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Groundwater flow simulation has become one of the top international issues in new generation of environmental applications. When managing large-scale groundwater flow problems, the intensive computational ability and large amounts of memory space required for modeling are the main bottlenecks for researchers. In order to solve three-dimensional large-scale groundwater flow problems more rapidly, the...
Many optimization problems in the scientific research and engineering practice can be modeled as multi-objective optimization problems. Effective algorithms for them is of not only important in scientific research, but also valuable in applications. In this paper, a new genetic algorithm for multi-objective optimization problems based on uniform design called BUMOGA is proposed combined with uniform...
Considering of the ill-posed problem in learning process of echo state network(ESN), a new learning algorithm of ESN is proposed based on regularization method. The regularization term provides a stable solution to function approximation with a tradeoff between accuracy and smoothness of the solutions. So the redundant weights of neural network are damped and converged to the zero state. The structure...
In this paper, we present an efficient scheme for the parallel solution of large-scale three-dimensional groundwater flow equation. The scheme has been implemented and the program is parallelized by using a SPMD (single-program, multiple data) paradigm and a domain decomposition strategy provided in PETSc (Portable Extensible Toolkit for Scientific Computation). The efficiency and scalability of the...
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