Using Self-organizing Map in a Computerized Decision Support System

Sirola, Miki; Lampi, Golan; Parviainen, Jukka

doi:10.1007/978-3-540-30499-9_20

Cited by 9 publications

(8 citation statements)

References 2 publications

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“…During the aforesaid training, we used a ''mask'' function to assign a null weight to the breeding parameters, whereas environmental variables were assigned a weight of 1 so that the ordination process was based on the environmental variables only. In addition, setting the mask value to zero for a given component removes the effect of that component on organization (Vesanto et al 2000;Vesanto and Hollmen 2003;Sirola et al 2004;Raivio 2006). The values for breeding parameters were thus visualized on the SOM previously trained with environmental variables only.…”

Section: Data Analysis and Modeling Proceduresmentioning

confidence: 99%

Using self-organizing maps to investigate environmental factors regulating colony size and breeding success of the White Stork (Ciconia ciconia)

et al. 2012

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We studied variations in the size of breeding colonies and in breeding performance of White Storks Ciconia ciconia in 2006-2008 in northeast Algeria. Each colony site was characterized using 12 environmental variables describing the physical environment, land-cover categories, and human activities, and by three demographic parameters: the number of breeding pairs, the number of pairs with chicks, and the number of fledged chicks per pair. Generalized linear mixed models and the self-organizing map algorithm (SOM, neural network) were used to investigate effects of biotic, abiotic, and anthropogenic factors on demographic parameters and on their relationships. Numbers of breeding pairs and of pairs with chicks were affected by the same environmental factors, mainly anthropogenic, which differed from those affecting the number of fledged chicks per pair. Numbers of fledged chicks per pair was not affected by colony size or by the number of nests with chicks. The categorization of the environmental variables into natural and anthropogenic, in connection with demographic parameters, was relevant to detect factors explaining variation in colony size and breeding parameters. The SOM proved a relevant tool to help determine actual dynamics in White Stork colonies, and thus to support effective conservation decisions at a regional scale. Keywords White Stork Á Ciconia ciconia Á Algeria Á Breeding performance Á Colony site Á Conservation Zusammenfassung Welche Umweltfaktoren regulieren Koloniegröße und Bruterfolg beim Weißstorch Ciconia ciconia?-der Einsatz von Selbstorganisierenden Karten Untersucht wurden Unterschiede in Brutkoloniestärke und Bruterfolg bei Weißstörchen Ciconia ciconia in Nordostalgerien, in den Jahren von 2006-2008. Jede Kolonie wurde anhand von zwölf Umweltvariablen charakterisiert, welche Auskunft über physische Umweltbedingungen, Landbedeckung und menschlichen Einfluss gaben, sowie anhand von drei demografischen Parametern: der Anzahl der Brutpaare, der Anzahl von Paaren mit Küken und der Anzahl flügger Junge pro Paar. Es wurden Generalisierte Lineare Gemischte Modelle und der Selbstorganisierende Karten-Algorithmus (Self-Organising Map, SOM, ein neuronales Netz) angewendet, um die Wirkung biotischer, abiotischer und anthropogener Faktoren auf die demografischen Parameter und die Beziehungen zwischen diesen zu untersuchen. Die Anzahl der Brutpaare und die der Paare mit Küken wurden von denselben (hauptsächlich anthropogenen) Umweltfaktoren beeinflusst. Dagegen wurde die Communicated by P. H. Becker.

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Section: Data Analysis and Modeling Proceduresmentioning

confidence: 99%

Using self-organizing maps to investigate environmental factors regulating colony size and breeding success of the White Stork (Ciconia ciconia)

et al. 2012

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“…During the training, we used a mask function to give a null weight to the five physical variables, whereas biological variables were given a weight of 1 so that the ordination process was based on the 28 invertebrate taxa only (Compin and Ce´re´ghino 2007). Setting mask value to 0 for a given component removes the effect of that component on organization (Sirola et al 2004). …”

Section: Modeling Proceduresmentioning

confidence: 99%

Ants mediate the structure of phytotelm communities in an ant‐garden bromeliad

Céréghino

Leroy

Déjean

et al. 2010

Ecology

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Abstract. The main theories explaining the biological diversity of rain forests often confer a limited understanding of the contribution of interspecific interactions to the observed patterns. We show how two-species mutualisms can affect much larger segments of the invertebrate community in tropical rain forests. Aechmea mertensii (Bromeliaceae) is both a phytotelm (plant-held water) and an ant-garden epiphyte. We studied the influence of its associated ant species (Pachycondyla goeldii and Camponotus femoratus) on the physical characteristics of the plants, and, subsequently, on the diversity of the invertebrate communities that inhabit their tanks. As dispersal agents for the bromeliads, P. goeldii and C. femoratus influence the shape and size of the bromeliad by determining the location of the seedling, from exposed to partially shaded areas. By coexisting on a local scale, the two ant species generate a gradient of habitat conditions in terms of available resources (space and food) for aquatic invertebrates, the diversity of the invertebrate communities increasing with greater volumes of water and fine detritus. Two-species mutualisms are widespread in nature, but their influence on the diversity of entire communities remains largely unexplored. Because macroinvertebrates constitute an important part of animal production in all ecosystem types, further investigations should address the functional implications of such indirect effects.

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“…During the training, we used a mask function to give a null weight to the four biological variables (crayfish occurrences), whereas environmental variables were given a weight of 1 so that the ordination process was based on the eight environmental variables only (Compin & Céréghino 2007). Setting mask value to zero for a given component removed the effect of that component on organization (Sirola et al 2004). The occurrence probability of each crayfish species in a given area in the form of the connection intensity was visualized on the SOM map in grey scale, and therefore allowed us: (1) to analyse the effect of each environmental variable on the patterning input dataset (sites), and (2) to predict the occurrence probability of each species in areas (i.e.…”

Section: Modelling Proceduresmentioning

confidence: 99%

Patterning the distribution of threatened crayfish and their exotic analogues using self-organizing maps

et al. 2010

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International audienceAbility to demonstrate statistical patterns of distribution by threatened species and by their potential competitors will determine success in forecasting locations at greatest risk, and ability to target management efforts. A self organizing map algorithm (SOM) was used to derive probabilities of presence of native (Austropotamobius pallipes) and exotic (Orconectes limosus, Pacifastacus leniusculus and Procambarus clarkii) crayfish species with respect to physical and landcover variables in a large stream system, using a simple presence-absence data set of species. Crayfish were sampled at 128 sites representing 86 rivers. The probability of occurrence of the native species increased at higher elevations above sea level and lower temperatures; populations appeared to be mostly confined to headwater streams where exotic competitors were unable to with stand the colder conditions. The distribution of exotic species was correlated with anthropogenic factors, such as the degree of urbanization and agricultural land area. Complementary modelling tools, such as GIS and SOMs, can help to maximize the information extracted from available data in the context of biological conservation

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Using Self-organizing Map in a Computerized Decision Support System

Cited by 9 publications

References 2 publications

Using self-organizing maps to investigate environmental factors regulating colony size and breeding success of the White Stork (Ciconia ciconia)

Using self-organizing maps to investigate environmental factors regulating colony size and breeding success of the White Stork (Ciconia ciconia)

Ants mediate the structure of phytotelm communities in an ant‐garden bromeliad

Patterning the distribution of threatened crayfish and their exotic analogues using self-organizing maps

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