| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 1107 | 4 | 4 | 2 |
The journal explores disciplines such as Artificial intelligence, Artificial neural network, Machine learning, Pattern recognition and Data mining. The concepts on Artificial intelligence presented in the journal can also apply to other research fields, including Genetic algorithm and Computer vision. The journal is focused mainly on Artificial neural network, particularly Backpropagation.
Machine learning research discussed connects with the study of Classifier (UML). International Journal of Computational Intelligence and Applications explores issues in Pattern recognition which can be linked to other research areas like Speech recognition and Feature (computer vision). Studies on Fuzzy logic discussed in the journal link to the field of Algorithm.
The most cited publications tackle a plethora of topics, such as Artificial intelligence, Machine learning, Pattern recognition, Data mining and Genetic algorithm. The journal papers feature Artificial intelligence research that overlaps with concepts in Particle swarm optimization. The most cited publications address concerns in Data mining which are intertwined with other disciplines, such as Cluster analysis, Feature selection, Curse of dimensionality and Nonlinear system.
The journal primarily tackles Artificial intelligence, Deep learning, Pattern recognition, Machine learning and Genetic algorithm. In International Journal of Computational Intelligence and Applications, Effective method, Adaptive sampling and Computer vision are investigated in conjunction with one another to address concerns in Artificial intelligence research. It facilitates discussions on Pattern recognition that incorporate concepts from other fields like Outcome (probability) and Metric (mathematics).
The research on Machine learning featured in the journal combines topics in other fields like Residual and Distance measures. Distributed computing and Data mining are some topics wherein Genetic algorithm research discussed in the journal have an impact. In the journal, Optimization algorithm and Decoding methods are investigated in conjunction with one another to address concerns in Artificial neural network research.
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 Computational Intelligence and Applications (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 Computational Intelligence and Applications (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, 5.56% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 5.88% 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 5.88% of all publications and 88.24% 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.
Completing research in computational intelligence opens a multitude of career paths in academia, research organizations, industry, and education. These fields such as artificial intelligence and machine learning are highly sought out, making qualified individuals valuable assets in the job market. Among these potential careers, teaching is an avenue worth exploring, as it allows for the sharing of knowledge and cultivating a new generation of researchers and specialists. Interested individuals may wonder about the journey toward becoming an educator in this field. For instance, let's consider the role of a history teacher, which, while different from computational intelligence, requires similar skills in research and content explanation. For those interested in teaching and based in the Palmetto State, check out this resource on how to be a history teacher in South Carolina which outlines the necessary steps to join the education sector. Entering the education sector can be rewarding, not only for the opportunity to shape future generations but also for the potential to conduct your own research and contribute more findings to your field of expertise. It’s also important to note that the skills used and developed in computational intelligence research- problem-solving, analytical thinking, and innovative designing- are incredibly useful in many other fields and careers. With the rapidly increasing demand for these skills, professionals in computational intelligence can have rewarding and impactful careers.
Mohammad Sultan Mahmud;Joshua Zhexue Huang;Xianghua Fu
(2020)Neha Singh;Deepali Virmani;Xiao-Zhi Gao
(2020)Luca Donati;Eleonora Iotti;Andrea Prati
(2021)Pursuing Computer Science in the USA offers various flexible and affordable pathways through online education. Many students choose self paced degrees, which allow learners to progress at their own speed, accommodating work and personal commitments. This flexibility is especially beneficial for those balancing careers or family life.
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