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where Ai are information granules (fuzzy sets de ned in the multivariable input space) and fi stand for the conclusion part. In essence, the form of the conclusion could be very diversi ed. We could encounter fuzzy sets, linear functions, polynomials, and neural networks. The vector of parameters of the conclusion part is denoted by ai. In particular, those could be the parameters of the polynomials or the connections of the neural network. The construction of fuzzy rule-based models has been a topic of intensive design studies and we have witnessed a great deal of important developments [12, 13, 18, 19, 21]. Particularly discussed were various issues dealing with multiobjective developments of fuzzy models involving a satisfaction of criteria of accuracy and interpretability. The design of rule-based topologies is naturally split into two phases: 1. Formation of the condition parts of the rules 2. Development of the conclusions of the rules The number of rules is directly associated with the granularity of the fuzzy model a unique feature of the class of rule-based architectures. The higher the number of the rules, the higher the granularity of the model and the more details are captured. Quite commonly, the condition parts of the rules are constructed with the use of fuzzy clustering, which produces a collection of information granules clusters formed in the input space. Various clustering techniques have been exploited as a generic design framework for the design of fuzzy sets and partition the input space. The development of the conclusion part is quite standard, as in many cases it boils down to the linear estimation problem with some eventual enhancements.

(4) x (m x I), y(x) (n xI), z(x) (p x 1), A (q x n), B (q x p) :

The number of clusters is another important design feature of the clustering algorithm. There have been a number of cluster validity indexes [10, 11], which are geared to assess the most suitable number of clusters that are supposed to correspond with the true structure in the data. The inherent problem with them is that quite often one gets several con icting suggestions depending on which cluster validity index has been selected. In this study, we follow a different path, which could be referred to as a granulation de-granulation strategy [17, 18]. In essence, once the information granules have been formed by the FCM, we use the prototypes to represent each pattern in the form of information granules by computing the corresponding membership degrees. At the next step, we complete a de-granulation, which is to estimate the pattern on the basis of the prototypes and the membership degrees. Ideally, we would expect that the result of such

The most common sound-related task in Flash is starting and stopping sounds at keyframes in synchronization with animation.

A dBm is a unit of power. It is expressed in a logarithm scale with reference to one milliwatt. 2130 dBm stands for 10213 mW, which is quite small! 18 The same applies to GPS L5, L2C, and M.

The phone option is included in a PMS for those properties that do not have an interface with the call-accounting system. With the call-accounting interface, the charges for local and long-distance phone calls, plus surcharges, will be posted automatically. Without the interface, the desk clerk must manually post the phone charge on the electronic folio.

Machine A (Investment Cost $10,000) Year 1 Saving (wages) Expenses Initial training cost Maintenance contract Special overhaul Supplies Depreciation Total expenses Saving less expenses Income tax 30% Net Income Add back depreciation Add scrap value Net Cash Flow $8,000 $3,500 900 1,300 1,800 $7,500 $ 500 ( 150) $ 350 1,800 Year 2 $8,000 Year 3 $8,000 Year 4 $8,000 Year 5 $8,000

29 One should understand that the receiver time could be far away from the real time, leading to a misinterpretation of the satellite con guration. 30 Or any other location obtained through the GSM network.

triangles For each reporting cell i, its vicinity is defined as the collection of all nonreporting cells that are reachable from cell i without crossing another reporting cell The reporting cell belongs to its own vicinity For example, the vicinity of cell C includes cells A, C, and F in Figure 26 A mobile station will update its location (ie, cell ID) whenever it moves into a new reporting cell For example, when a mobile station moves from cell B to cell A then to cell C in Figure 26, it will report its new location because cell B and cell C are two different reporting cells However, if a mobile station moves from cell B to cell A then move back into cell B, no location update is necessary.