1937-5093
Published by: American Institute of Mathematical Sciences
| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 300 | 32 | 47 | 9 |
The journal explores disciplines such as Mathematical analysis, Boltzmann equation, Statistical physics, Kinetic energy and Mathematical physics. The studies on Mathematical analysis discussed can also contribute to research in the domains of Compressibility and Nonlinear system. Kinetic and Related Models addresses concerns in Boltzmann equation which are intertwined with other disciplines, such as Boltzmann constant, Classical mechanics, Kinetic theory of gases, Uniqueness and Lattice Boltzmann methods.
Lattice Boltzmann methods study tackled is connected to the field of Bhatnagar–Gross–Krook operator. The research on Statistical physics tackled can also make contributions to studies in the areas of Limit (mathematics) and Fokker–Planck equation. Initial value problem research presented is mostly focused on the subject of Cauchy problem.
Most of the Bounded function studies addressed also intersect with Domain (mathematical analysis).
The most cited publications investigate studies in Mathematical analysis, Classical mechanics, Boltzmann equation, Boltzmann constant and Statistical physics. The most cited articles explore issues in Mathematical analysis which can be linked to other research areas like Work (thermodynamics) and Thermodynamic equilibrium. While the most cited papers focused on Statistical physics, they were also able to explore topics like Closure (topology), Limit (mathematics) and Kinetic energy.
The journal tackles a plethora of topics, such as Boltzmann equation, Statistical physics, Mathematical physics, Applied mathematics and Limit (mathematics). The research on Boltzmann equation featured in it combines topics in other fields like Thermodynamic limit, Relaxation (physics), Uniqueness, Sobolev space and Navier–Stokes equations. Topics in Statistical physics explored in it were investigated in conjunction with research in Range (statistics) and Kinetic energy.
Issues in Applied mathematics were discussed, taking into consideration concepts from other disciplines like Class (set theory), Relaxation (iterative method) and Rate of convergence. Concepts in Nonlinear system, as well as related topics in Mathematical analysis, Biological neuron model, Artificial neural network and Stochastic differential equation, are covered in the Kinetic theory of gases research presented in the journal. The Mathematical analysis works featured in the journal incorporate elements from Weak convergence, Random walk and Diffusion equation.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Kinetic and Related Models (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Kinetic and Related Models (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 87.18% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 20.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 60.00% of all publications and 20.00% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Michael Herty;Gabriella Puppo;Sebastiano Roncoroni;Giuseppe Visconti
(2020)Hyunjin Ahn;Seung-Yeal Ha;Woojoo Shim
(2021)Seung Yeal Ha;Seung Yeal Ha;Jinwook Jung;Jeongho Kim;Jinyeong Park
(2021)Fabio Camilli;Giulia Cavagnari;Raul De Maio;Benedetto Piccoli
(2021)Emeric Bouin;Jean Dolbeault;Christian Schmeiser
(2020)Jingwei Hu;Jie Shen;Yingwei Wang
(2020)Pursuing a degree in Mathematics opens doors to diverse career options, especially when complemented by related fields. Many students explore online programs that align with their interests and industry demands. For example, an ms in digital marketing degree cost tuition fees can be surprisingly affordable, allowing math graduates to transition into data-driven marketing roles.
If leadership and business are appealing, consider options like the cheapest 1 year online mba programs, which enable rapid advancement in management and analytics-based roles. These programs often value strong quantitative backgrounds, making mathematicians strong candidates.
For those interested in organizational dynamics, the masters degree in human resource management online can complement mathematical skills with people management expertise, broadening prospects in workforce analytics and HR technology.
Additionally, the healthcare sector offers opportunities where mathematics intersects with patient care data through nursing online programs. These programs combine practical healthcare training with analytical skills useful in health informatics and operations management.
