Complex & Intelligent Systems

Top Research Topics at Complex & Intelligent Systems?

The journal was organized to reinforce research efforts on Computational intelligence, Artificial intelligence, Fuzzy logic, Mathematical optimization and Algorithm. Some problems in Computational intelligence that were presented in the journal overlapped with concepts under Artificial neural network, Fuzzy set, Benchmark (computing), Evolutionary algorithm and Optimization problem. Issues in Artificial intelligence were discussed, taking into consideration concepts from other disciplines like Machine learning, Computer vision and Pattern recognition.

Segmentation is the primary subject of Pattern recognition works presented in it. Topics in Fuzzy logic explored in it were investigated in conjunction with research in Pythagorean theorem and Data mining. While Complex & Intelligent Systems focused on Mathematical optimization, it was also able to explore topics like Ranking and Convergence (routing).

• Computational intelligence (71.19%)
• Artificial intelligence (26.42%)
• Fuzzy logic (17.61%)

What are the most cited papers published in the journal?

• A benchmark test suite for evolutionary many-objective optimization (138 citations)
• Social group optimization (SGO): a new population evolutionary optimization technique (95 citations)
• Genetic programming for production scheduling: a survey with a unified framework (94 citations)

Research areas of the most cited articles at Complex & Intelligent Systems:

The most cited papers cover a variety of subjects, including Computational intelligence, Artificial intelligence, Mathematical optimization, Machine learning and Fuzzy logic. The published papers explore issues in Computational intelligence which can be linked to other research areas like Fuzzy set, Multi-objective optimization, Evolutionary algorithm and Algorithm, Optimization problem. While the journal articles focused on Artificial intelligence, they were also able to explore topics like Genetic algorithm scheduling and Test functions for optimization.

Papers citation over time

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.

Top authors and change over time

The top authors publishing in Complex & Intelligent Systems (based on the number of publications) are:

• Harish Garg (13 papers) published 8 papers at the last edition, 5 more than at the previous edition,
• Yaochu Jin (9 papers) published 3 papers at the last edition, 1 more than at the previous edition,
• Amir Hooshang Mazinan (8 papers) absent at the last edition,
• Ling Wang (7 papers) published 6 papers at the last edition, 5 more than at the previous edition,
• D. Nagarajan (7 papers) published 3 papers at the last edition, 2 more than at the previous edition.

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.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Complex & Intelligent Systems (based on the number of publications) are:

• Islamic Azad University (23 papers) published 9 papers at the last edition, 3 more than at the previous edition,
• Thapar University (17 papers) published 12 papers at the last edition, 9 more than at the previous edition,
• Beijing Jiaotong University (12 papers) published 10 papers at the last edition, 8 more than at the previous edition,
• King Abdulaziz University (11 papers) published 8 papers at the last edition,
• Southern University of Science and Technology (11 papers) published 6 papers at the last edition, 5 more than at the previous edition.

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.

Publication chance based on affiliation

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, 5.07% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 20.51% were posted by at least one author from the top 10 institutions publishing in the journal. Another 12.64% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 18.82% of all publications and 48.03% were from other institutions.

Returning Authors Index

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.

Returning Institution Index

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.

The experience to innovation index

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:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Career Opportunities in Complex & Intelligent Systems

The vast and varied nature of research topics in Complex & Intelligent Systems opens up abundant career opportunities for students and professionals. From academia, research, and development to technology companies and educational institutions, the demand for expertise in computational intelligence, artificial intelligence, fuzzy logic, mathematical optimization, and other associated areas is ever-growing. Whether you are interested in a research-oriented career path, looking to specialize, or thinking about switching career paths, having a solid understanding of these subjects can provide a significant advantage.

One of the popular career choices for individuals with knowledge and skills in complex & intelligent systems is becoming an educator. There is a significant requirement for teaching professionals who can impart education on these complex subjects. For example, if you are based in South Dakota and interested in an academic career, you can explore how to start your journey. You might wonder how an individual with a bachelor's degree can transition into this career. For helpful resources on this, you can refer to this guide on how to become a teacher in South Dakota with a bachelor's degree.

Apart from education and academia, individuals with skills in one or multiple areas of Complex & Intelligent Systems can also pursue roles such as Data Scientist, Machine Learning Engineer, AI Developer, and Systems Analyst among others. These roles involve applying the principles and techniques of intelligent systems to real-world problems, creating innovative solutions, and pushing the envelope of what's possible with technology.

No matter what your career aspirations are, understanding the varied research areas in Complex & Intelligent Systems can open doors to numerous exciting and rewarding professional opportunities.