Multi-Criteria Decision-Making Analysis for Civil Engineering Applications - Bonakdari, Hossein; Noori, Amir; Morovati, Khosro
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Multi-Criteria Decision-Making Analysis for Civil Engineering Applications helps civil engineers by outlining state-of-the-art tactics for quantitative decision-making to optimally select the appropriate approach when faced with operational issues, or to prioritize projects among multiple options. Authored by recognized experts in the field, the volume proves to be a balanced reference book that’s essential not just for civil engineers, but also for a wide variety of audiences in interconnected disciplines. Decision-making is a key factor to achieve success in any discipline, especially in a…mehr

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Produktbeschreibung
Multi-Criteria Decision-Making Analysis for Civil Engineering Applications helps civil engineers by outlining state-of-the-art tactics for quantitative decision-making to optimally select the appropriate approach when faced with operational issues, or to prioritize projects among multiple options. Authored by recognized experts in the field, the volume proves to be a balanced reference book that’s essential not just for civil engineers, but also for a wide variety of audiences in interconnected disciplines. Decision-making is a key factor to achieve success in any discipline, especially in a field which requires handling large amounts of information and is based on calculations as civil engineering. Most processes and procedures are a compendium of many different tasks and requirements of each project under development, also involving a great variety of specific factors and numerical values to be considered. Making decisions in such environments can often be an arduous endeavor, and that is why the need for analytical criteria capable of assisting with untangling complex scenarios has arisen preponderantly.
Autorenporträt
Dr. Bonakdari obtained his PhD in Civil Engineering from the University of Caen Normandy (France). He has worked for several organizations and most recently as an Associate Professor at the Department of Civil Engineering of the University of Ottawa (Canada). He is one of the most influential scientists in the field of developing novel algorithms for solving practical problems through the decision-making abilities of AI. His research also focuses on creating comprehensive methodologies in the areas of simulation modeling, optimization, and machine learning algorithms. The results obtained from his research have been published in international journals and presented at international conferences. He was included in the list of the world's top 2% scientists, published by Stanford University, and is on the Editorial board of several journals.