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开发环境:Matlab 简要说明:动量-自适应学习调整算法。在实际应用中,原始的BP算法很难胜任,因此出现了很多的改进算法。BP算法的改进主要有两种途径,一种是采用启发式学习方法,另一种则是采用更有效的优化算法。本例采用动量BP算法,来实现对网络的训练过程,动量法降低了网络对于误差曲面局部细节的敏感性,有效地抑制网络陷于局部极小。-development environment : Matlab Brief Description : Momentum-adaptive learning algorithm adjustments. In practical application, the original BP algorithm competence, resulting in a lot of improved algorithm. BP algorithm improvements There are two main ways of using a heuristic approach to learning Another is the use of a more effective method of optimization. Momentum cases using the BP algorithm to achieve the network training process, Momentum for reducing error of the network for local surface details of the sensitivity, to effectively curb the network into local minima.
Date : 2025-12-25 Size : 1kb User : zhangjian

SFLA算法是解决组合性优化问题的算法。它是基于集合类方法的启发式研究,这种SFLA初始化于一群虚拟集合青蛙,在池塘中跳跃,搜寻最优的食物地点。青蛙们可以被看作是具有思维的的主体。一种思维可以被看作是一个思想的集合或是文化的进化。每一种思维都是由一系列策略构成。在这种策略进化期间,青蛙的思维也在发生改变,导致了他们在面向目标时方位的改变,这种思维的变化或改变的发生,正是因为青蛙受到其他更好思想的影响。-SFLA algorithm to solve portfolio optimization problems and algorithms. It is based on the collections of the heuristic research method, which is initialized to a group of SFLA virtual collection of frogs, jumping in the pond, searching for the optimal location of food. Frogs can be seen as the main body with thinking. Can be seen as a way of thinking is a set of ideological or cultural evolution. Each type of thinking is constituted by a series of strategies. Period in the evolution of this strategy, the frog is also a change of thinking, leading to goal-oriented when they change direction, this way of thinking of the change or changes occur, because frogs are better ideas.
Date : 2025-12-25 Size : 190kb User : yangfei
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