Non-linear variable selection for artificial neural networks using partial mutual information

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Non-linear variable selection for artificial neural networks using partial mutual information is …
instance of (P31):
scholarly articleQ13442814

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P8978DBLP publication IDjournals/envsoft/MayMDF08
P356DOI10.1016/J.ENVSOFT.2008.03.007

P50authorHolger MaierQ57415258
P2093author name stringGraeme C. Dandy
Robert J. May
T.M.K. Gayani Fernando
P433issue10-11
P921main subjectartificial neural networkQ192776
P304page(s)1312-1326
P577publication date2008-10-01
P1433published inEnvironmental Modelling and SoftwareQ15763595
P1476titleNon-linear variable selection for artificial neural networks using partial mutual information
P478volume23

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cites work (P2860)
Q57606579A benchmarking approach for comparing data splitting methods for modeling water resources parameters using artificial neural networks
Q57606615An integrated dynamic modeling framework for investigating the impact of climate change and variability on irrigated agriculture
Q59072132Comparing the Selected Transfer Functions and Local Optimization Methods for Neural Network Flood Runoff Forecast
Q58891889Dimensionality reduction in drought modelling
Q50045859Estimation of effective connectivity using multi-layer perceptron artificial neural network
Q36529786Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks
Q57924243Heuristic Modelling of the Water Resources Management in the Guadalquivir River Basin, Southern Spain
Q59189729Large-scale ocean-atmospheric processes and seasonal rainfall variability in South Australia: accounting for non-linearity and establishing the hierarchy of influence
Q38776218Robust planning of sanitation services in urban informal settlements: An analytical framework
Q58891877Spring drought prediction based on winter NAO and global SST in Portugal
Q57521274Study on Applicability of Conceptual Hydrological Models for Flood Forecasting in Humid, Semi-Humid Semi-Arid and Arid Basins in China
Q61875117Towards better understanding of feature-selection or reduction techniques for Quantitative Structure–Activity Relationship models

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