Comparison of modelling techniques to predict macroinvertebrate community composition in rivers of Ethiopia
暂无分享,去创建一个
[1] A. E. Greenberg,et al. Standard methods for the examination of water and wastewater : supplement to the sixteenth edition , 1988 .
[2] Christopher J. C. Burges,et al. Geometry and invariance in kernel based methods , 1999 .
[3] A. Spacie,et al. Biological Monitoring of Aquatic Systems , 1994 .
[4] Sovan Lek,et al. Applications of artificial neural networks predicting macroinvertebrates in freshwaters , 2007, Aquatic Ecology.
[5] V. Resh. Multinational, Freshwater Biomonitoring Programs in the Developing World: Lessons Learned from African and Southeast Asian River Surveys , 2007, Environmental management.
[6] Michael Obach,et al. Artificial neural nets and abundance prediction of aquatic insects in small streams , 2006, Ecol. Informatics.
[7] C.J.F. ter Braak,et al. Predicting macro-fauna community types from environmental variables by means of support vector machines , 2005 .
[8] Peter Goethals,et al. Development and Application of Predictive River Ecosystem Models Based on Classification Trees and Artificial Neural Networks , 2003 .
[9] S. Sathiya Keerthi,et al. Improvements to Platt's SMO Algorithm for SVM Classifier Design , 2001, Neural Computation.
[11] M. Barbour,et al. Rapid bioassessment protocols for use in streams and wadeable rivers: periphyton , 1999 .
[12] Heekuck Oh,et al. Neural Networks for Pattern Recognition , 1993, Adv. Comput..
[13] Ian H. Witten,et al. Data mining: practical machine learning tools and techniques with Java implementations , 2002, SGMD.
[14] Sovan Lek,et al. Analysis of macrobenthic communities in Flanders, Belgium, using a stepwise input variable selection procedure with artificial neural networks , 2007, Aquatic Ecology.
[15] Pier Francesco Ghetti,et al. European perspective on biological monitoring , 1994 .
[16] Melissa Parsons,et al. Development of a Standardised Approach to River Habitat Assessment in Australia , 2004, Environmental monitoring and assessment.
[17] Haleh Vafaie,et al. Feature Selection Methods: Genetic Algorithms vs. Greedy-like Search , 2009 .
[18] Michael D. Vose,et al. The simple genetic algorithm - foundations and theory , 1999, Complex adaptive systems.
[19] Pat Langley,et al. Selection of Relevant Features and Examples in Machine Learning , 1997, Artif. Intell..
[20] Wayne Niblack,et al. Feature selection with stochastic complexity , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[21] D. M. Rosenberg,et al. Freshwater biomonitoring and benthic macroinvertebrates. , 1994 .
[22] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .
[23] Saso Dzeroski,et al. Predicting Chemical Parameters of River Water Quality from Bioindicator Data , 2000, Applied Intelligence.
[24] Ivan Bratko,et al. Machine Learning and Data Mining; Methods and Applications , 1998 .
[25] P. Goethals,et al. Use of genetic algorithms to select input variables in decision tree models for the prediction of benthic macroinvertebrates , 2003 .
[26] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[27] Ron Kohavi,et al. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.
[28] Andy P. Dedecker,et al. Decision Tree Models for Prediction of Macroinvertebrate Taxa in the River Axios (Northern Greece) , 2007, Aquatic Ecology.
[29] Peter Goethals,et al. Genetic algorithms for optimisation of predictive ecosystems models based on decision trees and neural networks , 2006 .
[30] John H. Holland,et al. Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .
[31] D. R. Cutler,et al. Effects of sample survey design on the accuracy of classification tree models in species distribution models , 2006 .
[32] Peter Goethals,et al. Multimetric Macroinvertebrate Index Flanders (MMIF) for biological assessment of rivers and lakes in Flanders (Belgium) , 2010 .
[33] Toshihide Ibaraki,et al. Finding Essential Attributes from Binary Data , 2003, Annals of Mathematics and Artificial Intelligence.
[34] Martin Welp. The Use of Decision Support Tools in Participatory River Basin Management , 2001 .
[35] Lucila Ohno-Machado,et al. A greedy algorithm for supervised discretization , 2004, J. Biomed. Informatics.
[36] Dimitri P. Solomatine,et al. Model Induction with Support Vector Machines: Introduction and Applications , 2001 .
[37] Geoff Holmes,et al. Benchmarking Attribute Selection Techniques for Discrete Class Data Mining , 2003, IEEE Trans. Knowl. Data Eng..
[38] Saso Dzeroski,et al. Simultaneous Prediction of Mulriple Chemical Parameters of River Water Quality with TILDE , 1999, PKDD.
[39] M. Gevrey,et al. Review and comparison of methods to study the contribution of variables in artificial neural network models , 2003 .
[40] Sovan Lek,et al. Application Of Artificial Neural Network Models To Analyse The Relationships Between Gammarus pulex L. (Crustacea, Amphipoda) And River Characteristics , 2005, Environmental monitoring and assessment.