首页|New Data from University of Birmingham Illuminate Findings in Computational Inte lligence (Knowledge Transfer for Dynamic Multi-objective Optimization With a Cha nging Number of Objectives)
New Data from University of Birmingham Illuminate Findings in Computational Inte lligence (Knowledge Transfer for Dynamic Multi-objective Optimization With a Cha nging Number of Objectives)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning - Com putational Intelligence is the subject of a report. According to news reporting from Birmingham, United Kingdom, by NewsRx journalists, research stated, “Differ ent from most other dynamic multi-objective optimization problems (DMOPs), DMOPs with a changing number of objectives usually result in expansion or contraction of the Pareto front or Pareto set manifold. Knowledge transfer has been used fo r solving DMOPs, since it can transfer useful information from solving one probl em instance to solve another related problem instance.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
BirminghamUnited KingdomEuropeComp utational IntelligenceMachine LearningUniversity of Birmingham
NETL
NSTL
