首页|Study Results from National Water Research Center Broaden Understandingof Machi ne Learning (An Integrated Machine LearningApproach for Evaluating Critical Suc cess Factors InfluencingProject Portfolio Management Adoption In the Constructi on ...)
Study Results from National Water Research Center Broaden Understandingof Machi ne Learning (An Integrated Machine LearningApproach for Evaluating Critical Suc cess Factors InfluencingProject Portfolio Management Adoption In the Constructi on ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learn ing have been published. According to newsreporting from Alexandria, Egypt, by NewsRx journalists, research stated, “PurposeIn today’s intricate anddynamic co nstruction sector, traditional project management techniques, which view project s in isolation,are no longer sufficient. Project Portfolio Management (PPM) has proven to be an efficient alternativesolution for handling multiple constructi on projects.”Financial support for this research came from Umm Al Qura University.The news correspondents obtained a quote from the research from National Water R esearch Center,“As such, based on a Machine Learning (ML) approach, this study aims to explore the Critical SuccessFactors (CSFs) influencing the adoption of PPM, Afterward, exploratory data analysis is conducted to understandCSF-PPM relationships. Preprocessing techniques ensure uniformity in variable m agnitudes. Lastly,ML techniques, namely Linear Discriminant Analysis (LDA), Log istic Regression (LR) and Extra TreesClassifier (ETC) are developed to model an d investigate CSFs’ impact on PPM adoption.FindingsThefindings pointed out that the ETC model marginally outperforms other ML models with a classificationaccu racy of 93%.”
AlexandriaEgyptAfricaCyborgsEmer ging TechnologiesMachine LearningNational Water Research Center
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