## Proceedings, Volumes 1-2IEEE, 1999 - Artificial intelligence |

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Page 467

2 Fuzzy C -

the formulated problem may be easier to solve computationally . This is due to

the fact that a non - fuzzy model often requires an exhaustive search in a huge ...

2 Fuzzy C -

**Means**Clustering The second reason for using these models is thatthe formulated problem may be easier to solve computationally . This is due to

the fact that a non - fuzzy model often requires an exhaustive search in a huge ...

Page 468

Luij = n i = 1 = 1 If Uj is fixed , then the optimal centre c ; that minimises Equation (

5 ) is the

algorithm is an iterated procedure through the following steps : Step 1 : Initialise

the ...

Luij = n i = 1 = 1 If Uj is fixed , then the optimal centre c ; that minimises Equation (

5 ) is the

**mean**of all vectors in the group i ... Summarising , the k -**means**algorithm is an iterated procedure through the following steps : Step 1 : Initialise

the ...

Page 470

For the one under consideration , when k -

five and ten iterations are needed to reach the improvement less than le - 5 . In

contrast , the fuzzy c -

For the one under consideration , when k -

**means**clustering is applied , betweenfive and ten iterations are needed to reach the improvement less than le - 5 . In

contrast , the fuzzy c -

**means**algorithm requires more than ten iterations .### What people are saying - Write a review

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### Contents

Java RealTime Distributed Processing Over ATM Networks with ChorusOS | 3 |

Optimizing Costs and Processing Times Under Variable External Processing | 4 |

Resources 1047 | 8 |

Copyright | |

59 other sections not shown

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### Common terms and phrases

action activity adaptive agent algorithm allows analysis application approach architecture Automation behavior block communication complex components configuration connection considered consists corresponding cost decision defined depends described detected determine developed devices distributed dynamic Engineering environment error example execution Figure final flow function given implementation important improve industrial initial input integrated interface International Java learning machine manufacturing means measurement method module monitoring necessary object obstacle obtained operations optimal output parameters performance planning plant position possible presented problem proposed reference represented robot rules scheduling selected sensor sequence server shown shows signal simulation solution specific step structure Table task techniques tool transition unit variables visual