Recent Applications of Artificial Neural Networks in Forest Resource Management: An Overview
暂无分享,去创建一个
[1] Daniel Z. Sui,et al. Recent Applications of Neural Networks for Spatial Data Handling , 1994 .
[2] Rattan Lal,et al. Predicting soil carbon in Mollisols using neural networks. , 1998 .
[3] P. Atkinson,et al. Introduction Neural networks in remote sensing , 1997 .
[4] Duc Truong Pham. Neural Networks In Engineering , 1970 .
[5] Odile Peyron,et al. Climatic Reconstruction in Europe for 18,000 YR B.P. from Pollen Data , 1998, Quaternary Research.
[6] Witold F. Krajewski,et al. Rainfall forecasting in space and time using a neural network , 1992 .
[7] Jon Atli Benediktsson,et al. Neural Network Approaches Versus Statistical Methods in Classification of Multisource Remote Sensing Data , 1989, 12th Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium,.
[8] W S McCulloch,et al. A logical calculus of the ideas immanent in nervous activity , 1990, The Philosophy of Artificial Intelligence.
[9] George F. Hepner,et al. Application of an artificial neural network to landcover classification of thematic mapper imagery , 1990 .
[10] William D. Batchelor,et al. Development of a neural network for soybean rust epidemics , 1997 .
[11] G. Gertner,et al. Modeling red pine tree survival with an artificial neural network , 1991 .
[12] Holger R. Maier,et al. Use of artificial neural networks for modelling cyanobacteria Anabaena spp. in the River Murray, South Australia , 1998 .
[13] F. Recknagel,et al. Artificial neural network approach for modelling and prediction of algal blooms , 1997 .
[14] David E. Rumelhart,et al. Predicting the Future: a Connectionist Approach , 1990, Int. J. Neural Syst..
[15] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[16] P. D. Heermann,et al. Classification of multispectral remote sensing data using a back-propagation neural network , 1992, IEEE Trans. Geosci. Remote. Sens..
[17] Bobby R. Hunt,et al. Extraction of shoreline features by neural nets and image processing , 1991 .
[18] Robert J. Marks,et al. Inversion Of Snow Parameters From Passive Microwave Remote Sensing Measurements By A Neural Network Trained With A Multiple Scattering Model , 1991, [Proceedings] IGARSS'91 Remote Sensing: Global Monitoring for Earth Management.
[19] V. Prybutok,et al. A neural network model forecasting for prediction of daily maximum ozone concentration in an industrialized urban area. , 1996, Environmental pollution.
[20] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .
[21] Heekuck Oh,et al. Neural Networks for Pattern Recognition , 1993, Adv. Comput..
[22] Robert F. Cromp,et al. Automatic labeling and characterization of objects using artificial neural networks , 1989 .
[23] P. Gong,et al. Mapping Ecological Land Systems and Classification Uncertainties from Digital Elevation and Forest-Cover Data Using Neural Networks , 1996 .
[24] F. Tangang,et al. Forecasting ENSO Events: A Neural Network–Extended EOF Approach. , 1998 .
[25] Yaqiu Jin,et al. Biomass retrieval from high-dimensional active/passive remote sensing data by using artificial neural networks , 1997 .
[26] A Comparison Of Neural Network And Expert System Methods For Analysis Of Remotely-sensed Imagery , 1992, [Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium.
[27] G. Z. Gertner,et al. Modeling individual tree survival probability with a random optimization procedure: an artificial neural network approach , 1995 .
[28] H. Maier,et al. The Use of Artificial Neural Networks for the Prediction of Water Quality Parameters , 1996 .
[29] G. O. Moe,et al. Multispectral image-processing with a three-layer backpropagation network , 1989, International 1989 Joint Conference on Neural Networks.
[30] George Z. Gertner,et al. Using a Parallel Distributed Processing System to Model Individual Tree Mortality , 1991 .
[31] J. Zhou,et al. Using Genetic Learning Neural Networks for Spatial Decision Making in GIs , 1996 .
[32] Robert M. Pap,et al. Handbook of neural computing applications , 1990 .
[33] H. R. Gimblett,et al. Applying neural networks to vegetation management plan development , 1997 .
[34] Scott E. Decatur,et al. Application of neural networks to terrain classification , 1989, International 1989 Joint Conference on Neural Networks.
[35] H. M. Rauscher,et al. Enhancing the Scientific Process with Artificial Intelligence: Forest Science Applications , 1991 .
[36] George L. Ball,et al. Neural network architectures for monitoring and stimulating changes in forest resource management , 1995 .
[37] V. E. Derr,et al. Prediction of El Nino events in the Pacific by means of neural networks , 1995 .
[38] Kevin Swingler,et al. Applying neural networks - a practical guide , 1996 .
[39] Peng Gong. Integrated Analysis of Spatial Data from Multiple Sources: An Overview , 1994 .
[40] David Haussler,et al. What Size Net Gives Valid Generalization? , 1989, Neural Computation.
[41] Kamal Sarabandi,et al. Application of an Artificial Neural Network in Canopy Scattering Inversion , 1992, [Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium.
[42] Geoffrey E. Hinton,et al. Learning representations of back-propagation errors , 1986 .
[43] George Z. Gertner,et al. A framework for uncertainty assessment of mechanistic forest growth models: a neural network example , 1997 .
[44] J.H.M. Wösten,et al. Testing an Artificial Neural Network for Predicting Soil Hydraulic Conductivity , 1996 .
[45] R N Coulson,et al. Artificial intelligence and natural resource management. , 1987, Science.
[46] X. H. Zhang,et al. Application of neural networks to identifying vegetation types from satellite images , 1997 .
[47] F. Verdenius,et al. Process models for neural network applications in agriculture , 1997 .
[48] A. Ishimaru,et al. Surface roughness determination using spectral correlations of scattered intensities and an artificial neural network technique , 1993 .
[49] Harry T. Valentine,et al. A Carbon-balance Model of Stand Growth: a Derivation Employing Pipe-model Theory and the Self-thinning Rule , 1988 .
[50] George F. Hepner,et al. Artificial neural network classification using a minimal training set - Comparison to conventional supervised classification , 1990 .
[51] Suranjan Panigrahi,et al. Artificial neural network models of wheat leaf wetness , 1997 .
[52] D. E. Rumelhart,et al. chapter Parallel Distributed Processing, Exploration in the Microstructure of Cognition , 1986 .
[53] William W. Hsieh,et al. Forecasting the equatorial Pacific sea surface temperatures by neural network models , 1997 .
[54] Daniel L. Civco,et al. Artificial Neural Networks for Land-Cover Classification and Mapping , 1993, Int. J. Geogr. Inf. Sci..
[55] I. Dimopoulos,et al. Application of neural networks to modelling nonlinear relationships in ecology , 1996 .