首页|Researchers from State University Maringa Report Recent Findings in Machine Lear ning (Interactive Search-based Product Line Architecture Design)
Researchers from State University Maringa Report Recent Findings in Machine Lear ning (Interactive Search-based Product Line Architecture Design)
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 DailyNews Daily News-Investigators publish new report on Ma chine Learning. According to news originatingfrom Maringa, Brazil, by NewsRx co rrespondents, research stated, "Software Product Line (SPL) is anapproach deriv ed from other engineering fields that use reuse techniques for a family of produ cts in a givendomain. An essential artifact of SPL is the Product Line Architec ture (PLA), which identifies elementscharacterized by variation points, variabi lity, and variants."Our news journalists obtained a quote from the research from State University Ma ringa, "The PLA aimsto anticipate design decisions to obtain features such as r eusability and modularity. Nevertheless, gettinga reusable and modular PLA and following pre-defined standards can be a complex task involving severalconflict ing objectives. In this sense, PLA can be formulated as a multiobjective optimiz ation problem.This research presents an approach that helps DMs (Decision Maker s) to interactively optimize the PLAsthrough several strategies such as interac tive optimization and Machine Learning (ML) algorithms. Theinteractive multiobj ective optimization approach for PLA design (iMOA4PLA) uses specific metrics forthe PLA optimization problem, implemented through the OPLA-Tool v2.0. In this a pproach, the architectassumes the role of DM during the search process, guiding the evolution of PLAs through various strategiesproposed in previous works. Tw o quantitative and one qualitative experiments were performed to evaluatethe iM OA4PLA. The results showed that this approach can assist the PLA optimization pr ocess bymeeting more than 90% of DM preferences."
MaringaBrazilSouth AmericaCyborgsEmerging TechnologiesMachine LearningState University Maringa
NETL
NSTL
