| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 988 | 8 | 15 | 3 |
The journal investigates areas of study like Applied mathematics, Mathematical optimization, Algorithm, Nonlinear system and Convergence (routing). The studies in Applied mathematics featured incorporate elements of Type (model theory), Boundary value problem, Ordinary differential equation, Numerical analysis and Order (group theory). It links adjacent topics like Mathematical optimization with Benchmark (computing).
The research on Nonlinear system discussed in the journal draws on the closely related field of Iterative method.
The journal articles mainly tackle studies in Algorithm, Mathematical optimization, Topology, Bifurcation and Skew. The published papers link adjacent topics like Algorithm with Convergence (routing). The studies on Mathematical optimization discussed at the published articles can also contribute to research in the domains of Magnitude (mathematics), Location model and Cluster analysis.
The main research concerns discussed in the journal are Applied mathematics, Mathematical optimization, Nonlinear system, Artificial intelligence and Support vector machine. While Applied mathematics is the focus of the journal, it also provided insights into the studies of Initial value problem, Partial differential equation, Class (set theory), Algebraic equation and Function (mathematics). Mathematical optimization research featured in International Journal of Computing Science and Mathematics incorporates concerns from various other topics such as Transformation (function) and Path (graph theory).
The journal focuses on Nonlinear system but sometimes tackles the closely related topic of Convergence (routing) which is concerned with Control theory, Lyapunov function, Feedback controller, Dynamical system and Control (management). While the primary focus in International Journal of Computing Science and Mathematics is Artificial intelligence, it also dissects topics surrounding Machine learning and The Internet as a whole. The subject of Algorithm, which is connected to the field of Rate of convergence and Nonlinear systems of equations, serves as the foundation of the Support vector machine research featured in International Journal of Computing Science and Mathematics.
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 International Journal of Computing Science and Mathematics (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 International Journal of Computing Science and Mathematics (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, 47.06% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 16.67% were posted by at least one author from the top 10 institutions publishing in the journal. Another 5.56% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 33.33% of all publications and 44.44% 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.
The intensive use of mathematical optimization and algorithms in this journal highlights the rising importance of these subjects in scientific research. This surge in interest opens up significant career opportunities and prospects in this field, particularly for individuals keen on pursuing an academic career.
As a notable example, working knowledge in these subjects forms a crucial foundational part of a career in elementary school teaching in mathematics. This is particularly true for states like Wyoming, where rigorous academic standards require educators to possess a comprehensive grounding in core mathematical concepts. For more information on making a career shift into this rewarding field, you can follow this guide on {anchor}.
Moreover, aspiring researchers can potentially contribute to the existing body of knowledge in this field, thereby bringing meaningful improvements in various scientific and technological domains. The theoretical aspects of mathematical optimization and algorithms, as featured in this journal, can find practical applications in diverse areas like machine learning, optimization of logistics, network design, and supply chain management. This wide array of applications further extends the career prospects for enthusiasts in this domain.
In conclusion, the dominant prevalence of mathematical optimization and algorithms in academic research underscores the value associated with mastering these subjects. Whether it's making a career switch, embarking on a scientific project, or simply nurturing a passion for math, investing time and effort in these disciplines can prove immensely fruitful.
Lei Du;Zhihua Cui
(2021)For students exploring Computer Science, related fields like engineering, data science, and physics offer complementary skills and alternative career paths. Many institutions now provide affordable options to pursue these disciplines online, allowing for flexible learning without sacrificing quality.
Mechanical Engineering remains a popular choice for those interested in the practical applications of technology. Programs like the cheapest online mechanical engineering degree offer an entry point to this extensive field, combining theoretical foundations with hands-on problem-solving skills essential for many tech-driven industries.
Physics is foundational for understanding the principles underlying computer hardware and algorithm design. Students can consider pursuing an online physics bachelor's degree that provides strong analytical and quantitative skills, broadening career opportunities in research and development.
Data science is a rapidly growing area closely linked with Computer Science. A well-structured data science learning path equips graduates with expertise in big data analytics, machine learning, and programming—skills highly sought after in diverse industries.
For those keen on hardware and systems, an online electrical engineering degree ranking can guide students toward top programs focused on circuits, embedded systems, and network infrastructure, complementing computer science knowledge for a well-rounded technology career.
