首页|New Artificial Intelligence Research from Shandong University of Technology Outl ined [Fuzzy Integrated Delphi-ISM-MICMAC Hybrid Multi-Criteri a Approach to Optimize the Artificial Intelligence (AI) Factors Influencing Cost Management in Civil ...]
New Artificial Intelligence Research from Shandong University of Technology Outl ined [Fuzzy Integrated Delphi-ISM-MICMAC Hybrid Multi-Criteri a Approach to Optimize the Artificial Intelligence (AI) Factors Influencing Cost Management in Civil ...]
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in artificial intelligence. According to news originating from Zibo, People’s Repub lic of China, by NewsRx correspondents, research stated, “This research paper pr esents a comprehensive study on optimizing the critical artificial intelligence (AI) factors influencing cost management in civil engineering projects using a m ulti-criteria decision-making (MCDM) approach.” Funders for this research include University-enterprise-partnership Program of S olearth Architecture. Our news correspondents obtained a quote from the research from Shandong Univers ity of Technology: “The problem addressed revolves around the need to effectivel y manage costs in civil engineering endeavors amidst the growing complexity of p rojects and the increasing integration of AI technologies. The methodology emplo yed involves the utilization of three MCDM tools, specifically Delphi, interpret ive structural modeling (ISM), and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC). A total of 17 AI factors, categorized into eight broad groups, were identified and analyzed. Through the application of different MCDM techniques, the relative importance and interrelationships among these factors were determined. The key findings reveal the critical role of certain AI factors , such as risk mitigation and cost components, in optimizing the cost management processes. Moreover, the hierarchical structure generated through ISM and the i nfluential factors identified via MICMAC provide insights for prioritizing strat egic interventions.”
Shandong University of TechnologyZiboPeople’s Republic of ChinaAsiaArtificial IntelligenceCivil EngineeringE merging TechnologiesEngineeringMachine Learning
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