| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 558 | 39 | 72 | 10 |
| Engineering and Technology | 1319 | 8 | 11 | 4 |
International Journal of Bio-inspired Computation facilitates discussions on Mathematical optimization, Artificial intelligence, Particle swarm optimization, Algorithm and Metaheuristic. It holds forums on Mathematical optimization that merges themes from other disciplines such as Convergence (routing) and Benchmark (computing). The Benchmark (computing) study featured in the journal draws connections with the study of Optimisation algorithm.
While work presented in it provided substantial information on Artificial intelligence, it also covered topics in Cuckoo search, Data mining, Swarm intelligence, Machine learning and Pattern recognition. International Journal of Bio-inspired Computation connects research in Data mining with the related topic of Cluster analysis. The studies in Swarm intelligence featured incorporate elements of Swarm behaviour and Ant colony.
The Particle swarm optimization research presented in International Journal of Bio-inspired Computation explores the relationship between Control theory and the closely related topic of Electric power system. Most of the Metaheuristic studies addressed also intersect with Firefly algorithm. The work on Evolutionary algorithm addressed in it expands to the thematically related Evolutionary computation.
The journal articles cover a variety of subjects, including Mathematical optimization, Artificial intelligence, Swarm intelligence, Particle swarm optimization and Cuckoo search. The studies on Mathematical optimization discussed at the most cited articles can also contribute to research in the domains of Algorithm and Benchmark (computing). The published articles focus on Artificial intelligence but the discussions also offer insight into other areas such as Machine learning and Firefly algorithm.
International Journal of Bio-inspired Computation generally zeroes in on subjects such as Artificial intelligence, Mathematical optimization, Algorithm, Optimisation algorithm and Pattern recognition. The journal explores issues in Artificial intelligence which can be linked to other research areas like Task (project management), Join (topology) and Distributed database. The journal features works in Mathematical optimization, more specifically Metaheuristic, Differential evolution and Particle swarm optimization, and explores their relation to disciplines like Quadratic assignment problem.
International Journal of Bio-inspired Computation addresses concerns in Algorithm which are intertwined with other disciplines, such as Evolutionary algorithm, Genetic algorithm and Adjacency matrix. In addition to Optimisation algorithm research, International Journal of Bio-inspired Computation aims to explore topics under Multivariable calculus, Size adjustment, Chaotic map and Order (ring theory). The research on Pattern recognition tackled can also make contributions to studies in the areas of Neighbourhood (graph theory) and Magnetic resonance imaging.
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 Bio-inspired Computation (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 Bio-inspired Computation (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, 32.50% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 14.81% were posted by at least one author from the top 10 institutions publishing in the journal. Another 14.81% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 22.22% of all publications and 48.15% 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.
Publishing a research paper in the International Journal of Bio-inspired Computation can provide various career advancement opportunities. The recognition gained from publishing in such a reputable journal is often beneficial when seeking academic positions or pursuing further research opportunities. An excellent example of a career path to consider is integrating the knowledge acquired and continuing research on topics like Mathematical optimization, Artificial intelligence, etc., to become a middle school math teacher.
Teaching enables academics to inspire the younger generation with their knowledge and potentially promote further interest in bio-inspired computation within schools. However, the process of becoming a teacher, particularly in the state of Massachusetts, involves various steps including, acquiring the necessary qualifications, applying for licensure, and gaining teaching experience. The process can take several years, but the experience is often rewarding, both personally and professionally.
More comprehensively understanding the process is essential if you are considering this career pathway. Here is a guide on how long does it take to become a middle school math teacher in Massachusetts.
However, it is essential to remember that research publication does not restrict oneself to one career path but opens up a plethora of opportunities across the academics and industry where bio-inspired computation and Artificial Intelligence's role is increasingly significant.
Redouane Boudjemaa;Diego Oliva;Fatima Ouaar
(2020)Samira Ghorbanpour;Trinadh Pamulapati;Rammohan Mallipeddi
(2021)Xuesong Yan;Chengyu Hu;Victor S. Sheng
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