### Table 13: Genetic Algorithm Optimization Results Step ACP3L ACP3H

2005

"... In PAGE 96: ... The optimal solutions are validated over the entire frame of data after the completion of each step described above. These actual ACP optimization results are summarized in Table13 and the sequential linearization performance is illustrated in Figure 52. Table 13: Genetic Algorithm Optimization Results Step ACP3L ACP3H... ..."

### Table 2. Genetic algorithm (optimized power)/(initial power) for fixed compile time

2000

"... In PAGE 13: ... For the largest graph, the fixed simulation time was not long enough to make much improvement, but the best result occurred for , where the simulations are less frequent. Table2 summarizes the power reduction for the genetic algorithm with and without using the period graph, with a fixed compile time of one hour. 9 Conclusion This paper has explored a period graph model that enables efficient voltage scaling optimization for self-timed implementations of iterative applications.... ..."

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### Table 2. Genetic algorithm (optimized power)/(initial power) for fixed compile time

"... In PAGE 6: ... For the largest graph, the fixed simulation time was not long enough to make much improvement, but the best result occurred for , where the simulations are less fre- quent. Table2 summarizes the power reduction for the genetic algorithm with and without using the period graph, with a fixed compile time of one hour. 9 Conclusion This paper has explored a period graph model that enables efficient voltage scaling optimization for self-timed implementations of iterative applications.... ..."

### Table 5.12: Genetic algorithm optimized lumber defect classifier results.

2005

### Table 2: Simulated annealing amp; genetic algorithm--constrained optimization

"... In PAGE 4: ... The confidence intervals for 95% confidence level were calculated for both the algorithms. Table2... ..."

### Table I. Candidate Optimization Phases in the Genetic Algorithm with Their Designations Optimization Phase Gene Description

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### Table 8.2. Candidate Optimization Phases in the Genetic Algorithm Experiments Optimization Phase Description

2005

### Table 1. Optimization parameters for genetic algorithm.

in Atmospheric Chemistry and Physics Optimizing CO2 observing networks in the presence of model error:

2004

### Table 8.5. Comparison of Three Di erent Fitness Values for the Genetic Algorithm optimizing for WCET Only Code Size Only both

2005

### Table II. Candidate Optimization Phases in the Genetic Algorithm along with their Designations Optimization Phase Gene Description

2005

Cited by 3