This study aims to determine the trend of published studies on the application of advanced artificial intelligence tools in the field of Fuzzy Logic. In this study, where documents published in the SCOPUS database were analyzed, the bibliometrix technique, one of the bibliometric analysis methods, was preferred. In the study where 232 documents were examined, it was determined that the published documents were between the years 1990 and 2025 and that the documents were published in 201 sources. It was determined that most of the published documents were published in the article document type. When the most cited studies at the global and local level were examined, it was seen that the most cited publication at the global level was “MELLIT A, 2008, PROG ENERGY COMBUST SCI”. It was determined that the most cited studies at the local level were “BOSE BK, 2017, PROC IEEE” and “MELLIT A, 2008, PROG ENERGY COMBUST SCI”. It was determined that the most trending topic in the published documents was “neural networks” and then “expert systems”. It is believed that the results obtained from the research will shed light and guide researchers who will work in this field.
Nowadays, smart technologies and data-driven decision-making processes have become a necessity. For
this reason, the integration of advanced artificial intelligence (AI) tools into many sectors is increasing.
With these tools, fuzzy logic has come to the fore in many areas, from the healthcare sector to industrial
automation systems, to manage uncertainty and make many complex decisions. To give an example from
the studies, fuzzy logic and Analytical Hierarchy Process (AHP) were applied in early-stage Alzheimer’s
diagnosis and allowed the evaluation of uncertain human behaviors [
Nowadays, the use of generative artificial intelligence in higher education is increasing day by day. The
qualitative development made by [
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To achieve the research purpose, the following questions were answered: 1. What is the distribution of publications in terms of main information, such as year, document type, etc.? 2. Which documents are cited most globally and locally? 3. What is the most trending topic? 4. What is the distribution of publications by year? 5. What are the most relevant sources?
In this study, which was conducted to determine the trend towards the application of advanced artificial
intelligence tools in the field of Fuzzy Logic, the SCOPUS database was used. SCOPUS was preferred
because it is “a database that provides a comprehensive overview of global interdisciplinary scientific
information covering the fields of science, technology, medicine, social sciences, arts and humanities” 1.
Additionally, the Scopus database was chosen because it provides easy access to researchers. For the
literature search, the “article title, abstract, keywords” search option in the SCOPUS database was
selected and the keywords TITLE-ABS-KEY (“Fuzzy Logic*" AND “Articfiial Intelligence*" OR "Advanced
AI Tools*") were used. All filters included in the data scan are given in Table 1. The literature search
conducted by the researchers was completed on June 20, 2025. In this context, the analyzed data were
limited to the studies indexed in SCOPUS until June 20, 2025. The data collected for the research
were analyzed with bibliometrix2, an open source tool that includes bibliometric analysis methods
developed by [
The study focused on general information about 232 documents, the most cited documents globally and locally, and trending topics.
As seen in Table 1, the documents published on the application of advanced artificial intelligence tools in the field of Fuzzy Logic were carried out between 1990 and 2025. In the mentioned years, a total of 232 studies were published in 201 sources such as journals, books, and similar. 80 of the publications were published in the article document type, 14 were books, 35 were book chapters, 61 were conference papers, 7 were conference reviews, and 35 were reviews. From the findings, it was determined that the authors preferred to write their publications in the "article" type. 1Scopus https://www.scopus.com/home.uri 2Bibliometrix https://www.bibliometrix.org/home/index.php/layout/bibliometrix 3Biblioshiny https://www.bibliometrix.org/home/index.php/layout/biblioshiny
The study also aimed to determine the citation status of documents published in the SCOPUS database. In this context, documents were examined according to their citation status both globally and locally. Table 2 provides the findings for the most cited documents globally.
As seen in Table 2, the top 10 most cited studies on the application of advanced artificial intelligence tools in the field of Fuzzy Logic are, respectively; “MELLIT A, 2008, PROG ENERGY COMBUST SCI”, “MELLIT A, 2009, RENEWABLE SUSTAINABLE ENERGY REV”, “BOSE BK, 1994, PROC IEEE”, “BOSE BK, 2017, PROC IEEE”, “PIMENOV DY, 2023, J INTELL MANUF”, “CHENG C-H, 2010, INF SCI”, “HANSON III CW, 2001, CRIT CARE MED”, “KAUR S, 2020, IEEE ACCESS”, “CARRILLO-PEREZ F, 2022, J ESTHETIC RESTORATIVE DENT” and “MOHAGHEGH SD, 2005, JPT J PET TECHNOL”. It is seen that these studies, which are cited globally and are extremely valuable in the field, started to be published in 2008 and continued until 2023. It was determined that the most cited researcher globally is “MELLIT A” with 2 diferent documents. It is recommended that researchers who will conduct future studies in this field read the documents published by these authors. In addition, it can be said that the first 10 most cited documents globally will guide researchers and shed light on their work. The analysis of the most cited documents locally is given in Table 3. When the most cited documents at the local level were examined, it was determined that the studies were distributed between the years 2008 and 2023, and “BOSE BK, 2017, PROC IEEE” and “MELLIT A, 2008, PROG ENERGY COMBUST SCI” shared the first place with 5 citations.
The findings obtained from the analysis conducted to determine trending topics in the documents published on the application of advanced artificial intelligence tools in the field of Fuzzy Logic are given in Table 4.
As seen in Table 4, the most frequently used word in published documents on advanced artificial intelligence tools in the field of Fuzzy Logic was determined as “neural networks” ( = 28). Another word most frequently used by the authors in the studies was determined as “expert systems” ( = 20). Other trending topics in the studies were; “fuzzy sets” ( = 13), “knowledge based systems” ( = 7), “decision support systems” ( = 6), “computer vision” ( = 6) and “machine tools”, “fuzzy control”, “bayesian networks” and “problem solving” with 5 frequencies, respectively.
The distribution of published documents on the use of advanced artificial intelligence tools in the field of Fuzzy Logic by year is given in Table 5.
As seen in Table 5, the first studies on the use of advanced artificial intelligence tools in the field of Fuzzy Logic began in 1990 ( = 1). While no publications were found in 1991, only one publication was found in the SCOPUS database in 1992 and 1993. An examination of the findings revealed that the 2020s were the most productive years, quantitatively. While 17 documents were published in the SCOPUS database in 2020, 23 were published in 2021, 27 in 2022 and 2023, 38 in 2024, and 23 in 2025. This number is expected to increase towards the end of 2025. The results indicate that interest in the use of advanced artificial intelligence tools in the field of Fuzzy Logic has gained significance since 2020.
The distribution of the most productive sources in this field, which include documentation on the use of advanced artificial intelligence tools in the field of Fuzzy Logic, is given in Table 6.
As seen in Table 6, the source that published the documents on the use of advanced artificial intelligence tools in the field of Fuzzy Logic the most was determined as “LECTURE NOTES IN COMPUTER SCIENCE (INCLUDING SUBSERIES LECTURE NOTES IN ARTIFICIAL INTELLIGENCE AND LECTURE NOTES IN BIOINFORMATICS)” ( = 6). The other most productive sources, quantitatively, are “LECTURE NOTES IN NETWORKS AND SYSTEMS” ( = 5), “ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING” ( = 3), “HELIYON” ( = 3), “LECTURE NOTES ON DATA ENGINEERING AND COMMUNICATIONS TECHNOLOGIES” ( = 3), “APPLIED SCIENCES (SWITZERLAND)” ( = 2), “ARTIFICIAL INTELLIGENCE: APPROACHES, TOOLS, AND APPLICATIONS” ( = 2), “DYNA (COLOMBIA) ( = 2)”, “EAI/SPRINGER INNOVATIONS IN COMMUNICATION AND COMPUTING” ( = 2) and “ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE” ( = 2). The distribution of the most productive sources by year is visualized in Figure 2.
This study aims to determine the trend of published studies on the application of advanced artificial
intelligence tools in the field of Fuzzy Logic. In this study, where documents published in the SCOPUS
database were analyzed, the bibliometrix technique, one of the bibliometric analysis methods, was
preferred. In the study where 232 documents were examined, it was determined that the published
documents were between the years 1990 and 2025 and that the documents were published in 201 sources.
It was determined that most of the published documents were published in the article document
type. When the most cited studies at the global and local level were examined, it was seen that the
most cited publication at the global level was “MELLIT A, 2008, PROG ENERGY COMBUST SCI”. It
was determined that the most cited studies at the local level were “BOSE BK, 2017, PROC IEEE” and
“MELLIT A, 2008, PROG ENERGY COMBUST SCI”. It was determined that the most trending topic in the
published documents was “neural networks” and then “expert systems”. These findings demonstrate the
importance of AI in energy systems and sustainability studies. These findings are consistent with studies
that demonstrate the capacity of AI to address uncertainty in complex environments in studies such as
Industry 4.0 [