, Los Alamos, United States
Guest Editor
Sunil Kumar
Department of Mathematics, National Institute of Technology, Jamshedpur, India
Guest Editor
Cristina Caridade
Department of Physics and Mathematics, Coimbra Institute of Engineering, Polytechnic Institute of Coimbra, Coimbra, Portugal
Guest Editor
Lukasz Glinka
American Association of International Researchers under Natural Science Forum (Membership NS-AAIR-1011, 2014-present), American Research Institute for Policy Development, New York, United States
Guest Editor
Fateme Ghomanjani
Internal and Preventive Medicine, College of Veterinary Medicine, Mosul University, Mosul, Iran
Guest Editor
Petr Belov
Moscow State University after Bauman, Москва, Russian Federation
Guest Editor
Hai Zhang
School of Mathematics and Computation Science, Anqing Normal University, Anqing, China
Guest Editor
Onur Alp Ilhan
Mathematics Department, Erciyes University, Kayseri, Turkey
Guest Editor
lugen zake
University of Mosul, Iraq
Guest Editor
lugen zake
University of Mosul, Mosul, Iraq
Guest Editor
Asif Ekbal
Department of Computer Science and Engineering, Indian Institute Of Technology Patna, Patna, India
Guest Editor
Mahmoud Farag
Mathematics and Statistics Department, Minia University, Cairo, Egypt
Guest Editor
Taha Abdel Wahid
Basic Sciences Department, ELGazeera High Institute for Engineering and Technology, Cairo, Egypt
Guest Editor
Rahul Banerjee
Department Of Mathematics, St. Paul's Cathedral Mission College, Kolkata, India
Guest Editor
Mohammed O. Al-Amr
Department of Mathematics, College of Computer Sciences and Mathematics, University of Mosul, Mosul, Iraq
Guest Editor
Mahboubeh Molavi-Arabshahi
Marine Science Department, Iranian National Institute for Oceanography & Atmospheric science (INIOAS), Tehran, Iran
03Published Articles
The following articles have been published in this special issue.
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Issue: Volume 4, Issue 1-1, January 2015Pages: 12-17Received: 4 January 2015Accepted: 26 January 2015Published: 9 February 2015DOI: 10.11648/j.acm.s.2015040101.13Downloads:Views:Abstract: The Finite Volume Method (FVM) is currently the most popular method in CFD. The main reason is that it can resolve some of the difficulties that the other methods have. Finite volume methods are a class of discretization schemes that have proven highly successful in approximating the solution of a wide variety of conservation law systems [1]. Finit... Show More -
Implicit Runge-Kutta Method for Van Der Pol Problem
Issue: Volume 4, Issue 1-1, January 2015Pages: 6-11Received: 7 June 2014Accepted: 25 June 2014Published: 13 July 2014DOI: 10.11648/j.acm.s.2015040101.12Downloads:Views:Abstract: In this manuscript the implicit Runge-Kutta (IRK) method, with three slopes of order five has been explained, and is applied to Van der pol stiff differential equation. Truncation error, of order five, has been estimated. Stability of the procedure for the Van der pol equation, is analyzed by the Lyapunov method. To illustrate the structure of the... Show More -
Issue: Volume 4, Issue 1-1, January 2015Pages: 1-5Received: 21 April 2014Accepted: 22 June 2014Published: 30 June 2014DOI: 10.11648/j.acm.s.2015040101.11Downloads:Views:Abstract: In this paper substantiated for a Manjeron generalized equation with non-smooth coefficients a three dimensional Goursat problem -3D Goursat problem with non-classical boundary conditions is considered, which requires no matching conditions. Equivalence of these conditions three dimensional boundary condition is substantiated classical, in the case... Show More
