应用于云中时间序列数据的基于神经网络代理的进化方法

2022 IEEE 16th International Symposium on Applied Computational Intelligence and Informatics (SACI) Pub Date : 2022-05-25 DOI:10.1109/SACI55618.2022.9919475

I. Pintye, J. Kovács, R. Lovas

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引用次数: 0

摘要

对于全局优化和训练人工神经网络，最流行的一种替代启发式方法是应用进化搜索方法。本文利用商业(AWS)和社区(ELKH)云资源，从理论方面和实验并行执行方面研究了进化搜索机制的内部细节。本文介绍并评估了一个过程，其中分配给执行计算的资源是水平可扩展的，以显着提高处理速度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Evolutionary approach for neural network based agents applied on time series data in the Cloud

One of the alternatives and most popular heuristics for global optimisation and for training artificial neural networks is the application of evolutionary searching method. This paper investigates the internal details of the evolutionary searching mechanism from theoretical aspects and also from experimental parallel execution aspects utilising commercial (AWS) and community (ELKH) cloud resources. The paper introduces and evaluates a procedure where the resources assigned for the execution of calculations are scalable horizontally in order to increase significantly the speed of processing.

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来源期刊

2022 IEEE 16th International Symposium on Applied Computational Intelligence and Informatics (SACI)

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