| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 167 | 76 | 102 | 30 |
| Engineering and Technology | 228 | 81 | 117 | 29 |
The journal mostly deals with topics like Mathematical optimization, Production (economics), Artificial intelligence, Process (engineering) and Artificial neural network. Mathematical optimization research featured in it incorporates concerns from various other topics such as Algorithm and Job shop scheduling, Flow shop scheduling. The journal covers Job shop scheduling research under the subject of Scheduling (computing).
The research on Production (economics) featured in Journal of Intelligent Manufacturing combines topics in other fields like Quality (business), Industrial engineering, Reliability engineering, Manufacturing engineering and Operations research. The work on Artificial intelligence tackled in it brings together disciplines like Machine learning, Data mining, Computer vision and Pattern recognition. The journal investigates Data mining research which frequently intersects with Fuzzy logic.
Journal of Intelligent Manufacturing connects research in Process (engineering) with the related topic of Systems engineering. Journal of Intelligent Manufacturing explores topics in Artificial neural network which can be helpful for research in disciplines like Control engineering and Process (computing). The study on Process (computing) presented in the journal intersects with the topics under Engineering drawing.
The journal papers investigate areas of study like Mathematical optimization, Production (economics), Artificial intelligence, Artificial neural network and Process (engineering). The journal papers explore research in Job shop scheduling and overlapping concepts in Scheduling (production processes) and Heuristics to expand the discourse in Mathematical optimization. While Artificial neural network is the key highlight in the journal articles, thet also covered some subjects on Data mining and Fuzzy logic.
Journal of Intelligent Manufacturing focuses largely on the fields of Artificial intelligence, Process (computing), Production (economics), Process (engineering) and Algorithm. Machine learning, Computer vision and Pattern recognition are some topics wherein Artificial intelligence research discussed in the journal have an impact. The research on Process (computing) tackled can also make contributions to studies in the areas of Artificial neural network and Laser power scaling.
The Artificial neural network study featured in Journal of Intelligent Manufacturing draws parallels with the field of Machining. Production (economics) research presented in Journal of Intelligent Manufacturing encompasses a variety of subjects, including Quality (business), Production line and Reliability engineering. Discussions in the journal are anchored in the subject of Process (engineering) and the similar topic of Industry 4.0.
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 Journal of Intelligent Manufacturing (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 Journal of Intelligent Manufacturing (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, 5.71% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 15.15% were posted by at least one author from the top 10 institutions publishing in the journal. Another 8.23% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 12.12% of all publications and 64.50% 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.
Kendrik Yan Hong Lim;Pai Zheng;Pai Zheng;Chun Hsien Chen
(2020)Unknown
(2022)Xiang Li;Xiang Li;Wei Zhang;Qian Ding;Jian-Qiao Sun
(2020)Wattana Viriyasitavat;Li Da Xu;Zhuming Bi;Assadaporn Sapsomboon
(2020)Chunyang Xia;Chunyang Xia;Zengxi Pan;Joseph Polden;Huijun Li
(2021)Jingchao Jiang;Yi Xiong;Zhiyuan Zhang;David W. Rosen;David W. Rosen
(2020)Ammar H. Elsheikh;Taher A. Shehabeldeen;Taher A. Shehabeldeen;Jianxin Zhou;Ezzat Showaib
(2020)Pai Zheng;Pai Zheng;Xun Xu;Chun-Hsien Chen
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