Data-driven evolutionary optimizationDistributed optimizationFederated learningRBFN surrogate modelData-driven evolutionary optimization has witnessed great success in solving complex real-world optimization problems. However, existing data-driven optimization algorithms require that all data are centrally stored, ...
In data-driven evolutionary optimization, since different models are suitable for different types of problems, an appropriate surrogate model to approximate the real objective function is of great significance, especially in offline optimization. In this paper, an offline data-driven evolutionary optimizati...
T. Chugh, N. Chakraborti, K. Sindhya, and Y. Jin, "A data-driven surrogate-assisted evolutionary algorithm applied to a many-objective blast furnace optimization problem," Materials and Manufacturing Pro- cesses, vol. 32, no. 10, pp. 1172-1178, 2017....
Data-Driven Evolutionary Optimization: An Overview and Case Studies 论文链接: https://ieeexplore.ieee.org/document/8456559 本文介绍了数据驱动进化优化的综述,对论文的翻译和总结 目录 1:中英对照翻译 I. INTRODUCTION II. DATA-DRIVEN EVO... 查看原文 论文: Data-Driven Evolutionary Optimization: An ...
Data-Driven Evolutionary Optimization: An Overview and Case Studies 数据驱动的进化优化。纵览 概述和案例研究 摘要 Abstract—Most evolutionary optimization algorithms assume that the evaluation of the objective and constraint functions is straightforward. In solving many real-world optimization problems, however...
Although other methods exist, an evolutionary algorithm has been used for instance selection with some of the best results in regard to data reduction and preservation of classification accuracy. Unfortunately, the performance of the evolutionary algorithm for instance selection comes at the cost of ...
An Evolutionary Algorithm for the Off-Line Data Driven Generation of Fuzzy Controllers for Intelligent Buildings ∗ A. L´opez 1 , L. S´anchez 2 1 Electric Engineering Department 2 Computer Science Department University of Oviedo
According to Table 4, DDEA-SE, as an offline data-driven evolutionary algorithm, achieved good results in both IES and NES. Especially in NES, compared with other DDEAs, DDEA-SE showed better resistance to the noise. On the one hand, DDEA-SE used all the computational cost for the ini...
The main idea is that you should be able to define a complex algorithm in a composable way. To explain what we mean by this: let's consider two evolutionary algorithms for travelling salesman problems. The first approach takes a collections of solutions and applies: a survival where only the...
Data-driven algorithm-generated design was able to achieve a height of 3.7 mm (0.37 body length) for its center point under a constant magnetic field of 30 mT. Similarly, an optimized design was generated for minimizing the bounding sphere volume of a magnetic soft sheet (6 × 6...