ARTIFICIAL NEURAL NETWORKS APPLIED IN FOREST BIOMETRICS AND MODELING: STATE OF THE ART (JANUARY/2007 TO JULY/2018) Article Swipe
Flávio Chiarello
,
María Teresinha Arns Steiner
,
E. B. de Oliveira
,
Júlio Eduardo Arce
,
Júlio César Ferreira
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1590/01047760201925022626
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1590/01047760201925022626
Artificial Intelligence has been an important support tool in different spheres of activity, enabling knowledge aggregation, process optimization and the application of methodologies capable of solving complex real problems. Despite focusing on a wide range of successful metrics, the Artificial Neural Network (ANN) approach, a technique similar to the central nervous system, has gained notoriety and relevance with regard to the classification of standards, intrinsic parameter estimates, remote sense, data mining and other possibilities. This article aims to conduct a systematic review, involving some bibliometric aspects, to detect the application of ANNs in the field of Forest Engineering, particularly in the prognosis of the essential parameters for forest inventory, analyzing the construction of the scopes, implementation of networks (type ? classification), the software used and complementary techniques. Of the 1,140 articles collected from three research databases (Science Direct, Scopus and Web of Science), 43 articles underwent these analyses. The results show that the number of works within this scope has increased continuously, with 32% of the analyzed articles predicting the final total marketable volume, 78% making use of Multilayer Perceptron Networks (MLP, Multilayer Perceptron) and 63% from Brazilian researchers.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1590/01047760201925022626
- http://www.scielo.br/pdf/cerne/v25n2/2317-6342-cerne-25-02-140.pdf
- OA Status
- diamond
- Cited By
- 10
- References
- 48
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2971635058
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2971635058Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1590/01047760201925022626Digital Object Identifier
- Title
-
ARTIFICIAL NEURAL NETWORKS APPLIED IN FOREST BIOMETRICS AND MODELING: STATE OF THE ART (JANUARY/2007 TO JULY/2018)Work title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-06-01Full publication date if available
- Authors
-
Flávio Chiarello, María Teresinha Arns Steiner, E. B. de Oliveira, Júlio Eduardo Arce, Júlio César FerreiraList of authors in order
- Landing page
-
https://doi.org/10.1590/01047760201925022626Publisher landing page
- PDF URL
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https://www.scielo.br/pdf/cerne/v25n2/2317-6342-cerne-25-02-140.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://www.scielo.br/pdf/cerne/v25n2/2317-6342-cerne-25-02-140.pdfDirect OA link when available
- Concepts
-
Biometrics, State (computer science), Artificial neural network, Computer science, Geography, Artificial intelligence, Forestry, AlgorithmTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
10Total citation count in OpenAlex
- Citations by year (recent)
-
2022: 3, 2021: 6, 2020: 1Per-year citation counts (last 5 years)
- References (count)
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48Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W922142870, https://openalex.org/W2079574800, https://openalex.org/W2218392507, https://openalex.org/W2794415590, https://openalex.org/W2884442040, https://openalex.org/W2748693723, https://openalex.org/W2767851916, https://openalex.org/W1986667872, https://openalex.org/W1963988599, https://openalex.org/W1998048588, https://openalex.org/W2741274520, https://openalex.org/W2071881814, https://openalex.org/W2792322696, https://openalex.org/W2610524947, https://openalex.org/W2091085409, https://openalex.org/W3182449099, https://openalex.org/W1735015910, https://openalex.org/W2045897831, https://openalex.org/W2394716203, https://openalex.org/W2496728541, https://openalex.org/W2090675543, https://openalex.org/W2020691931, https://openalex.org/W2030720783, https://openalex.org/W2530797269, https://openalex.org/W3008663578, https://openalex.org/W161283806, https://openalex.org/W2588248442, https://openalex.org/W2619655716, https://openalex.org/W1996701210, https://openalex.org/W1991563031, https://openalex.org/W2026212992, https://openalex.org/W1999525425, https://openalex.org/W2773578505, https://openalex.org/W2791831799, https://openalex.org/W1862695827, https://openalex.org/W4237814833, https://openalex.org/W2092357153, https://openalex.org/W2289205268, https://openalex.org/W2018061490, https://openalex.org/W1983988574, https://openalex.org/W1498436455, https://openalex.org/W2475095754, https://openalex.org/W2091832726, https://openalex.org/W2566591319, https://openalex.org/W2002966798, https://openalex.org/W2317688426, https://openalex.org/W2115759662, https://openalex.org/W2081843548 |
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