Improved Empirical Formula Modeling Method Using Neuro-Space Mapping for Coupled Microstrip Lines.

Shuxia Yan, Fengqi Qian, Chenglin Li, Jian Wang, Xu Wang, Wenyuan Liu

Abstract read

In one paragraph

Article in Micromachines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Shuxia YanSchool of Electronics and Information Engineering, Tiangong University, Tianjin 300387, China.

Fengqi QianSchool of Electronics and Information Engineering, Tiangong University, Tianjin 300387, China.

Chenglin LiSchool of Electronics and Information Engineering, Tiangong University, Tianjin 300387, China.

Jian WangSchool of Microelectronics, Tianjin University, Tianjin 300072, China.ORCID 0000-0003-4361-8946

Xu WangSchool of Microelectronics, Tianjin University, Tianjin 300072, China.ORCID 0000-0003-3155-050X

Wenyuan LiuSchool of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi'an 710021, China.

Funding

China Postdoctoral Science Foundation 2020M680883National Natural Science Foundation of China 62201335Natural Science Foundation of Shaanxi Provincial Department of Education 21JK0548

6 · The paper itself

Abstract

In this paper, an improved empirical formula modeling method using neuro-space mapping (Neuro-SM) for coupled microstrip lines is proposed. Empirical formulas with correction values are used for the coarse model, avoiding a slow trial-and-error process. The proposed model uses mapping neural networks (MNNs), including both geometric variables and frequency variables to improve accuracy with fewer variables. Additionally, an advanced method incorporating simple sensitivity analysis expressions into the training process is proposed to accelerate the optimization process. The experimental results show that the proposed model with its simple structure and an effective training process can accurately reflect the performance of coupled microstrip lines. The proposed model is more compatible than models in existing simulation software.

Indexed as

coupled microstrip linesmapping neural networksmicrowave devicesmodelingoptimization

Identifiers

PMID37630136

DOI10.3390/mi14081600

PMCPMC10456232

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

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.