| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Engineering and Technology | 139 | 114 | 193 | 38 |
| Computer Science | 374 | 30 | 38 | 16 |
The topics of Artificial intelligence, Structural engineering, Algorithm, Operations research and Mathematical optimization are the focal point of discussions in the journal. It holds forums on Artificial intelligence that merges themes from other disciplines such as Machine learning, Computer vision and Pattern recognition. Structural engineering studies presented include Finite element method and Structural health monitoring.
Mathematical optimization research presented is mostly focused on the subject of Genetic algorithm. The Artificial neural network study featured in it draws parallels with the field of Data mining.
The most cited articles tackle a plethora of topics, such as Artificial intelligence, Structural engineering, Artificial neural network, Structural health monitoring and Algorithm. Issues in Artificial intelligence were discussed in the journal papers, taking into consideration concepts from other disciplines like Computer vision and Pattern recognition. The journal publications deal with Algorithm in conjunction with Mathematical optimization and similar fields in Operations research and Optimal design.
Computer-aided Civil and Infrastructure Engineering aims to foster the development of research in Artificial intelligence, Computer vision, Structural engineering, Pattern recognition and Algorithm. It focused on Artificial intelligence research but expanded to cover Machine learning. The work on Computer vision addressed in it expands to the thematically related Surface (mathematics).
Bridge (interpersonal) is a key component of Structural engineering research discussed in Computer-aided Civil and Infrastructure Engineering. Computer-aided Civil and Infrastructure Engineering dives deep in exploring the relationship between the study of Pattern recognition and Damage detection.
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 Computer-aided Civil and Infrastructure Engineering (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 Computer-aided Civil and Infrastructure Engineering (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, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 26.32% were posted by at least one author from the top 10 institutions publishing in the journal. Another 16.45% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 18.42% of all publications and 38.82% 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.
Chaobo Zhang;Chih‐chen Chang;Maziar Jamshidi
(2020)Yongjia Xu;Xinzheng Lu;Barbaros Cetiner;Ertugrul Taciroglu
(2021)Yunpeng Wu;Yunpeng Wu;Yong Qin;Yu Qian;Feng Guo
(2021)Mingzhu Wang;Jack C. P. Cheng
(2020)Yang Zhang;Yang Zhang;Ka-Veng Yuen
(2021)Neetesh Sharma;Armin Tabandeh;Paolo Gardoni
(2020)Yiming Bie;Jinhua Ji;Xiangyu Wang;Xiangyu Wang;Xiaobo Qu
(2021)Chen Xiong;Jin Huang;Xinzheng Lu
(2020)Yasutaka Narazaki;Vedhus Hoskere;Tu A. Hoang;Yozo Fujino
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