Self-organizing map (SOM) for species distribution modelling of birds species at Kenyir landscape
Identifying which biodiversity species are more dominant than others in any area is a very challenging task. This is because of the abundant of biodiversity species that may become the majority species in any particular region. This situation create a large da...
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| Format: | Article |
| Language: | English |
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Institute of Advanced Engineering and Science (IAES)
2019
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| Online Access: | http://umpir.ump.edu.my/id/eprint/25853/7/Self-organizing%20map%20%28SOM%29%20for%20species%20distribution%20modelling.pdf |
| _version_ | 1796993547816140800 |
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| author | Salwana, Mohamad David, Gertrude Mohd Tajuddin, Abdullah Wan Isni Sofiah, Wan Din Eh Phon, Danakorn Nincarean Ahmad Firdaus, Zainal Abidin |
| author_facet | Salwana, Mohamad David, Gertrude Mohd Tajuddin, Abdullah Wan Isni Sofiah, Wan Din Eh Phon, Danakorn Nincarean Ahmad Firdaus, Zainal Abidin |
| author_sort | Salwana, Mohamad |
| collection | UMP |
| description | Identifying which biodiversity species are more dominant than others in any area is a very challenging task. This is because of the abundant of biodiversity species that may become the majority species in any particular region. This situation create a large dataset with a complex variables to be analysed. Moreover, the responds of organisms and environmental factors are
occurred in a non-linear correlation. The effort to do so is really important in order to conserve the biodiversity of nature. To understand the complex relationships that exist between species distribution and their habitat, we analysed the interactions among bird diversity, spatial distribution and land use types at Kenyir landscape in Terengganu, Malaysia by using artificial neural network
(ANN) method of self-organizing map (SOM) analysis. SOM
performs an unsupervised and non-linear analysis on a complex and large dataset. It is capable to handle the non-linear correlation between organism and environmental factors because SOM identifies clusters and relationships
between variables without the fixed assumptions of linearity or normality. The result suggested that SOM analysis was suited for understanding the relationships between bird species assemblages and habitat characteristics. |
| first_indexed | 2024-03-06T12:35:32Z |
| format | Article |
| id | UMPir25853 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:35:32Z |
| publishDate | 2019 |
| publisher | Institute of Advanced Engineering and Science (IAES) |
| record_format | dspace |
| spelling | UMPir258532019-10-03T07:41:53Z http://umpir.ump.edu.my/id/eprint/25853/ Self-organizing map (SOM) for species distribution modelling of birds species at Kenyir landscape Salwana, Mohamad David, Gertrude Mohd Tajuddin, Abdullah Wan Isni Sofiah, Wan Din Eh Phon, Danakorn Nincarean Ahmad Firdaus, Zainal Abidin QA75 Electronic computers. Computer science QA76 Computer software Identifying which biodiversity species are more dominant than others in any area is a very challenging task. This is because of the abundant of biodiversity species that may become the majority species in any particular region. This situation create a large dataset with a complex variables to be analysed. Moreover, the responds of organisms and environmental factors are occurred in a non-linear correlation. The effort to do so is really important in order to conserve the biodiversity of nature. To understand the complex relationships that exist between species distribution and their habitat, we analysed the interactions among bird diversity, spatial distribution and land use types at Kenyir landscape in Terengganu, Malaysia by using artificial neural network (ANN) method of self-organizing map (SOM) analysis. SOM performs an unsupervised and non-linear analysis on a complex and large dataset. It is capable to handle the non-linear correlation between organism and environmental factors because SOM identifies clusters and relationships between variables without the fixed assumptions of linearity or normality. The result suggested that SOM analysis was suited for understanding the relationships between bird species assemblages and habitat characteristics. Institute of Advanced Engineering and Science (IAES) 2019-12 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/25853/7/Self-organizing%20map%20%28SOM%29%20for%20species%20distribution%20modelling.pdf Salwana, Mohamad and David, Gertrude and Mohd Tajuddin, Abdullah and Wan Isni Sofiah, Wan Din and Eh Phon, Danakorn Nincarean and Ahmad Firdaus, Zainal Abidin (2019) Self-organizing map (SOM) for species distribution modelling of birds species at Kenyir landscape. International Journal of Electrical and Computer Engineering (IJECE), 9 (6). pp. 5235-5243. ISSN 2088-8708. (Published) http://ijece.iaescore.com/index.php/IJECE/article/view/20549 http://doi.org/10.11591/ijece.v9i6.pp5235-5243 |
| spellingShingle | QA75 Electronic computers. Computer science QA76 Computer software Salwana, Mohamad David, Gertrude Mohd Tajuddin, Abdullah Wan Isni Sofiah, Wan Din Eh Phon, Danakorn Nincarean Ahmad Firdaus, Zainal Abidin Self-organizing map (SOM) for species distribution modelling of birds species at Kenyir landscape |
| title | Self-organizing map (SOM) for species distribution modelling of birds species at Kenyir landscape |
| title_full | Self-organizing map (SOM) for species distribution modelling of birds species at Kenyir landscape |
| title_fullStr | Self-organizing map (SOM) for species distribution modelling of birds species at Kenyir landscape |
| title_full_unstemmed | Self-organizing map (SOM) for species distribution modelling of birds species at Kenyir landscape |
| title_short | Self-organizing map (SOM) for species distribution modelling of birds species at Kenyir landscape |
| title_sort | self organizing map som for species distribution modelling of birds species at kenyir landscape |
| topic | QA75 Electronic computers. Computer science QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/25853/7/Self-organizing%20map%20%28SOM%29%20for%20species%20distribution%20modelling.pdf |
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