Comparing Regression Models with Count Data to Artificial Neural Network and Ensemble Models for Prediction of Generic Escherichia coli Population in Agricultural Ponds Based on Weather Station Measurements
Authors:
- Gonca BuyrukoğluGBGonca Buyrukoğlu
- Selim BuyrukoğluSBSelim Buyrukoğlu
- Zeynal TopalcengizZTZeynal Topalcengiz
- 1 December 2021
- journal article
- research article
- Published by Elsevier in Microbial Risk Analysis
- Vol. 19
Abstract
No abstract availableKeywords
Funding Information
- Muş Alparslan Üniversitesi
This publication has 48 references indexed in Scilit:
- Spatial-temporal variations of microbial water quality in surface reservoirs and canals used for irrigationAgricultural Water Management, 2013
- Crop Classification by Forward Neural Network with Adaptive Chaotic Particle Swarm OptimizationSensors, 2011
- A Fast Learning Algorithm for Deep Belief NetsNeural Computation, 2006
- Modeling Count Data with Excess ZeroesSociological Methods & Research, 2003
- Ensembling neural networks: Many could be better than allArtificial Intelligence, 2002
- A neural network approach to identifying non-point sources of microbial contaminationWater Research, 1999
- Zero-Inflated Poisson Regression, with an Application to Defects in ManufacturingTechnometrics, 1992
- Specification and testing of some modified count data modelsJournal of Econometrics, 1986
- Estimating the Dimension of a ModelThe Annals of Statistics, 1978
- A new look at the statistical model identificationIEEE Transactions on Automatic Control, 1974