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Dept. of Computational Intelligence & Systems Science Tokyo Institute of Technology

博士本審査 2006.01.04. Family of S elf- O rganized N etwork Inspired by I mmune A lgorithm ( SONIA ) and Their Various Applications. Dept. of Computational Intelligence & Systems Science Tokyo Institute of Technology. SONIA. SONIA-DNN. CMF-SONIA. Muhammad R. Widyanto 03D35190. F-SONIA.

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Dept. of Computational Intelligence & Systems Science Tokyo Institute of Technology

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  1. 博士本審査 2006.01.04 Family of Self-Organized Network Inspired by Immune Algorithm (SONIA) and Their Various Applications Dept. of Computational Intelligence & Systems Science Tokyo Institute of Technology SONIA SONIA-DNN CMF-SONIA Muhammad R. Widyanto 03D35190 F-SONIA EF-SONIA

  2. SONIA CMF-SONIA SONIA-DNN F-SONIA EF-SONIA Thesis Road Map Chapter 1 Introduction [Jx]: Journal Paper x-th Chapter 2 [J1] SONIA and Food Quality Prediction Chapter 3 [J2] SONIA-DNN and Preference Modeling Chapter 4 [J3] F-SONIA and Fragrance Recognition Chapter 5 [J4] CMF-SONIA and Overlapping Pat. Clas. Chapter 6 [J5] EF-SONIA and Unknown Odor Recog. Chapter 7 Conclusions

  3. SONIA CMF-SONIA SONIA-DNN F-SONIA EF-SONIA Contents Chap. 1 Introduction Chap. 2 SONIA and Food Quality Prediction Chap. 3 SONIA-DNN for Preference Modeling Chap. 4 F-SONIA for Fragrance Recognition Chap. 5 CMF-SONIA for Overlapping Pattern Class. Chap. 6 EF-SONIA for Unknown Odor Recognition Chap. 7 Conclusions

  4. Chap. 1 Introduction Low Generalization Global Response Overfitting Problems BPNN [Rumelhart, 86] Back-Propagation Neural Network

  5. Chap. 1 Introduction Local Response Characteristics only Diverse Representation Opportunity Immune Algorithm [Timmis, 01]

  6. Chap. 1 Introduction BPNN [Rumelhart,86] Immune Algorithm[Timmis,01] Better Recognition Better Generalization SONIA Solution A Self-Organized Network inspired by Immune Algorithm [proposed]

  7. Chap. 1 Introduction Food Quality Prediction SONIA CMF-SONIA SONIA-DNN F-SONIA EF-SONIA Preference Modeling Fragrance Recognition Overlapping Pat. Clas. Unknwon Odor Recog. SONIA Applications

  8. SONIA Contents Chap. 1 Introduction Chap. 2 SONIA and Food Quality Prediction Chap. 3 SONIA-DNN for Preference Modeling Chap. 4 F-SONIA for Fragrance Recognition Chap. 5 CMF-SONIA for Overlapping Pattern Class. Chap. 6 EF-SONIA for Unknown Odor Recognition Chap. 7 Conclusions

  9. Chap. 2 SONIA ・ ・ ・ ・ ・ ・ ・ ・ ・ Input Vector Hidden Unit Antigen Recognition Ball (RB) Self-Organized Network inspired by Immune Algorithm [proposed] Input layer Hidden layer Output layer BPNN : [Rumelhart,86] Immune Algorithm : [Timmis,01]

  10. Chap. 2 SONIA Antigen Input Vector Epitope Euclidian Distance Paratope Antibody Unit Centroid B Cell Recognition Ball (RB) Hidden Unit Recognition Ball & Hidden Unit [proposed]

  11. Chap. 2 SONIA Hidden Unit 1 Hidden Unit 2 RB 1 Hidden Unit i RB 2 RB i Mutated Hidden Unit n Mutated RB n B-Cell Construction & Mutation [proposed] Antibody Generation [Timmis,01] Hidden Unit Creation of BPNN [proposed] Antigen [1..m] Input Vector [1..m]

  12. Chap. 2 SONIA BPNN Regularization [MacKay, 92] Approximation Error : 0.00241 BPNN [Rumelhart, 86] Approximation Error : 0.01994 h(x) h(x) h(x) h(x) SONIA with mutation [proposed] Approximation Error : 0.00118 SONIA without mutation Approximation Error : 0.01008 Approximation TrainingData x x x x

  13. Chap. 2 SONIA Prediction Engine: Neural Networks Production Area Quality Control Server Quality Check Supermarket Perishable Food Food Store Frozen Truck Market Area Food Quality Prediction Collaborative Project with Japan Ministry of Agriculture and CSD Inc.

  14. Chap. 2 SONIA Time-temperature Data Data Collection : Data Lodger Data Collection : Data Lodger Channel 1 Channel 2 oC Pre-Processing : Range Selection Pre-Processing : Range Selection Time ( X5 Minutes ) Range Selected Quality ch1:Mean Neural Networks Feature Extraction : Mean & Standard Deviation Feature Extraction : Mean & Standard Deviation ch1:SD A good ch2:Mean B C ch2:SD D E Prediction System [proposed] Collaborative Project with Japan Ministry of Agriculture and CSD Inc.

  15. Chap. 2 SONIA Recognition Accuracy TOP MIDDLE BOTTOM Collaborative Project with Japan Ministry of Agriculture and CSD Inc. SONIA BPNN Recognition (%) 100 50 0 TOP MIDDLE BOTTOM

  16. SONIA-DNN Contents Chap. 1 Introduction Chap. 2 SONIA and Food Quality Prediction Chap. 3 SONIA-DNN for Preference Modeling Chap. 4 F-SONIA for Fragrance Recognition Chap. 5 CMF-SONIA for Overlapping Pattern Class. Chap. 6 EF-SONIA for Unknown Odor Recognition Chap. 7 Conclusions

  17. Chap. 3 SONIA-DNN Modeling DM Preference ??? Alternative1: Nissan Fuga Price: 5 million yen Decision Maker (DM) Engine: 3000 cc Consumption: 10km/l Decision Maker (DM) Preference JSPS Center Of Excellence Project Preference Value

  18. Chap. 3 SONIA-DNN Alternative1: Nissan Fuga Decision Maker (DM) Alternative2: Toyota Mark X Preference Value by Comparisons Comparison Value

  19. Chap. 3 SONIA-DNN SONIA(1) SONIA(2) SONIA-based Decision Neural Network [proposed] JSPS Center Of Excellence Project Alternative 1 Comparison Value Alternative 2 Incomplete Comparisons Better Generalization

  20. Chap. 3 SONIA-DNN Decision Maker (DM) Incomplete Comparisons JSPS Center Of Excellence Project Too many! Limited Training Data

  21. Chap. 3 SONIA-DNN Decision Maker (DM) Lp-metric Function Benchmark [Sun, 1996] Preference Value Alternative

  22. Chap. 3 SONIA-DNN 21 comparison values 7 discarded randomly, 14 training samples Experimental Setting

  23. Chap. 3 SONIA-DNN Average Error (%) 4 2 0 BPNN-DNN SONIA-DNN Experimental Result Excellent!

  24. Chap. 3 SONIA-DNN BPNN-DNN [Chen, 2004] SONIA-DNN [proposed] Experiments JSPS Center Of Excellence Project Average Error (%) 8 4 Wonderful! 0 18 15 12 Number of Samples

  25. F-SONIA Contents Chap. 1 Introduction Chap. 2 SONIA and Food Quality Prediction Chap. 3 SONIA-DNN for Preference Modeling Chap. 4 F-SONIA for Fragrance Recognition Chap. 5 CMF-SONIA for Overlapping Pattern Class. Chap. 6 EF-SONIA for Unknown Odor Recognition Chap. 7 Conclusions

  26. Chap. 4 F-SONIA Human Experts Perfume Industry Three Mixture Two Mixture Pure Perfume Artificial Odor Discrimination System Problem Complexity Odor Discrimination System

  27. Chap. 4 F-SONIA Sensory System Frequency Counter System Neural Network Artificial Odor Discrimination System Collaboration with University of Indonesia Under Indonesia Ministry of Sciences & Technology Project

  28. Chap. 4 F-SONIA Input Vector Fuzzy Input Vector Euclidean Distance Fuzzy Similarity Unit Centroid Fuzzy Unit Centroid SONIA : Hidden Unit F-SONIA : Fuzzy Hidden Unit Fuzzy Similarity based SONIA(1/4) [proposed] Collaboration with University of Indonesia Under Indonesia Ministry of Sciences & Technology Project

  29. Chap. 4 F-SONIA SONIA : Crisp Value 1 Membership Value F-SONIA : [proposed] Frequency Fuzzy Triangular Number Fuzzy Similarity based SONIA(2/4) [proposed] Collaboration with University of Indonesia Under Indonesia Ministry of Sciences & Technology Project minimum mean maximum

  30. Chap. 4 F-SONIA Membership Value 1 Frequency Fuzzy Similarity based SONIA(3/4) [proposed] Collaboration with University of Indonesia Under Indonesia Ministry of Sciences & Technology Project Input Vector Hidden Unit Vector Similarity Value (μ)

  31. Chap. 4 F-SONIA Input Unit Hidden Unit Sensor 1 Square Root of Quadratic Distances ・ ・ ・ Euclidean Distance Sensor i Arithmetic Mean of Similarity Measures Sensor 1 ・ ・ ・ Fuzzy Similarity Sensor i Fuzzy Similarity based SONIA(4/4) [proposed] Collaboration with University of Indonesia Under Indonesia Ministry of Sciences & Technology Project SONIA : F-SONIA :[proposed]

  32. Chap. 4 F-SONIA Citrus-Canangga-Ethanol(%) Collaboration with University of Indonesia Under Indonesia Ministry of Sciences & Technology Project Recognition (%) 100 50 0 F-SONIA [proposed] FLVQ [Sakuraba,91] LVQ [Kohonen,86] BPNN [Rumelhart,86] SONIA

  33. Chap. 4 F-SONIA Error SONIA F-SONIA Epoch Error Convergence Collaboration with University of Indonesia Under Indonesia Ministry of Sciences & Technology Project

  34. Chap. 4 F-SONIA Dissimilarity Definition [Hastie,01] SONIA F-SONIA Dissimilarity Comparison Collaboration with University of Indonesia Under Indonesia Ministry of Sciences & Technology Project

  35. CMF-SONIA Contents Chap. 1 Introduction Chap. 2 SONIA and Food Quality Prediction Chap. 3 SONIA-DNN for Preference Modeling Chap. 4 F-SONIA for Fragrance Recognition Chap. 5 CMF-SONIA for Overlapping Pattern Class. Chap. 6 EF-SONIA for Unknown Odor Recognition Chap. 7 Conclusions

  36. Chap. 5 CMF-SONIA Class A Class B Overlapping Data Adaptive Clustering inspired by B-Cell Construction of SONIA Errors in Classification

  37. Chap. 5 CMF-SONIA Class A Class B Class Majority F-SONIA[proposed] Good Idea! Class Majority for each Cluster Reduce Errors in Classification

  38. Chap. 5 CMF-SONIA F2 (Hz) 2000 0 heed head hid had heard hud hood hod who’d hawed 0 750F1(Hz) Vowel Data [Lippmann,89]

  39. Chap. 5 CMF-SONIA Recognition Accuracy Recognition (%) 80 Excellent! 40 0 CMF-SONIA [proposed] F-SONIA BPNN [Rumelhart,86]

  40. Chap. 5 CMF-SONIA F2 (Hz) 2000 0 0 750F1(Hz) Classification Plane Wow!

  41. EF-SONIA Contents Chap. 1 Introduction Chap. 2 SONIA and Food Quality Prediction Chap. 3 SONIA-DNN for Preference Modeling Chap. 4 F-SONIA for Fragrance Recognition Chap. 5 CMF-SONIA for Overlapping Pattern Class. Chap. 6 EF-SONIA for Unknown Odor Recognition Chap. 7 Conclusions

  42. Chap. 6EF-SONIA Input Neural Nets Known Odor Unknown Odor Unknown Odor Recognition Collaboration with University of Indonesia Under Indonesia Ministry of Sciences & Technology Project

  43. Chap. 6EF-SONIA Arithmetic Mean High Similarity NoSimilarity Far with High Similarity High Similarity

  44. Chap. 6EF-SONIA Euclidean Fuzzy Similarity [proposed] No Similarity

  45. Chap. 6EF-SONIA Similarity Measure Membership Value Input Vector Hidden Unit Vector 1 Similarity Value (μ) Euclidean Dimension ?? ??

  46. Chap. 6EF-SONIA Averaging Approach Elliptical Approach Fuzziness Region ?? Second Dimension ?? First Dimension

  47. Chap. 6EF-SONIA Elliptical Approach [proposed] Brilliant Idea! Θ

  48. Chap. 6EF-SONIA Citrus-Canangga-Ethanol(%) Excellent!

  49. SONIA CMF-SONIA SONIA-DNN F-SONIA EF-SONIA Contents Chap. 1 Introduction Chap. 2 SONIA and Food Quality Prediction Chap. 3 SONIA-DNN for Preference Modeling Chap. 4 F-SONIA for Fragrance Recognition Chap. 5 CMF-SONIA for Overlapping Pattern Class. Chap. 6 EF-SONIA for Unknown Odor Recognition Chap. 7 Conclusions

  50. Chap. 7 Conclusions SONIA CMF-SONIA SONIA-DNN F-SONIA EF-SONIA - Proposed Methods - - Applications - SONIA Food Quality Prediction Preference Modeling SONIA-DNN Fragrance Recognition F-SONIA Overlapping Patt. Class. CMF-SONIA Unknown Odor Recog. EF-SONIA Research Results SONIA Family

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