| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 86 | 55 | 92 | 19 |
| Computer Science | 199 | 154 | 207 | 26 |
The primary areas of discussion in the journal are Artificial intelligence, Control theory, Nonlinear system, Algorithm and Artificial neural network. It holds forums on Artificial intelligence that merges themes from other disciplines such as Machine learning, Computer vision and Pattern recognition. It focuses on Control theory as well as the interrelated topic of Chaotic.
The published articles mostly deal with topics like Artificial intelligence, Control theory, Complex system, Nonlinear system and Artificial neural network. The journal papers focus on Artificial intelligence but the discussions also offer insight into other areas such as Natural language processing, Machine learning, Theoretical computer science and Pattern recognition. Issues in Control theory were discussed in the most cited publications, taking into consideration concepts from other disciplines like Chaotic and Fuzzy logic.
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 Complexity (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 Complexity (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, 16.82% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 12.05% were posted by at least one author from the top 10 institutions publishing in the journal. Another 6.54% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 19.97% of all publications and 61.45% 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.
Mauro Castelli;Fabiana Martins Clemente;Aleš Popovič;Aleš Popovič;Sara Silva
(2020)Mohammad Kamrul Hasan;Muhammad Shafiq;Shayla Islam;Bishwajeet Pandey
(2021)Hijaz Ahmad;Ali Akgül;Tufail A. Khan;Predrag S. Stanimirović
(2020)Ibrahim Yasser;Fahmi Khalifa;Mohamed A. Mohamed;Ahmed Shaban Samrah
(2020)Ke Niu;Ke Niu;Jiayang Guo;Yijie Pan;Xin Gao
(2020)Hijaz Ahmad;Tufail A. Khan;Predrag S. Stanimirović;Yu-Ming Chu
(2020)Mi Li;Lei Cao;Qian Zhai;Peng Li
(2020)Xiaojia Ye;Wei Liu;Hong Li;Mingjing Wang
(2021)Jiying Lai;Shujing Gao;Yujiang Liu;Xinzhu Meng
(2020)Hanwen Liu;Huaizhen Kou;Chao Yan;Lianyong Qi
(2020)Exploring online education options can be a strategic way to launch or advance a career in Computer Science. Many students seek college majors that make the most money, and Computer Science consistently ranks as one of the top fields for high earning potential. Choosing the right degree program is crucial for gaining relevant skills and improving job prospects.
Cost is another important factor. Affordable programs allow students to obtain quality education without excessive debt. Consider looking into affordable online bachelor's degree options, which provide flexibility and savings while maintaining academic standards.
Application fees can sometimes be a barrier for prospective students. Luckily, several reputable institutions offer degree programs through colleges with no application fee, making it easier to apply to multiple schools and find the best fit.
For those eager to enter the workforce quickly, fast track bachelor's degree online programs offer an accelerated route to graduation. These programs can help students earn their degrees in less time while still covering core computer science concepts.
