Evidence map›Paper›PMID 37915363›Full record

ReviewInnovation (Cambridge (Mass.))2023

Toward parallel intelligence: An interdisciplinary solution for complex systems.

Yong Zhao, Zhengqiu Zhu, Bin Chen, Sihang Qiu, Jincai Huang, Xin Lu, Weiyi Yang, Chuan Ai, Kuihua Huang, Cheng He and 3 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Innovation (Cambridge (Mass.)), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Yong ZhaoCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, China.
Zhengqiu ZhuCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, China.
Bin ChenCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, China.
Sihang QiuCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, China.
Jincai HuangCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, China.
Xin LuCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, China.
Weiyi YangCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, China.
Chuan AiCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, China.
Kuihua HuangCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, China.
Cheng HeShanghai Institute of Infectious Disease and Biosecurity, Shanghai 200032, China.
Yucheng JinDepartment of Computer Science, Hong Kong Baptist University, Hong Kong, China.
Zhong LiuCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, China.
Fei-Yue WangState Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The growing complexity of real-world systems necessitates interdisciplinary solutions to confront myriad challenges in modeling, analysis, management, and control. To meet these demands, the parallel systems method rooted in the artificial systems, computational experiments, and parallel execution (ACP) approach has been developed. The method cultivates a cycle termed parallel intelligence, which iteratively creates data, acquires knowledge, and refines the actual system. Over the past two decades, the parallel systems method has continuously woven advanced knowledge and technologies from various disciplines, offering versatile interdisciplinary solutions for complex systems across diverse fields. This review explores the origins and fundamental concepts of the parallel systems method, showcasing its accomplishments as a diverse array of parallel technologies and applications while also prognosticating potential challenges. We posit that this method will considerably augment sustainable development while enhancing interdisciplinary communication and cooperation.

Identifiers

PMID37915363
PMCPMC10616416

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.