Ecological Informatics

Cover -- Contents -- Part I: Introduction -- 1. Ecological Applications of Fuzzy Logic -- 1.1 Fuzzy Sets and Fuzzy Logic -- 1.2 Fuzzy Approach to Ecological Modelling and Data Analysis -- 1.3 Fuzzy Classification: A Fuzzy Clustering Approach -- 1.4 Fuzzy Regionalisation: A Fuzzy Kriging Approach -- 1.5 Fuzzy Knowledge-Based Modelling -- 1.6 Conclusions -- References -- 2. Ecological Applications of Qualitative Reasoning -- 2.1 Introduction -- 2.2 Why Use QR for Ecology? -- 2.3 What is Qualitative Reasoning? -- 2.4 Tools and Software -- 2.5 Examples of QR-based Ecological Modelling -- 2.6 Conclusion -- References -- 3. Ecological Applications of Non-Supervised Artificial Neural Networks -- 3.1 Introduction -- 3.2 How to Compute a Self-Organizing Map (SOM) with an Abundance Dataset? -- 3.3 How to Use a Self-Organizing Map with an Abundance Dataset? -- 3.4 Discussion -- 3.5 Conclusion -- References -- 4. Ecological Applications of Genetic Algorithms -- 4.1 Introduction -- 4.2 Ecology and Ecological Modelling -- 4.3 Genetic Algorithm Design Details -- 4.4 Applications of Genetic Algorithms to Ecological Modelling -- 4.5 Predicting the Future with Genetic Algorithms -- 4.6 The Next Generation: Hybrids Genetic Algorithms -- References -- 5. Ecological Applications of Evolutionary Computation -- 5.1 Introduction -- 5.2 Ecological Modelling -- 5.3 Evolutionary Computation -- 5.4 Ecological Modelling and Evolutionary Algorithms -- 5.5 Conclusion -- References -- 6. Ecological Applications of Adaptive Agents -- 6.1 Introduction -- 6.2 Adaptive Agents Framework -- 6.3 Individual-Based Adaptive Agents -- 6.4 State Variable-Based Adaptive Agents -- 6.5 Conclusions -- Acknowledgements -- References -- 7. Bio-Inspired Design of Computer Hardware by Self-Replicating Cellular Automata -- 7.1 Introduction -- 7.2 Cellular Automata -- 7.3 Von Neumann's Universal Constructor -- 7.4 Self-Replicating Loops -- 7.5 Self-Replication in the Embryonics Project -- 7.6 Conclusions -- Acknowledgements -- References -- Part II: Prediction and Elucidation of Stream Ecosystems -- 8. Development and Application of Predictive River Ecosystem Models Based On Classification Trees and Artificial Neural Networks -- 8.1 Introduction -- 8.2 Study Sites, Data Sources and Modelling Techniques -- 8.3 Results -- 8.4 Discussion -- Acknowledgements -- References -- 9. Modelling Ecological Interrelations in Running Water Ecosystems with Artificial Neural Networks -- 9.1 Introduction -- 9.2 Materials and Methods -- 9.3 Data Exploration with Unsupervised Learning Systems -- 9.4 Correlations and Predictions with Supervised Learning Systems -- 9.5 Assessment of Model Quality and Visualisation Possibilities: Hybrid Networks -- 9.6 Conclusions -- Acknowledgements -- Refe.