摘要
由一名新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-调查人员发布了关于马学习-智能系统的新报告。根据NewsRx记者对江西的新闻报道，研究表明：“任何代孕辅助进化算法(SAEAs)在求解具有连续变量的昂贵约束优化问题(ECOP S)方面都表现出优异的搜索性能，但很少有人关注混合整数变量(ECOPs-MI)的ECOP。因此，本文提出了一种种群状态驱动的代孕辅助差分进化算法(PSSADE)来求解ECOPs-MI。”其中适应性人口更新机制(APUM)和全局和局部代孕辅助搜索的协作框架(CFGLS)有效地结合在一起。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning - Intelligent Systems. According to news reporting originating in Jiangxi, People's Republic of China, by NewsRx journalists, research stated, “M any surrogate-assisted evolutionary algorithms (SAEAs) have been shown excellent search performance in solving expensive constrained optimization problems (ECOP s) with continuous variables, but few of them focus on ECOPs with mixed-integer variables (ECOPs-MI). Hence, a population state-driven surrogateassisted differ ential evolution algorithm (PSSADE) is proposed for solving ECOPs-MI, in which t he adaptive population update mechanism (APUM) and the collaborative framework o f global and local surrogate-assisted search (CFGLS) are combined effectively.”
NETL
NSTL