About the Author |
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xiii | |
Preface to the Third Edition |
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xv | |
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1 | (24) |
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2 | (1) |
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3 | (3) |
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The utility of Fuzzy Systems |
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6 | (2) |
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Limitations of Fuzzy Systems |
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8 | (2) |
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The Illusion: Ignoring Uncertainty and Accuracy |
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10 | (3) |
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Uncertainty and Information |
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13 | (1) |
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14 | (1) |
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Fuzzy Sets and Membership |
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14 | (2) |
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16 | (2) |
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Sets as Points in Hypercubes |
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18 | (2) |
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20 | (1) |
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20 | (1) |
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21 | (4) |
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Classical Sets and Fuzzy Sets |
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25 | (23) |
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26 | (8) |
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Operations on Classical Sets |
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28 | (1) |
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Properties of Classical (Crisp) Sets |
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29 | (3) |
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Mapping of Classical Sets to Functions |
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32 | (2) |
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34 | (7) |
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35 | (2) |
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37 | (3) |
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Alternative Fuzzy Set Operations |
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40 | (1) |
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41 | (1) |
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42 | (1) |
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42 | (6) |
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Classical Relations and Fuzzy Relations |
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48 | (41) |
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49 | (1) |
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49 | (5) |
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Cardinalityof Crisp Relations |
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51 | (1) |
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Operation on Crisp Relations |
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52 | (1) |
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Properties of Crisp Relations |
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52 | (1) |
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53 | (1) |
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54 | (8) |
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Cardinality of Fuzzy Relations |
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55 | (1) |
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Operations on Fuzzy Relations |
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55 | (1) |
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Properties of Fuzzy Relations |
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55 | (1) |
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Fuzzy Cartesian Product and Composition |
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55 | (7) |
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Tolerance and Equivalence Relations |
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62 | (3) |
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Crisp Equivalence Relation |
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63 | (1) |
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64 | (1) |
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Fuzzy Tolerance and Equivalence Relations |
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65 | (3) |
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68 | (4) |
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69 | (2) |
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71 | (1) |
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71 | (1) |
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Other Forms of the Composition Operation |
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72 | (1) |
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72 | (1) |
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73 | (1) |
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73 | (16) |
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Properties of Membership Functions, Fuzzification, and Defuzzification |
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89 | (28) |
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Features of the Membership Function |
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90 | (2) |
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92 | (1) |
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93 | (2) |
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Defuzzification to Crisp Sets |
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95 | (2) |
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λ Cuts for Fuzzy Relations |
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97 | (1) |
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Defuzzification to Scalars |
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98 | (12) |
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110 | (1) |
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111 | (1) |
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112 | (5) |
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117 | (57) |
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117 | (22) |
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118 | (6) |
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124 | (7) |
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131 | (3) |
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134 | (4) |
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Other Forms of the Implication Operation |
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138 | (1) |
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139 | (20) |
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140 | (2) |
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142 | (3) |
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Fuzzy (Rule-Based) Systems |
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145 | (3) |
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Graphical Techniques of Inference |
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148 | (11) |
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159 | (2) |
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161 | (1) |
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162 | (12) |
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Development of Membership Functions |
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174 | (37) |
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Membership Value Assignments |
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175 | (31) |
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175 | (1) |
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176 | (2) |
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178 | (1) |
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179 | (10) |
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189 | (10) |
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199 | (7) |
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206 | (1) |
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206 | (1) |
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207 | (4) |
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Automated Methods for Fuzzy Systems |
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211 | (34) |
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212 | (3) |
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Batch Least Squares Algorithm |
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215 | (4) |
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Recursive Least Squares Algorithm |
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219 | (3) |
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222 | (5) |
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227 | (2) |
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229 | (4) |
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Modified Learning From Examples |
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233 | (9) |
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242 | (1) |
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242 | (1) |
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243 | (2) |
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245 | (31) |
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Fuzzy Relational Equations |
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250 | (1) |
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Nonlinear Simulation Using Fuzzy Systems |
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251 | (4) |
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Fuzzy Associative Memories (FAMS) |
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255 | (9) |
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264 | (1) |
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265 | (1) |
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266 | (10) |
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Decision Making with Fuzzy Information |
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276 | (56) |
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Fuzzy Synthetic Evaluation |
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278 | (2) |
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280 | (3) |
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283 | (2) |
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285 | (4) |
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Multiobjective Decision Making |
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289 | (5) |
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Fuzzy Bayesian Decision Method |
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294 | (10) |
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Decision Making Under Fuzzy States and Fuzzy Actions |
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304 | (13) |
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317 | (1) |
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318 | (1) |
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319 | (13) |
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332 | (37) |
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Classification by Equivalence Relations |
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333 | (6) |
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333 | (2) |
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335 | (4) |
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339 | (1) |
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340 | (1) |
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340 | (1) |
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341 | (8) |
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349 | (8) |
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352 | (5) |
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357 | (3) |
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Hardening the Fuzzy c-Partition |
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360 | (1) |
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Similarity Relations from Clustering |
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361 | (1) |
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362 | (1) |
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362 | (1) |
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363 | (6) |
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Fuzzy Pattern Recognition |
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369 | (39) |
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370 | (1) |
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Partitions of the Feature Space |
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371 | (1) |
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Single-Sample Identification |
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371 | (7) |
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Multifeature Pattern Recognition |
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378 | (12) |
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390 | (8) |
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398 | (1) |
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399 | (1) |
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400 | (8) |
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Fuzzy Arithmetic and the Extension Principle |
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408 | (29) |
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408 | (10) |
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Crisp Functions, Mapping, and Relations |
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409 | (2) |
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Functions of Fuzzy Sets-Extension Principle |
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411 | (1) |
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Fuzzy Transform (Mapping) |
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411 | (2) |
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413 | (5) |
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418 | (2) |
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Interval Analysis in Arithmetic |
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420 | (2) |
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Approximate Methods of Extension |
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422 | (10) |
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423 | (3) |
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426 | (2) |
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428 | (1) |
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429 | (3) |
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432 | (1) |
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433 | (1) |
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433 | (4) |
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437 | (64) |
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Control System Design Problem |
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439 | (3) |
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Control (Decision) Surface |
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440 | (1) |
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Assumptions in a Fuzzy control System Design |
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441 | (1) |
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Simple Fuzzy Logic Controllers |
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441 | (1) |
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Examples of Fuzzy Control System Design |
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442 | (11) |
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Aircraft Landing Control Problem |
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446 | (7) |
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Fuzzy Engineering Process Control |
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453 | (11) |
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Classical Feedback Control |
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453 | (4) |
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457 | (7) |
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Fuzy Statistical Process Control |
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464 | (14) |
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Measurement Data - Traditional SPC |
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466 | (6) |
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Attribute Data-Traditional SPC |
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472 | (6) |
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478 | (1) |
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479 | (3) |
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482 | (2) |
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484 | (17) |
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501 | (29) |
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501 | (7) |
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One-Dimensional Optimization |
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502 | (6) |
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508 | (12) |
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Concept Variables and Causal Relations |
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508 | (2) |
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510 | (10) |
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520 | (4) |
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524 | (1) |
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525 | (1) |
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526 | (4) |
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Monotone Measures: Belief, Plausibility, Probability, and Possibility |
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530 | (49) |
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531 | (1) |
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532 | (5) |
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537 | (3) |
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540 | (2) |
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Possibility and Necessity Measures |
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542 | (7) |
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Possibility Distributions as Fuzzy Sets |
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549 | (2) |
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Possibility Distributions Derived from Empirical Intervals |
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551 | (18) |
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Deriving Possibility Distributions from Overlapping Intervals |
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552 | (2) |
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Redistributing Weight from Nonconsonant to Consonant Intervals |
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554 | (14) |
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Comparision of Possibility Theory and Probability Theory |
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568 | (1) |
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569 | (2) |
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571 | (1) |
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572 | (7) |
Index |
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579 | |