Comparison of physical characteristics between Rana latouchtii and Rana adenopleura using grey system theory and Artificial Neural Network

Chuang, Tsai-Fu; Chang, Yuan-Hsiou

doi:10.1016/j.ecoleng.2014.03.038

Cited by 11 publications

(8 citation statements)

References 27 publications

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“…MAEs for the fitted and cross-validated models were reported in Appendix 1, Table A1.2. Lower values of MAE indicated a better fit (Chuang and Chang 2014).…”

Section: Statistical Analysesmentioning

confidence: 98%

Within-scale and cross-scale interaction effects of temperature and human socioeconomic conditions on avian abundance

Chaudhary¹,

Gutzwiller²

2020

ACE

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The interactive effects of climate and human socioeconomic factors on biodiversity in the Anthropocene may be studied most effectively from a social-ecological perspective. Climate can affect avian abundance, and socioeconomics may affect the human propensity to contribute to conservation. Yet, little is known about how these two factors interact to affect species. We assessed the relative influence of within-scale (landscape) and cross-scale (region-landscape) interaction effects of breeding-season temperature and four socioeconomic variables (percent female, percent college educated, median age, and median income) on the relative abundance of eight forest bird species in the Eastern Temperate Forest Ecoregion of North America. We used negative binomial regression to model relative abundance over three years. Akaike's Information Criterion for small sample sizes (AICc) was used to rank a set of nine a priori models for each combination of species and socioeconomic variable. Of the 32 best-supported models, seven included informative within-scale interactions and three additional models included informative cross-scale interactions, indicating that the relationships between species' relative abundance and socioeconomic variables varied for different levels of temperature. Our results suggest that interactions were generally less influential than were climate, socioeconomic, and habitat variables. Distinct responses to interactions were not evident between habitat groups or between wintering groups. Interactions between human socioeconomic variables and breeding-season temperature at different spatial scales can affect forest bird abundance in species-specific ways. Ignoring the effects of interactions on broad-scale patterns of avian abundance may result in misleading interpretations about additive effects and, consequently, ineffective use of limited conservation resources. Effets interactifs dans l'échelle et inter-échelles entre la température et les conditions socioéconomiques humaines sur l'abondance de la faune aviaire RÉSUMÉ. Les effets interactifs du climat et des facteurs socioéconomiques humains sur la biodiversité au cours de la période Anthropocène peuvent être étudiés particulièrement efficacement du point de vue socio-écologique. Le climat peut affecter l'abondance de la faune aviaire et les aspects socioéconomiques peuvent influer sur la propension humaine à contribuer à la conservation. Pourtant, on ne sait que peu de choses sur la manière dont ces deux facteurs interagissent pour affecter les espèces. Nous avons évalué l'influence relative des effets des interactions dans l'échelle (paysage) et horst-échelle (région-paysage) de la température pendant la saison de reproduction et de quatre variables socioéconomiques (pourcentage de femmes, pourcentage de diplômés universitaires, âge moyen et revenu médian) sur l'abondance relative de huit espèces d'oiseaux forestiers dans l'écorégion forestière tempérée de l'Est de l'Amérique du Nord. Nous avons utilisé la régression binomiale négative pour modéli...

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“…MAEs for the fitted and cross-validated models were reported in Appendix 1, Table A1.2. Lower values of MAE indicated a better fit (Chuang and Chang 2014).…”

Section: Statistical Analysesmentioning

confidence: 98%

Within-scale and cross-scale interaction effects of temperature and human socioeconomic conditions on avian abundance

Chaudhary¹,

Gutzwiller²

2020

ACE

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“…Among the various statistical approaches for prediction (e.g., Kuhn and Johnson 2016), some machine-learning methods (e.g., multivariate adaptive regression splines, neural networks, support vector machines, and classification and regression trees) offer promise for uncovering complex relationships in big data and providing superior predictive ability without overfitting 22 the data (Lantz 2015). Prediction uncertainties for models can be characterized using confidence intervals on expected (mean) values of the response variable and on metrics of prediction accuracy (Chuang and Chang 2014;Hauduc et al 2015). To judge whether an RCI effect is meaningful in a practical sense (e.g., biologically, physically, or socially important), and therefore whether management action is warranted, recreation ecologists will need to estimate RCI effect sizes (see Neter et al 1989;Gutzwiller et al 2010).…”

Section: Study Design and Analytical Considerationsmentioning

confidence: 99%

Understanding and managing the interactions of impacts from nature-based recreation and climate change

Monz

Gutzwiller

Hausner

et al. 2020

Ambio

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“…In the light of the above, this paper puts forward an evaluation system for the adaptive teaching ability of college art teachers, and creates an evaluation model for the said ability based on the grey relational analysis (GRA) [23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Evaluation Model of Adaptive Teaching Ability of College Art Teachers

Kong

2020

Int. J. Emerg. Technol. Learn.

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The existing evaluation models for the teaching ability of college art teachers are unadaptable, unsystematic and incomplete. To solve these problems, this paper puts forward a novel model to evaluate the adaptive teaching ability of college art teachers. Firstly, the teaching demand of college art teachers was analyzed in the knowledge age, highlighting the necessity to evaluate the adaptive teaching ability of college art teachers. Next, an evaluation system was established for the adaptive teaching ability of college art teachers in the knowledge age, and different types of evaluation indices were identified. On this basis, the grey relational analysis (GRA) was introduced to build an evaluation model for the adaptive teaching ability of college art teachers. The GRA-based evaluation model enjoys good operability and feasibility. To sum up, this paper fully integrates the evaluation system and evaluation model for the adaptive teaching ability of college art teachers. The research results have great significance in terms of theoretical innovations and practical applications.

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Comparison of physical characteristics between Rana latouchtii and Rana adenopleura using grey system theory and Artificial Neural Network

Cited by 11 publications

References 27 publications

Within-scale and cross-scale interaction effects of temperature and human socioeconomic conditions on avian abundance

Within-scale and cross-scale interaction effects of temperature and human socioeconomic conditions on avian abundance

Understanding and managing the interactions of impacts from nature-based recreation and climate change

Evaluation Model of Adaptive Teaching Ability of College Art Teachers

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