A First Course in FUZZY and NEURAL CONTROL

272 CHAPTER 8. APPLICATIONS estimator (Kalmanfiltering algorithm) described on page 263. There are a total of 48 consequent para ...

8.4. IDENTIFICATION OF TRASH IN COTTON 273 Table 8.7. Final values of consequent parameters: 232-partition Consequent Parameters ...

274 CHAPTER 8. APPLICATIONS Initial MF's on Area 0 0.2 0.4 0.6 0.8 1 1.2 0 1000 2000 3000 4000 5000 Area Final MF's on Area 0 0. ...

8.4. IDENTIFICATION OF TRASH IN COTTON 275 Classification results of test samples using ANFIS The classification of various tras ...

276 CHAPTER 8. APPLICATIONS pepper objects at high accuracies, the computation of the classification rates might be skewed as a ...

8.4. IDENTIFICATION OF TRASH IN COTTON 277 Initial MF's on Edif 0 0.2 0.4 0.6 0.8 1 1.2 0 0.1 0.2 0.3 0.4 0.5 Edif Final MF's on ...

278 CHAPTER 8. APPLICATIONS Table 8.15 illustrates the classification results of the training data. As seen from the table, the ...

8.5. INTEGRATED PEST MANAGEMENT SYSTEMS 279 Table 8.16. Classification results of trash objects infive test samples using ANFIS: ...

280 CHAPTER 8. APPLICATIONS Referring to Figure 8.21, the collection of insects is a random sample that is representative of the ...

8.5. INTEGRATED PEST MANAGEMENT SYSTEMS 281 ïIf ratio of insects is small and pest A is high, then apply high concentration pest ...

282 CHAPTER 8. APPLICATIONS Table 8.18. List of insects in cotton and alfalfafields Insect Type Good Bad Comments Assassin bug X ...

8.5. INTEGRATED PEST MANAGEMENT SYSTEMS 283 Figure 8.23. Cucumber beetle Figure 8.24. Lygus adult Thetypeoffeaturesusedinaclassi ...

284 CHAPTER 8. APPLICATIONS empirical relationships that describe the features of objects. Size, shape, and other qualitative de ...

8.5. INTEGRATED PEST MANAGEMENT SYSTEMS 285 Figure 8.25. Clustering approach Referring to Figure 8.25, while class objects A and ...

286 CHAPTER 8. APPLICATIONS feature. Because only two linguistic variables are used for each feature, a total of 32 rules is gen ...

8.5. INTEGRATED PEST MANAGEMENT SYSTEMS 287 Figure 8.30. Perimeter after training Figure 8.31. Form-factor before training Figur ...

288 CHAPTER 8. APPLICATIONS Figure 8.33. Roundness-factor before training Figure 8.34. Roundness-factor after training Figure 8. ...

8.5. INTEGRATED PEST MANAGEMENT SYSTEMS 289 Figure 8.36. Compactness-factor after training Figure 8.37 illustrates the performan ...

290 CHAPTER 8. APPLICATIONS 8.6 Comments............................... The applications discussed in this chapterclearly illust ...

Bibliography [1] S. Abe and M.S. Lan, A method for fuzzy rule extraction directly from numerical data and its application to pat ...