Journal of Robotics, Networking and Artificial Life

ISSN (Online):
2352-6386
ISSN (Print):
2405-9021
Editor(s)-in-Chief:

Masanori Sugisaka

Indexed in:
  • Web of Science - ESCI
  • Scopus (CiteScore: 0.07)
  • Directory of Open Access Journals (DOAJ)
  • Subject: dblp computer science bibliography
  • General: Ulrichsweb, Google Scholar
  • Local: CNKI, Wanfang Data

The Journal of Robotics, Networking and Artificial Life is a peer reviewed journal publishing original research articles and reviews on the development of new technologies in the fields of robotics, networking and artificial life. Read full Aims & Scope

This is an open access journal, i.e. all articles are immediately and permanently free to read, download, copy & distribute. The journal is published under the CC BY-NC 4.0 user license which defines the permitted 3rd-party reuse of its articles. To publish an open access article in this journal, Authors are requested to pay an Article Publication Charge (APC) of EUR 850 per accepted paper. For details on eligibility for APC waivers or discounts, please refer to our APC Waivers and Discounts policy. Submission of articles is free of charge.

For any questions about this publication, please contact our publishing team.

Journal Metrics

Impact Factor
N/A (ESCI only)
5-Year Impact Factor
N/A (ESCI only)
Immediacy Index
N/A (ESCI only)
CiteScore
0.07
Source-Normalized Impact/Paper
TBC (June 2022)
SCImago Journal Rank
TBC (June 2022)
Field-Weighted Citation Impact
TBC (June 2022)
Eigenfactor
0.00015
Article Influence
N/A (ESCI only)
Total Citations (Scopus data)
138
Cited Half-Life
N/A
Citing Half-Life
N/A
Total Downloads
198,045
Average Publication Speed
34.3 weeks
Acceptance Rate
37.0%

Tuning Suitable Features Selection using Mixed Waste Classification Accuracy

Hassan Mehmood Khan, Norrima Mokhtar, Heshalini Rajagopal, Anis Salwa Mohd Khairuddin, Wan Amirul Bin Wan Mohd Mahiyidin, Noraisyah Mohamed Shah, Raveendran Paramesran
Volume 8, Issue 4, March 2022, Pages 298-303

Chinese Traditional Color Harmony Inheritance Method for High-speed Railway

Liangyu Shi, Wei Pei, Jinfeng Li, Kazunori Miyata, Siqun Ma, Haoran Xie
Volume 8, Issue 4, March 2022, Pages 304-311

RETRACTION: Design of an Optimized GMV Controller based on Data-Driven Approach

Liying Shi, Zhe Guan, Toru Yamamoto
In Press, Uncorrected Proof, Available Online: 29 December 2021

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