Contents
Part I Introduction ............................................................. 1
1. Ecological Applications of Fuzzy Logic ................................... 3
1.1 Fuzzy Sets and Fuzzy Logic ................................................................... 3
1.2 Fuzzy Approach to Ecological Modelling and Data Analysis ............... .4
1.3 Fuzzy Classification: A Fuzzy Clustering Approach .............................. 6
1.4 Fuzzy Regionalisation: A Fuzzy Kriging Approach ............................... 9
1.5 Fuzzy Knowledge-Based Modelling ....................................................... 9
1.6 Conclusions ........................................................................................... 12
References ............................................................................................. 12
2. Ecological Applications of Unsupervised Artificial Neural
Networks ..................................................................................... 15
2.1 Introduction ........................................................................................... 15
2.2 How to Compute a Self-Organizing Map (SOM) with an Abundance
Dataset? ................................................................................................ 16
2.2.1
A Dataset for Demonstrations ........................................................ 16
2.2.2
The Self-Organizing Map (SOM) Algorithm ................................ 18
2.3 How to Use a Self-Organizing Map with an Abundance Dataset? ....... 22
2.3.1
Mapping the Stations ..................................................................... 22
2.3.2
Displaying a Variable .................................................................... 24
2.3.3
Displaying an Abiotic Variable ..................................................... 25
2.3.4
Clustering with a SOM .................................................................. 26
2.4 Discussion ............................................................................................. 29
2.5 Conclusion ............................................................................................ 31
References ............................................................................................. 32
3. Ecological Applications of Genetic Aigorithms ..................... 35
3.1 Introduction ........................................................................................... 35
3.2 Ecology and Ecological Modelling ....................................................... 36
3.3 Genetic Algorithm Design Details ........................................................ 38
3.4 Applications of Genetic Algorithms to Ecological Modelling .............. 40
3.5 Predicting the Future with Genetic Algorithms .................................... 43
3.6 The Next Generation: Hybrids Genetic Algorithms ............................. 44
References ............................................................................................. 45
Part I Introduction ............................................................. 1
1. Ecological Applications of Fuzzy Logic ................................... 3
1.1 Fuzzy Sets and Fuzzy Logic ................................................................... 3
1.2 Fuzzy Approach to Ecological Modelling and Data Analysis ............... .4
1.3 Fuzzy Classification: A Fuzzy Clustering Approach .............................. 6
1.4 Fuzzy Regionalisation: A Fuzzy Kriging Approach ............................... 9
1.5 Fuzzy Knowledge-Based Modelling ....................................................... 9
1.6 Conclusions ........................................................................................... 12
References ............................................................................................. 12
2. Ecological Applications of Unsupervised Artificial Neural
Networks ..................................................................................... 15
2.1 Introduction ........................................................................................... 15
2.2 How to Compute a Self-Organizing Map (SOM) with an Abundance
Dataset? ................................................................................................ 16
2.2.1
A Dataset for Demonstrations ........................................................ 16
2.2.2
The Self-Organizing Map (SOM) Algorithm ................................ 18
2.3 How to Use a Self-Organizing Map with an Abundance Dataset? ....... 22
2.3.1
Mapping the Stations ..................................................................... 22
2.3.2
Displaying a Variable .................................................................... 24
2.3.3
Displaying an Abiotic Variable ..................................................... 25
2.3.4
Clustering with a SOM .................................................................. 26
2.4 Discussion ............................................................................................. 29
2.5 Conclusion ............................................................................................ 31
References ............................................................................................. 32
3. Ecological Applications of Genetic Aigorithms ..................... 35
3.1 Introduction ........................................................................................... 35
3.2 Ecology and Ecological Modelling ....................................................... 36
3.3 Genetic Algorithm Design Details ........................................................ 38
3.4 Applications of Genetic Algorithms to Ecological Modelling .............. 40
3.5 Predicting the Future with Genetic Algorithms .................................... 43
3.6 The Next Generation: Hybrids Genetic Algorithms ............................. 44
References ............................................................................................. 45