Titlebook: Computational Optimization and Applications in Engineering and Industry; Xin-She Yang,Slawomir Koziel Book 2011 Springer Berlin Heidelberg

摇晃

保留

Studies in Computational Intelligencehttp://image.papertrans.cn/c/image/232880.jpg

Infect

https://doi.org/10.1007/978-3-642-20986-4Computational Intelligence; Computational Optimization

1FAWN

978-3-642-26884-7Springer Berlin Heidelberg 2011

athlete’s-foot

https://doi.org/10.1007/978-981-15-4159-9 the data, different models can be used in different regions of the network. We present a strategy that adaptively applies the models and discretizations, using adjoint-based error estimators to maintain the accuracy of the solution. Finally, we give numerical examples for both types of networks.

刺耳

Listening and Silence in Supervisioneuristic algorithms are wellsuited to find the optimal parameters for these sequences. The motivation behind the use of biologically inspired heuristic and/or meta-heuristic algorithms is due to their ability to solve large, complex, and dynamic problems

Juvenile

LEVY

Supervision in the Legal Professionese problems are the optimization of settings (pressure or flow rate) in existing wells, optimization of the locations of new wells, and data assimilation or history matching. The performance of the derivative-free algorithms is shown to be quite acceptable, especially when they are implemented within a distributed computing environment.

Accolade

Focused Issues in Family Therapywledge from past observed catastrophe behaviour is used to guide the GA during various phases towards promising solution areas resulting in a fast convergence. Together with parallel computing techniques it becomes a viable estimation approach in environmental emergency modelling. Encouraging results were obtained in predicting forest fire spread.

Lipoprotein(A)

Gudmund Fossli,Hans Christian Michaelsening them to two conventional concrete material cases. The first case is simulation of concrete compressive strength using mix properties and the second problem is prediction of elastic modulus of concrete using its compressive strength.