Immunology as a Metaphor for Computational ... - Napier University

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Appendix B. Experimental results obtained using SOSDM 197subset size p means differ Data stored in SOSDM at each epochfor FPS Standard SOSDM FPS10 1.000000 50.275636 49.82063620 1.000000 50.275636 49.86809130 1.000000 50.275636 49.91945540 1.000000 50.275636 49.97886450 1.000000 50.275636 49.96536460 1.000000 50.275636 49.98372770 1.000000 50.275636 50.00045580 1.000000 50.275636 50.03922790 1.000000 50.275636 50.017182100 1.000000 50.275636 50.038636110 1.000000 50.275636 50.044545120 1.000000 50.275636 50.023000130 1.000000 50.275636 50.023636140 1.000000 50.275636 50.071591150 1.000000 50.275636 50.068000160 1.000000 50.275636 50.063773170 1.000000 50.275636 50.078273180 1.000000 50.275636 50.089773190 1.000000 50.275636 50.081455200 1.000000 50.275636 50.087364Table B.4: Table shows the probability that the mean fitness across entire dataset obtainedusing FPS is statistically different than the mean fitness obtained when all datais stored at each epoch
Appendix B. Experimental results obtained using SOSDM 198subset size p means differ Data stored in SOSDM at each epochfor FPS All data FPS10 1.000000 44.238182 46.19363620 0.999552 44.238182 45.45090930 0.999974 44.238182 45.67454540 0.999999 44.238182 45.88909150 1.000000 44.238182 45.92636460 0.999985 44.238182 45.68636470 1.000000 44.238182 46.00454580 0.999987 44.238182 45.63909190 0.999944 44.238182 45.539091100 0.998712 44.238182 45.297273110 0.999276 44.238182 45.340909120 0.999964 44.238182 45.570000130 0.999976 44.238182 45.653636140 0.999778 44.238182 45.458182150 0.999979 44.238182 45.624545160 0.999979 44.238182 45.586364170 0.999998 44.238182 45.689091180 0.999867 44.238182 45.498182190 0.999984 44.238182 45.605455200 0.999441 44.238182 45.333636Table B.5: Table shows the probability that the mean fitness of smallest cluster usingFPS is statistically different than the mean fitness obtained when all data is stored ateach epoch
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AbstractThe biological immune syste
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DeclarationI declare that this thes
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Table of Contents1 Introduction 11.
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5.3.1 Default Parameters . . . . .
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List of Figures2.1 ’Lock and Key
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List of Tables2.1 Structural and fu
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Chapter 1IntroductionThe study of b
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Chapter 1. Introduction 3scientists
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Chapter 1. Introduction 5Thus, the
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Chapter 1. Introduction 7of the cha
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Chapter 1. Introduction 94. Analysi
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Chapter 2. Background 11paratopeepi
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Chapter 2. Background 13antigenepit
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£Chapter 2. Background 15low the m
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Chapter 2. Background 17Antigene 0p
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Chapter 2. Background 19maintained
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E £ ρ¥ £Chapter 2. Background 2
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Chapter 2. Background 23genetically
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Chapter 2. Background 251. Choose a
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Chapter 2. Background 27non-interbr
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Chapter 2. Background 29been made i
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Chapter 2. Background 31patterns wi
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Chapter 2. Background 33reported on
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Chapter 2. Background 35Immunos 81
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Chapter 2. Background 37recognition
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Chapter 2. Background 391. Create a
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Chapter 2. Background 41environment
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Chapter 2. Background 43a)input dat
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Chapter 2. Background 45antibody wi
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Chapter 3. Immune Systems for Sched
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Chapter 4Applying an Immune System
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Chapter 4. Applying an Immune Syste
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Chapter 5. EA Based Model — COSDM
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Chapter 6. A Self-Organising SDM
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Page 196 and 197: Chapter 7. Conclusion 181however wh
Page 198 and 199: Chapter 7. Conclusion 183features m
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Page 204 and 205: Chapter 7. Conclusion 189Clustering
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Page 208 and 209: Appendix ACoincidences in permutati
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Page 218 and 219: Bibliography 203[Cooke and Hunt, 19
Page 220 and 221: Bibliography 205[Farmer et al., 198
Page 222 and 223: Bibliography 207[Hart et al., 1998]
Page 224 and 225: Bibliography 209[Kohonen, 1982b] Ko
Page 226 and 227: Bibliography 211[Potter and De Jong
Page 228: Bibliography 213[Timmis et al., 199
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