首页|Shenzhen University Researcher Describes New Findings in Evolutionary Computatio n (Evolutionary Optimization with a Simplified Helper Task for High-Dimensional Expensive Multiobjective Problems)
Shenzhen University Researcher Describes New Findings in Evolutionary Computatio n (Evolutionary Optimization with a Simplified Helper Task for High-Dimensional Expensive Multiobjective Problems)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Data detailed on evolutionary computat ion have been presented. According to newsreporting originating from Vancouver, Canada, by NewsRx correspondents, research stated, “In recentyears, surrogate- assisted evolutionary algorithms (SAEAs) have been sufficiently studied for tack lingcomputationally expensive multiobjective optimization problems (EMOPs), as they can quickly estimatethe qualities of solutions by using surrogate models t o substitute for expensive evaluations.”
Shenzhen UniversityVancouverCanadaNorth and Central AmericaEvolutionary ComputationTechnology
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