دورية أكاديمية
A comparison of artificial neural networks and random forests to predict native fish species richness in Mediterranean rivers
| العنوان: | A comparison of artificial neural networks and random forests to predict native fish species richness in Mediterranean rivers |
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| المؤلفون: | Olaya Marín, Esther Julia, Martinez-Capel, Francisco, Vezza, Paolo |
| المساهمون: | Universitat Politècnica de València. Instituto de Investigación para la Gestión Integral de Zonas Costeras - Institut d'Investigació per a la Gestió Integral de Zones Costaneres, Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient, Ministerio de Educación y Ciencia, Ministerio de Ciencia e Innovación, Ministerio de Economía y Competitividad, European Commission |
| بيانات النشر: | EDP Sciences |
| سنة النشر: | 2013 |
| المجموعة: | Universitat Politécnica de Valencia: RiuNet / Politechnical University of Valencia |
| مصطلحات موضوعية: | Artificial neural networks, Random forests, Native fish, Species richness, Mediterranean rivers, Réseaux de neurones, Forêts aléatoires, Poissons indigènes, Richesse spécifique, Rivières méditerranéennes, TECNOLOGIA DEL MEDIO AMBIENTE |
| الوصف: | The original publication is available at www.kmaejournal.org ; [EN] Machine learning (ML) techniques have become important to support decision making in management and conservation of freshwater aquatic ecosystems. Given the large number of ML techniques and to improve the understanding of ML utility in ecology, it is necessary to perform comparative studies of these techniques as a preparatory analysis for future model applications. The objectives of this study were (i) to compare the reliability and ecological relevance of two predictive models for fish richness, based on the techniques of artificial neural networks (ANN) and random forests (RF) and (ii) to evaluate the conformity in terms of selected important variables between the two modelling approaches. The effectiveness of the models were evaluated using three performance metrics: the determination coefficient (R2), the mean squared error (MSE) and the adjusted determination coefficient (R2adj) and both models were developed using a k-fold crossvalidation procedure. According to the results, both techniques had similar validation performance (R2 = 68% for RF and R2 = 66% for ANN). Although the two methods selected different subsets of input variables, both models demonstrated high ecological relevance for the conservation of native fish in the Mediterranean region. Moreover, this work shows how the use of different modelling methods can assist the critical analysis of predictions at a catchment scale. ; [FR] Les techniques d’apprentissage automatique (ML) sont devenues importantes pour aider à la décision dans la gestion et la conservation des écosystèmes aquatiques d’eau douce. Étant donné le grand nombre de techniques ML pour améliorer la compréhension de l’utilité des ML en écologie, il est nécessaire de réaliser des études comparatives de ces techniques comme analyse préparatoire pour des applications de modèles futurs. Les objectifs de cette étude étaient : (i) de comparer la fiabilité et la pertinence écologique de deux modèles prédictifs pour la ... |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 1961-9502 |
| العلاقة: | Knowledge and Management of Aquatic Ecosystems; info:eu-repo/grantAgreement/MICINN//CSD2009-00065/ES/Evaluación y predicción de los efectos del cambio global en la cantidad y la calidad del agua en ríos ibéricos/; info:eu-repo/grantAgreement/MEC//CGL2007-66412/ES/EVALUACION DEL POTENCIAL ECOLOGICO DE RIOS REGULADOS POR EMBALSES Y DESARROLLO DE CRITERIOS PARA SU MEJORA SEGUN LA DIRECTIVA MARCO DEL AGUA./; info:eu-repo/grantAgreement/EC/FP7/275577/EU/Environmental River Management: An Innovative Holistic Approach for Mediterranean Streams/; http://dx.doi.org/10.1051/kmae/2013052Test; urn:issn:1961-9502; http://hdl.handle.net/10251/44816Test |
| DOI: | 10.1051/kmae/2013052 |
| الإتاحة: | https://doi.org/10.1051/kmae/2013052Test http://hdl.handle.net/10251/44816Test |
| حقوق: | http://rightsstatements.org/vocab/InC/1.0Test/ ; info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.BA1A51DE |
| قاعدة البيانات: | BASE |
Full Text Finder | تدمد: | 19619502 |
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| DOI: | 10.1051/kmae/2013052 |