Self-organising map methods in integrated modelling of environmental and economic systems

Shanmuganathan, Subana; Sallis, Philip; Buckeridge, John S.

doi:10.1016/j.envsoft.2005.04.011

Cited by 38 publications

(14 citation statements)

References 4 publications

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“…While conventional methods might distortion along non-linear relationships (Giraudel and Lek, 2001), SOM is stated to be useful for exploratory data analysis in a multidimensional scale (Shanmuganathan et al, 2006). The SOM method has been already used successfully in potamoplankton ecology (Várbíró et al, 2007;Stankovi c et al, 2012); in fish zonation (Lasne et al, 2007); as well as in diatom research at large spatial scales (Rimet et al, 2004;Park et al, 2006;Stenger-Kovács et al, 2014).…”

Section: Statistical Analysesmentioning

confidence: 99%

A large river (River Loire, France) survey to compare phytoplankton functional approaches: Do they display river zones in similar ways?

Abonyi

Leitão²,

Stanković³

et al. 2014

Ecological Indicators

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Phytoplankton river zonation N:P ratio Si:P ratio River water quality management A B S T R A C T Functional groups of phytoplankton make possible various classifications among taxa and this approach has been receiving a growing scientific interest. We compared three frequently used classifications as possible ecological tools in providing river zones along the large, Continental Atlantic River Loire. The different number of functional groups in each classification was synchronized into six clusters using the Self Organizing Map (SOM) method, which clusters (as river zones where relevant) were then compared in their response to geographical location, hydrological and chemical constraints. Our findings demonstrated that all the three classifications might serve as a rational tool, but at different level of understanding. Only approaches based on fine functional resolution in benthic and planctonic diatoms, as well as in cyanobacteria were able to provide reliable river zones at both whole river, and at spatio-temporal scales. Functional groups of these approaches followed different regional patterns in geographical, physical and chemical constraints, and were useful ecological indicators of natural river longitudinal processes, as well as of human impacts such as damming or agriculture.

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Section: Statistical Analysesmentioning

confidence: 99%

A large river (River Loire, France) survey to compare phytoplankton functional approaches: Do they display river zones in similar ways?

Abonyi

Leitão²,

Stanković³

et al. 2014

Ecological Indicators

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“…The need for better techniques, tools and practices to analyze ecological systems within an integrated framework has never been so great (Shanmuganathan et al 2006). Multi-model approach conditioned on data should thus be preferred.…”

Section: Introductionmentioning

confidence: 99%

Spatial succession modeling of biological communities: a multi-model approach

Zhang

Wei

2008

Environ Monit Assess

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Strong spatial correlation may exist in the spatial succession of biological communities, and the spatial succession can be mathematically described. It was confirmed by our study on spatial succession of both plant and arthropod communities along a linear transect of natural grassland. Both auto-correlation and cross-correlation analyses revealed that the succession of plant and arthropod communities exhibited a significant spatial correlation, and the spatial correlation for plant community succession was stronger than arthropod community succession. Theoretically it should be reasonable to infer a site's community composition from the last site in the linear transect. An artificial neural network for state space modeling (ANNSSM) was developed in present study. An algorithm (i.e., Importance Detection Method (IDM)) for determining the relative importance of input variables was proposed. The relative importance for plant families Gramineae, Compositae and Leguminosae, and arthropod orders Homoptera, Diptera and Orthoptera, were detected and analyzed using IDM. ANNSSM performed better than multivariate linear regression and ordinary differential equation, while ordinary differential equation exhibited the worst performance in the simulation and prediction of spatial succession of biological communities. A state transition probability model (STPM) was proposed to simulate the state transition process of biological communities. STPM performed better than multinomial logistic regression in the state transition modeling. We suggested a novel multi-model framework, i.e., the joint use of ANNSSM and STPM, to predict the spatial succession of biological communities. In this framework, ANNSSM and STPM can be separately used to simulate the continuous and discrete dynamics.

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“…The SOM is a fascinating neural network method that has found increasing interest in water resources applications such as river flow and rainfallrunoff (Hsu et al 2002;Wang 2006), precipitation (Hong et al 2005;Kalteh and Berndtsson 2007), surface water quality (Bowden et al 2002(Bowden et al , 2005a and climate, environment, ecology, etc. (Cereghino et al 2001;Tran et al 2003;Schutze et al 2005;Shanmuganathan et al 2006). Detailed reviews of SOM along with assessments of their application in water resources and hydrology can be found in ASCE (2000b) and Kalteh et al (2008).…”

Section: Introductionmentioning

confidence: 99%

Development of Design Hyetographs for Ungauged Sites Using an Approach Combining PCA, SOM and Kriging Methods

Chen

Lin

Hsu

2011

Water Resour Manage

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A design hyetograph represents the temporal distribution of rainfall intensity associated with a return period. The choice of the design hyetograph will have a significant influence on the shape and peak value of the hydrograph. Hence, the determination of design hyetographs is an important task in the hydrologic designs. In this paper, an approach is proposed to develop design hyetographs for ungauged sites. The proposed approach is composed of four steps: principal component analysis (PCA), self-organizing map (SOM)-based clustering, region delineation, and krigingbased construction. Firstly, PCA is applied to obtain the principal components of the design hyetographs. Then the transformed data resulting from PCA and the three geographic characters of the gauges are used as input data to the SOM, which is applied to group the rain gauges into specific clusters. Thirdly, the regions for these clusters are delineated and then the regions map is made. Finally, the design hyetographs for ungauged sites is constructed by using the kriging method. The proposed approach is applied to estimate the design hyetographs of ungauged sites in Taiwan. For comparison with the proposed approach, three other approaches are executed. Four gauges are treated as ungauged and the three approaches are used to construct the design hyetographs. The results show that accurate estimated design hyetographs can be obtained by the proposed approach. Cross-validation tests further have been performed to examine the stability and the accuracy of these approaches. Again, the results indicate that the proposed approach is more accurate and stable than the other approaches. Overall, the results demonstrate L.-H. Chen et al. that the proposed approach is useful to develop design hyetographs for ungauged sites.

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Self-organising map methods in integrated modelling of environmental and economic systems

Cited by 38 publications

References 4 publications

A large river (River Loire, France) survey to compare phytoplankton functional approaches: Do they display river zones in similar ways?

A large river (River Loire, France) survey to compare phytoplankton functional approaches: Do they display river zones in similar ways?

Spatial succession modeling of biological communities: a multi-model approach

Development of Design Hyetographs for Ungauged Sites Using an Approach Combining PCA, SOM and Kriging Methods

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