| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 270 | 92 | 144 | 21 |
| Engineering and Technology | 719 | 19 | 33 | 12 |
The main research concerns discussed in International Journal of Computational Intelligence Systems are Artificial intelligence, Fuzzy logic, Mathematical optimization, Data mining and Pattern recognition. The studies in Artificial intelligence featured incorporate elements of Machine learning, Computer vision and Natural language processing. The journal covers various topics on Fuzzy logic such as Fuzzy set, Fuzzy set operations, Fuzzy number and Fuzzy classification.
The journal connects research in Fuzzy set operations with the related topic of Defuzzification. The study on Mathematical optimization presented is investigated in conjunction with research in Algorithm.
The published articles cover a variety of subjects, including Artificial intelligence, Fuzzy logic, Machine learning, Data mining and Mathematical optimization. The Artificial intelligence studies presented in the most cited articles encompass related topics like Fuzzy set operations and also examine its connection to subjects such as Term (time). While Fuzzy logic is the focus of the most cited papers, it also provides insights into the studies of Quality (business), Analytic hierarchy process, Operations research and Management science.
International Journal of Computational Intelligence Systems mostly deals with topics like Artificial intelligence, Fuzzy logic, Pattern recognition, Mathematical optimization and Deep learning. In International Journal of Computational Intelligence Systems, Multiple-criteria decision analysis, Machine learning and Computer vision are investigated in conjunction with one another to address concerns in Artificial intelligence research. The journal features studies on Machine learning, including topics such as Support vector machine.
Topics in Fuzzy logic were tackled in line with various other fields like Discrete mathematics, Relation (database), Pure mathematics and Regular polygon. International Journal of Computational Intelligence Systems tackles studies in Computational intelligence and the interrelated subject of Algebra and Intuitionistic fuzzy to gain insights into Relation (database). While Pattern recognition is the key highlight in it, it also covered some subjects on Selection (genetic algorithm) and Feature (computer vision).
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 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 Computational Intelligence 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, 93.60% 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 0.00% of all publications and 100.00% 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.
While International Journal of Computational Intelligence Systems covers a broad range of pivotal topics such as Artificial Intelligence, Fuzzy Logic, and Mathematical Optimization, it is also important to underline the practical implications and the future directions of research these studies might inspire.
The practical applications of these research topics extend into diverse sectors, including but not limited to healthcare, education, business, and environmental science. For example, artificial intelligence and machine learning techniques are being leveraged to develop predictive models in healthcare, helping with early diagnoses and personalized treatment planning. Similarly, efforts in data mining and pattern recognition are increasingly being utilized in the education sector to enhance learning outcomes and personalize education. This is where the application of obtaining a teaching credential comes into play, with many opting for cost-effective online solutions like the cheapest teaching credential program in Vermont.
Given the fast-paced changes and technological advancements in these fields, future research directions will likely involve exploring the integration of these systems into the broader societal context, such as harnessing AI for sustainable development goals or promoting equitable education through data-driven decision-making. Further examination into the ethical considerations of comprehensive data usage and AI-based decision-making are also paramount to ensure unbiased, privacy-respecting practices that benefit society as a whole.
Unknown
(2023)Shengdong Du;Tianrui Li;Xun Gong;Shi-Jinn Horng
(2020)Lei Wang;Harish Garg
(2020)Huchang Liao;Zhongyuan Ren;Ran Fang
(2020)Shui-Hua Wang;Xiaosheng Wu;Yu-Dong Zhang;Chaosheng Tang
(2020)Peide Liu;Gulfam Shahzadi;Muhammad Akram
(2020)Unknown
(2022)Simone Spolaor;Caro E.M. Fuchs;Paolo Cazzaniga;Uzay Kaymak
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