| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 866 | 8 | 11 | 5 |
International Journal of Intelligent Engineering and Systems generally zeroes in on subjects such as Artificial intelligence, Computer network, Pattern recognition, Computer vision and Algorithm. The research on Artificial intelligence featured in International Journal of Intelligent Engineering and Systems combines topics in other fields like Machine learning and Natural language processing. Wireless sensor network is a focus of the Computer network works in the journal.
The published articles aim to foster the development of research in Artificial intelligence, Pattern recognition, Fuzzy logic, Game based and Cloud computing. The journal papers address concerns in Artificial intelligence which are intertwined with other disciplines, such as Machine learning and Computer vision. Issues in Pattern recognition were discussed in the journal articles, taking into consideration concepts from other disciplines like Information hiding, Pearson product-moment correlation coefficient, Electronic nose and Dual (category theory).
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 Intelligent Engineering and Systems (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 Intelligent Engineering and Systems (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, 99.20% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 0.00% 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 100.00% of all publications and 0.00% 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.
One of the advantages of diving into the fields of Intelligent Engineering and Systems is the wide range of career options. While research and academia are the main focus for most in this field, graduates can also explore other career paths such as becoming educators in the field. For example, those who have a passion for education and mathematics may consider becoming a middle school math teacher. This role is critical in shaping the mathematical skills of the students at an impressionable age and sparking initial interest in fields like intelligent engineering and systems. To understand the pathway to this career, you may visit this link to find out how long it takes to become a middle school math teacher in Kansas. Other potential career paths can range from systems analyst, data scientist, artificial intelligence engineer, software developer, to machine learning specialist. The wide variety of strategies that are used in these careers offer vast opportunities for practitioners in the field of Intelligent Engineering and Systems. Hence, one of the essential things to consider in your career development is choosing the most engaging and relevant job. This decision should be guided by understanding the nature of work, the skills you possess, and your long-term career objectives.
Mohammad Dehghani;Zeinab Montazeri;Hadi Givi
(2020)Mohammad Dehghani;Mohammad Mardaneh;Josep Guerrero
(2020)Mohammad Dehghani;Zeinab Montazeri;Ali Dehghani
(2020)Admi Syarif;Dian Anggraini;Kurnia Muludi
(2020)Admi Syarif;Ade Pamungkas;Renaldi Kumar
(2021)For those interested in Computer Science, exploring flexible learning options is crucial. Many students turn to online degree programs to balance education with work or personal commitments. These programs offer a variety of majors, including accelerated paths tailored for quicker completion.
Some learners prefer to fast-track their education through a degree in 6 months online, which provides foundational skills in a condensed timeframe. Building on this, many institutions also offer online accelerated bachelor's degree options, enabling students to enter the workforce sooner without compromising quality.
When planning a career post-graduation, it’s important to consider the earning potential of your degree. Computer Science often ranks among the highest paid degrees, reflecting strong demand across industries like software development, cybersecurity, and artificial intelligence.
Ultimately, leveraging these online degree pathways can provide an efficient and rewarding route into dynamic tech careers.
