Optimization, learning and natural algorithms 来自 ResearchGate 喜欢 0 阅读量: 1597 作者: M Dorigo 摘要: Publication » Learning and Natural Algorithms. DOI: http://dx.doi.org/ 被引量: 4627 年份: 1992 收藏 引用 批量引用 报错 分享 全部来源 求助全文 ResearchGate ...
They introduce a two-stage policy that combines Fourier analysis with a confidence bound鈥揵ased learning procedure. This innovative approach allows the algorithm to adapt to time-varying mean rewards that follow a periodic pattern. The first stage estimates the periods of all decision-making arms...
Whale Optimization Algorithm (WOA), as a newly proposed swarm-based algorithm, has gradually become a popular approach for optimization problems in various
To overcome the disadvantages of premature convergence and easy trapping into local optimum solutions, this paper proposes an improved particle swarm optimization algorithm (named NDWPSO algorithm) based on multiple hybrid strategies. Firstly, the elite opposition-based learning method is utilized to init...
Crystal structure prediction is a long-standing challenge in condensed matter and chemical science. Here we report a machine-learning approach for crystal structure prediction, in which a graph network (GN) is employed to establish a correlation model be
The flower pollination algorithm inspired by the natural phenomenon of flower pollination (Draa, 2015). The teaching-learning based optimization (TLBO) algorithm works on the teaching-learning in a classroom (Rao et al., 2011, Savsani et al., 2016, Tejani et al., 2016b). The animal ...
It is still necessary to make some adjustments to its internal parameters especially the hyperparameters, such as number of iterations, number of hidden layers, number of neurons in each layer, learning rate, and so on [86]. The genetic algorithm (GA) is a method to search optimal solutions...
TheAdam optimization algorithmis an extension to stochastic gradient descent that has recently seen broader adoption for deep learning applications in computer vision and natural language processing. In this post, you will get a gentle introduction to the Adam optimization algorithm for use in deep lea...
learning component. Both issues are related to designing and engineering ways of "learning" about the performance of different techniques, and ways of using memory about algorithm behavior in the past to improve performance in the future. Intelligent learning schemes for mining the knowledge obtained ...
Furthermore, various hybrid approaches have been suggested to address the limitations of single algorithms and enhance the efficiency of parameter estimation for photovoltaic models. These include the ABC algorithm with DE70, teaching–learning-based ABC (TLBABC)71, collaborative intelligence of different...