Mapping sunflower yield as affected by Ridolfia segetum patches and elevation by applying evolutionary product unit neural networks to remote sensed data

Authors:
P. A. Gutiérrez;F. López-Granados;J. M. Peña-Barragán;M. Jurado-Expósito;M. T. Gómez-Casero;C. Hervás-Martínez
Affiliations:
Institute for Sustainable Agriculture, C.S.I.C., 14080 Cordoba, Spain;Institute for Sustainable Agriculture, C.S.I.C., 14080 Cordoba, Spain;Institute for Sustainable Agriculture, C.S.I.C., 14080 Cordoba, Spain;Institute for Sustainable Agriculture, C.S.I.C., 14080 Cordoba, Spain;Institute for Sustainable Agriculture, C.S.I.C., 14080 Cordoba, Spain;Department of Computing and Numerical Analysis, University of Cordoba, Campus de Rabanales, 14071 Cordoba, Spain
Venue:
Computers and Electronics in Agriculture
Year:
2008

Citing 16
Cited 7

Product units: a computationally powerful and biologically plausible extension to backpropagation networks

Neural Computation
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)

Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Evolutionary computation: toward a new philosophy of machine intelligence

Evolutionary computation: toward a new philosophy of machine intelligence
The nature of statistical learning theory

The nature of statistical learning theory
Comparison of genetic algorithms, random restart and two-opt switching for solving large location-allocation problems

Computers and Operations Research - Special issue: artificial intelligence, evolutionary programming and operations research
Training Product Unit Neural Networks with Genetic Algorithms

IEEE Expert: Intelligent Systems and Their Applications
On the complexity of computing and learning with multiplicative neural networks

Neural Computation
Evolutionary product unit based neural networks for regression

Neural Networks
JCLEC: a Java framework for evolutionary computation

Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue (pp 315-357) "Ordered structures in many-valued logic"
Empirical investigation of the benefits of partial lamarckianism

Evolutionary Computation
Artificial neural networks to predict corn yield from Compact Airborne Spectrographic Imager data

Computers and Electronics in Agriculture
Hybridization of evolutionary algorithms and local search by means of a clustering method

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
COVNET: a cooperative coevolutionary model for evolving artificial neural networks

IEEE Transactions on Neural Networks
Pruning algorithms-a survey

IEEE Transactions on Neural Networks
An evolutionary algorithm that constructs recurrent neural networks

IEEE Transactions on Neural Networks
Use of a quasi-Newton method in a feedforward neural network construction algorithm

IEEE Transactions on Neural Networks

Logistic regression product-unit neural networks for mapping Ridolfia segetum infestations in sunflower crop using multitemporal remote sensed data

Computers and Electronics in Agriculture
A logistic radial basis function regression method for discrimination of cover crops in olive orchards

Expert Systems with Applications: An International Journal
Original paper: Early detection and classification of plant diseases with Support Vector Machines based on hyperspectral reflectance

Computers and Electronics in Agriculture
Hybrid artificial neural networks: models, algorithms and data

IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Parameter estimation of q-Gaussian Radial Basis Functions Neural Networks with a Hybrid Algorithm for binary classification

Neurocomputing
A multi-objective neural network based method for cover crop identification from remote sensed data

Expert Systems with Applications: An International Journal
Ordinal classification using hybrid artificial neural networks with projection and kernel basis functions

HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

Recent advances in remote sensing technology have triggered the need for highly flexible modelling methods to estimate several crop parameters in precision farming. The aim of this work was to determine the potential of evolutionary product unit neural networks (EPUNNs) for mapping in-season yield and forecasting systems of sunflower crop in a natural weed-infested farm. Aerial photographs were taken at the late vegetative (mid-May) growth stage. Yield, elevation and weed data were combined with multispectral imagery to obtain the dataset. Statistical and EPUNNs approaches were used to develop different yield prediction models. The results obtained using different EPUNN models show that the functional model and the hybrid algorithms proposed provide very accurate prediction compared to other statistical methodologies used to solve that regression problem.