Weight and Structure Determination Neural Network Aided With Double Pseudoinversion for Diagnosis of Flat Foot Article Swipe
Liangming Chen
,
Zhiguan Huang
,
Yuhe Li
,
Nianyin Zeng
,
Mei Liu
,
Anjie Peng
,
Long Jin
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1109/access.2019.2903634
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1109/access.2019.2903634
Deep learning models often have complicated structures with low computational speed and the requirement of a large amount of storage space, which limits their own practical application on some devices with insufficient computing power. This paper proposes the weight and structure determination neural network aided with double pseudoinversion (WASDNN-DP) that can overcome these shortcomings. First, the model structure, theoretical bases, and the algorithms of WASDNN-DP are given. In the process of constructing the network, the weight matrix between the hidden layer and the output layer is first randomly generated. After the weight matrix between the input layer and the hidden layer is analytically determined, the weight matrix between the hidden layer and the output layer is re-determined by the pseudo-inverse method. Furthermore, in WASDNN-DP, the structure of the neural network is determined by a progressive method. Subsequently, based on two datasets collected from children aged 7-15 years by using smart insoles, the comparative experiments between WASDNN-DP and some other machine learning models are carried out, which illustrate the superiority of the proposed WASDNN-DP in the diagnosis of flat foot.
Related Topics
Concepts
Artificial neural network
Computer science
Layer (electronics)
Matrix (chemical analysis)
Artificial intelligence
Inverse
Power (physics)
Process (computing)
Algorithm
Set (abstract data type)
Pattern recognition (psychology)
Mathematics
Materials science
Programming language
Geometry
Operating system
Physics
Quantum mechanics
Composite material
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2019.2903634
- https://ieeexplore.ieee.org/ielx7/6287639/8600701/08662574.pdf
- OA Status
- gold
- Cited By
- 33
- References
- 45
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2921061144
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2921061144Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/access.2019.2903634Digital Object Identifier
- Title
-
Weight and Structure Determination Neural Network Aided With Double Pseudoinversion for Diagnosis of Flat FootWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-01-01Full publication date if available
- Authors
-
Liangming Chen, Zhiguan Huang, Yuhe Li, Nianyin Zeng, Mei Liu, Anjie Peng, Long JinList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2019.2903634Publisher landing page
- PDF URL
-
https://ieeexplore.ieee.org/ielx7/6287639/8600701/08662574.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://ieeexplore.ieee.org/ielx7/6287639/8600701/08662574.pdfDirect OA link when available
- Concepts
-
Artificial neural network, Computer science, Layer (electronics), Matrix (chemical analysis), Artificial intelligence, Inverse, Power (physics), Process (computing), Algorithm, Set (abstract data type), Pattern recognition (psychology), Mathematics, Materials science, Programming language, Geometry, Operating system, Physics, Quantum mechanics, Composite materialTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
33Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 2, 2023: 7, 2022: 6, 2021: 8Per-year citation counts (last 5 years)
- References (count)
-
45Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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