| Abstract | 第1-8页 |
| Chapter 1 Introduction | 第8-16页 |
| ·Neural networks(NN) | 第8-12页 |
| ·Quantitative structure & activity relationships (QSAR) | 第12-14页 |
| ·Simultaneous determination of the PAHs in environmental samples usingfluorescence spectra | 第14页 |
| ·Consideration about this study | 第14-16页 |
| Chapter 2 Neural Networks (NNs) Theory | 第16-29页 |
| ·Back-propagation neural networks(BPN) | 第16-21页 |
| ·Radial basis function neural networks (RBFN) | 第21-26页 |
| ·General regression neural networks(GRNN) | 第26-29页 |
| Chapter 3 Predictionofn-octanol/waterPartition CoefficientsforPolychlorinated Dibenzo-p-dioxins Using General Regression NeuralNetwork | 第29-40页 |
| ·Experimental | 第29-33页 |
| ·Results and discussion | 第33-39页 |
| ·Conclusions | 第39-40页 |
| Chapter 4 Prediction of the Ah Receptor Binding Affinity(pEC50) ofPolychlorinatedUsingRadialBasisFunction Neural Network(RBFN) | 第40-51页 |
| ·Experimental | 第40-42页 |
| ·Results and discussion | 第42-49页 |
| ·Conclusions | 第49-51页 |
| Chapter 5 Analysis of Polycyclic Aromatic Hydrocarbons (PAHs) in WaterSamples by Synchronous Fluorescence Using Radial Basis FunctionNeural Network (RBFN) | 第51-63页 |
| ·Experimental | 第51-54页 |
| ·Results and discussion | 第54-61页 |
| ·Conclusions | 第61-63页 |
| Chapter 6 Conclusions and Advices | 第63-64页 |
| ·Conclusions | 第63页 |
| ·Advices | 第63-64页 |
| Acknowledgement | 第64-65页 |
| References | 第65-76页 |
| Appendix 1: Papers Published | 第76页 |
