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Performance index table

The learning element consists of a Performance Index (PI) table combined with a rule generation and modification algorithm, which creates new rules, or modifies existing ones. The structure of a SOFLC is shown in Figure 10.17. With SOFLC it is usual to express the PI table and rulebase in numerical, rather than linguistic format. So, for... [Pg.344]

Figure 9.9 shows HP steam consumption under different parameter settings of A, B, and C. Solution D was omitted as the differences between D and C are relatively small. For this performance index, solution A consumes the least steam while solution C the most. Here, the steam consumption of solution C was sacrificed to achieve more gains in the fuel gas and energy gain. The cost of steam consumption is calculated in Table 9.7. [Pg.295]

To better illustrate the effect of the optimization process, Table 9.10 summarizes the various key performance indexes considered in terms of dollars. The best solution is point C optimized by MOEA, where the total consumption of fuel and steam is the lowest while the energy gain is the highest. However it has the highest steam consumption. [Pg.297]

A clutch performance index is then assigned to the oil, which can then be classified according to Table 9.13 as JASO MA, MAI and MA2 (high friction, suitable for wet clutch applications) or JASO MB (low friction, more suited to dry clutch or... [Pg.322]

The classification on the basis of the normahzed performance index Ipi is given in Table 8.2. [Pg.132]

Table 8.2. Classification of materials by normalized performance index Ipi... Table 8.2. Classification of materials by normalized performance index Ipi...
Table 8.6. Classification ofprocesses on the basis of the performance index... Table 8.6. Classification ofprocesses on the basis of the performance index...
The classification of the materials obtained with this new performance index is shown in Figure 8.10 and Table 8.8. [Pg.148]

If we adjust the previous performance index by the functional unit (amount of liquid transported per unit mass of the bottle), we obtain the modifications presented in Table 8.9. [Pg.148]

Table 4. Construction project schedule, safety, quality, investment performance index weight. [Pg.245]

Table 2. Ensemble reconstruction performance indexes obtained with simple mean, median and trimmed mean aggregations on undisturbed, noisy and drifted signals. [Pg.108]

The data in Table 5.5 indicate that the separation characteristics of each feed are quite different. By repeated use of the automated selection procedures in FDS, the information shown in Table 5.6 can be produced. The numbers listed under the subheadings D and W indicate the relative performance index of the equipment as a solids dewatering or cake washing device respectively (better performance is associated with greater index values). A indicates that the equipment is not suitable for the particular separation. [Pg.245]

Results indicate that all GNM models were able to find an optimally set of inputs close to the true optimum and maintained this conditions over the time. It can be observed that the deviations respects to the nominal optimum are more severe when more inexact is the process model using in the RTO. Other issue observed is the sensitive of the RTO/GNM system to the initial conditions in the optimizer. In order to compare the performance of each model considered in this work, a dynamic performance index, deEned as the total profit obtained over the time window was calculated and shown in Table 1. Results show that a more exact model brings best performance, specifically the three reaction model. [Pg.398]

Table 5 shows the cumulative performance index with uniform weighting for FC 1-IV for control structures a and b that differ on the installation or not of a feed/purge stream system for component D (see dashed envelope at the bottom of column C2 in Figure 1) calculated at various disturbance magnitudes. The cumulative index, 2sc, uses all the scaled controlled and manipulated variables specified for each control structure. The results reveal... [Pg.347]

Heat transmission rate, peak of heat transmission rate, propensity of flashover (or fire performance index) are the parameters which characterize heat generation during a fire. These parameters are affected by Table 12.4 re-... [Pg.401]

Controller tuning relations for the ITAE performance index are shown in Table 12.3. These relations were developed for the FOPTD model of Eq. 12-10... [Pg.221]

Both shape and materials selections should be carried out together since shaping depends on the type of material - for example ceramics are more difficult to shape than metals. Let us concentrate on mechanics, which is the focus of the book, and more precisely now on the mechanical design that has been extensively reviewed by Ashby (2001). Several performance indices are listed in Table 2.5 according to the application. At this stage, these indices do not yet consider shape. Let us take an example to determine the performance index and determine how shape influences this performance. This will allow us to introduce the shape factor and hence understand how shape contributes to object strength. [Pg.50]

Performance index If weightages of 1,2,...etc, are attached to the 1st, 2nd,...ranks respectively, total score of each model can be computed. Ratio of this total score to that of WWA, identified as performance index, PI, is taken as a measure of effectiveness of each policy. Table 5 shows the PI of different policies with respect to WWA, showing better position occupied by DLIC. [Pg.122]

TABLE 5 - Performance Index (PI) of different lot sizing strategies (PI for WWA is taken as 1)... [Pg.125]

Ellipsometry and Thermal Gravimetric Analysis. Ellipsometry was performed on thin film samples deposited on silicon substrates to determine film Sickness and refractive index. Table I lists values of thickness and refractive index for films prepared from A2(fresh) and A2(aged) sols after varying periods of aging (prior to... [Pg.110]

Whereas there is no universally accepted specification for marketed natural gas, standards addressed in the United States are Hsted in Table 6 (8). In addition to these specifications, the combustion behavior of natural gases is frequently characteri2ed by several parameters that aid in assessing the influence of compositional variations on the performance of a gas burner or burner configuration. The parameters of flash-back and blow-off limits help to define the operational limits of a burner with respect to flow rates. The yeUow-tip index helps to define the conditions under which components of the natural gas do not undergo complete combustion, and the characteristic blue flame of natural gas burners begins to show yellow at the flame tip. These... [Pg.172]


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See also in sourсe #XX -- [ Pg.344 , Pg.346 ]




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