Title | Neural Nets: Applications in Geography [electronic resource] / edited by Bruce C. Hewitson, Robert G. Crane |
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Imprint | Dordrecht : Springer Netherlands : Imprint: Springer, 1994 |
Connect to | http://dx.doi.org/10.1007/978-94-011-1122-5 |
Descript | XI, 196 p. online resource |
One โ Looks and Uses -- 1.0 Origins and Growth -- 1.1 Conceptual Overview -- 1.2 Neural Net Structures -- 1.3 Implementing the Neural Net -- 1.4 Inevitable Caveats and Cautions -- 1.5 Where Next? -- Two โ Neural Networks and their Applications -- 2.0 Introduction -- 2.1 Neural Network Language and Basic Operation -- 2.2 Multilayer Perceptrons and the Backpropagation of Error Algorithm -- 2.3 Kohonenโs Self-Organizing Feature Maps -- 2.4 Neural Networks and System Identification -- 2.5 Areas of Current Research -- Three โ Neuro Classification of Spatial Data -- 3.0 Towards a Computational Geography -- 3.1 Whither Neuroclassification? -- 3.2 Review of Potential Neuroclassifier Architectures -- 3.3 Competitive Learning Nets -- 3.4 Self-Organizing Map -- 3.5 Adaptive Resonance Theory -- 3.6 Associative Memory Nets -- 3.7 Comparisons With Conventional Classifiers -- 3.8 Kohonenโs Self-Organizing Map -- 3.9 Conclusions -- ChapterChapter Four โ Self Organizing Maps โ Application to Census Data -- 4.0 South African Census Records -- 4.1 Net Classification -- 4.2 Interpretation of the Mapping Surface -- 4.3 Interpretation of Regions in the Mapping โThe โBlackโ Population -- 4.4 Spatial Distribution of the Mapping -- 4.5 Conclusions -- Five - Predicting Snowfall from Synoptic Circulation: A Comparison of Linear Regression and Neural Network Methodologies -- 5.0 Introduction -- 5.1 Data Preparation and Methodology -- 5.2 Principal Component Analysis โ 700 mb Data -- 5.3 SNOTEL Data Preparation -- 5.4 Stepwise Multiple Regression Analyses -- 5.5 Five-Day Smoothed Results -- 5.6 Neural Network Analysis -- 5.7 Conclusions -- Six - Neural Computing and the Aids Pandemic: The Case of Ohio -- 6.0 The AIDS Pandemic, circa, 1993 -- 6.1 Spatiotemporal Neural Forecasting -- 6.2 Neural Forecasting of the AIDS Epidemic -- 6.3 A Sensitivity Analysis -- 6.4 Neural Spatiotemporal Forecasting: Qualified Conclusions -- Seven - Precipitation Controls in Southern Mexico -- 7.0 The Issue -- 7.1 Southern Mexico Precipitation -- 7.2 Climate Representation in the Data Set -- 7.3 Neural Net Design and Training -- 7.4 Neural Net Interpretation-Theory -- 7.5 Neural Net Interpretation โ Implementation -- 7.6 Precipitation Onset -- 7.7 Early Established Summer Rains -- 7.8 Late Summer Precipitation Maximum -- 7.9 Decay of the Summer Rains -- 7.10 Conclusions -- Eight - Classification of Arctic Cloud and Sea Ice Features in Multi-Spectral Satellite Data -- 8.0 Introduction -- 8.1 Cloud Detection and Classification -- 8.2 Cloud Pattern Analysis Using Texture -- 8.3 Discussion -- 8.4 Other Neural Network Applications to Cloud Classification -- 8.5 Sea Ice Fracture Patterns -- 8.6 Neural Network Approach -- 8.7 Conclusions -- Appendix I - Neural Network Resources -- Appendix II - Fortran 77 Listing for Kohonen Self Organizing Map