Based on the validated model, a proposed optimization pattern of the boiler is undertaken and examined by means of CFD.
The two types of neural networks have attained broad applications in knowledge acquisition, combinatorial optimization, pattern recognition, and other areas [3].
In the second level of optimization, pattern search is further used to enhance the segmentation results using shape description as a complementary feature.
Conversely, the observed optimization pattern (despite being imperfect) constitutes a more parsimonious solution, as it implies a minimal disruption to the pre-existing trapline.
Although there is no centralized module that dictates the behavior of individuals, local interactions cause a global optimization pattern to emerge [ 8- 10].
In view of the large area, low abundance and high heterogeneity of Sulige gas field, a series of techniques have been developed including hierarchical description for the reservoir architecture of large composite sand bodies and well spacing optimization, well pattern optimization, design and optimization for horizontal trajectory and deliverability evaluation for different types of gas wells.
Binhua Tang et al. proposed a supervised combinatorial-optimization pattern based on information and signal processing theories to infer and analyze the genetic regulatory networks.
A supervised combinatorial-optimization pattern based on information and signal-processing theories is introduced into the inference and analysis of genetic regulatory networks.
After optimization of patterns, color of selected patterns will be optimized.
The second group includes derivative-free algorithms including particle swarm optimization (PSO), pattern search (PS), guided pattern search (GPS), covariance matrix adaptation evolutionary strategy (CMAES), differential evolution (DE) and self-adaptive differential evolution (SADE).
