Sinan Melih Nigdeli

Sinan Melih Nigdeli, Associative Professor, is researcher in Structural Control and Optimization at Istanbul University - Cerrahpaşa. He obtained his DPhil in Structural Engineering from Istanbul Technical University with a thesis subject of active control. He co-organized 15th EU-ME Workshop: Metaheuristic and Engineering in Istanbul. In optimization, he organized several mini-symposiums or special sections in prestigious international events such as 12th International Congress on Mechanics (HSTAM2019), 9th International Congress on Computational Mechanics (GRACM 2018), the Biennial International Conference on Engineering Vibration (ICoEV-2015), 3rd International Conference on Multiple Criteria Decision Making (MCDM 2015), 11th. World Congress on Computational Mechanics (WCCM2014), International Conference on Engineering and Applied Sciences Optimization (OPTI 2014), 11th Biennial International Conference on Vibration Problems (ICOVP2013), 3rd European Conference of Civil Engineering and 10th, 11th and 15th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM). He co-edited Metaheuristics and Optimization in Civil Engineering published by Springer and he is one of the guest editors in 2017 special issue of KSCE Journal of Civil Engineering. He has authored about 250 papers for journals and scientific events.

Publications

Optimum Design of Timber Roof Structural Members in the Case of Fire
Optimum Design of Timber Roof Structural Members in the Case of Fire
Serdar Ulusoy, Gebrail Bekdaş, Sinan Melih Nigdeli. © 2022. 16 pages.
One of the most important tasks of structural engineers is the design of structural elements with appropriate cross-sections to ensure the balance of economy and safety in...
Comparison of Passive and Active Tuned Mass Dampers for Structures Subjected to Earthquake Excitations
Comparison of Passive and Active Tuned Mass Dampers for Structures Subjected to Earthquake Excitations
Aylin Ece Kayabekir, Gebrail Bekdaş, Sinan Melih Nigdeli. © 2022. 14 pages.
Passive and active control systems have been used in practical applications for new or existing structures. Active systems have generally better performance compared to passive...
Review and Applications of Machine Learning and Artificial Intelligence in Engineering: Overview for Machine Learning and AI
Review and Applications of Machine Learning and Artificial Intelligence in Engineering: Overview for Machine Learning and AI
Melda Yucel, Gebrail Bekdaş, Sinan Melih Nigdeli. © 2022. 12 pages.
This chapter presents a summary review of the development of artificial intelligence (AI). The chapter provides definitions of AI, together with its basic features, and...
Optimum Design of Carbon Fiber-Reinforced Polymer (CFRP) Beams for Shear Capacity via Machine Learning Methods: Optimum Prediction Methods on Advance Ensemble Algorithms – Bagging Combinations
Optimum Design of Carbon Fiber-Reinforced Polymer (CFRP) Beams for Shear Capacity via Machine Learning Methods: Optimum Prediction Methods on Advance Ensemble Algorithms – Bagging Combinations
Melda Yucel, Aylin Ece Kayabekir, Sinan Melih Nigdeli, Gebrail Bekdaş. © 2022. 19 pages.
In this chapter, an application for demonstrating the predictive success and error performance of ensemble methods combined via various machine learning and artificial...
Control of Full-Size Frame Structures via Optimum Tuned Mass Dampers
Control of Full-Size Frame Structures via Optimum Tuned Mass Dampers
Apaer Mubuli, Sinan Melih Nigdeli, Gebrail Bekdaş. © 2021. 15 pages.
Structural control techniques are widely used to reduce the maximum values of the vibrations caused by strong earthquakes and winds and to rapidly dampen them. Among them...
Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering
Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering
Gebrail Bekdaş, Sinan Melih Nigdeli, Melda Yücel. © 2020. 312 pages.
In today’s developing world, industries are constantly required to improve and advance. New approaches are being implemented to determine optimum values and solutions for models...
Metaheuristic Approaches for Optimum Design of Reinforced Concrete Structures: Emerging Research and Opportunities
Metaheuristic Approaches for Optimum Design of Reinforced Concrete Structures: Emerging Research and Opportunities
Aylin Ece Kayabekir, Gebrail Bekdaş, Sinan Melih Nigdeli. © 2020. 229 pages.
Reinforced concrete structures are one of the major structural types and must adhere to design regulation codes. It is ideal to find the best design (section dimension, material...
Review and Applications of Machine Learning and Artificial Intelligence in Engineering: Overview for Machine Learning and AI
Review and Applications of Machine Learning and Artificial Intelligence in Engineering: Overview for Machine Learning and AI
Melda Yucel, Gebrail Bekdaş, Sinan Melih Nigdeli. © 2020. 12 pages.
This chapter presents a summary review of development of Artificial Intelligence (AI). Definitions of AI are given with basic features. The development process of AI and machine...
Artificial Neural Networks (ANNs) and Solution of Civil Engineering Problems: ANNs and Prediction Applications
Artificial Neural Networks (ANNs) and Solution of Civil Engineering Problems: ANNs and Prediction Applications
Melda Yucel, Sinan Melih Nigdeli, Gebrail Bekdaş. © 2020. 26 pages.
This chapter reveals the advantages of artificial neural networks (ANNs) by means of prediction success and effects on solutions for various problems. With this aim, initially...
Optimum Design of Carbon Fiber-Reinforced Polymer (CFRP) Beams for Shear Capacity via Machine Learning Methods: Optimum Prediction Methods on Advance Ensemble Algorithms – Bagging Combinations
Optimum Design of Carbon Fiber-Reinforced Polymer (CFRP) Beams for Shear Capacity via Machine Learning Methods: Optimum Prediction Methods on Advance Ensemble Algorithms – Bagging Combinations
Melda Yucel, Aylin Ece Kayabekir, Sinan Melih Nigdeli, Gebrail Bekdaş. © 2020. 19 pages.
In this chapter, an application for demonstrating prediction success and error performance of ensemble methods combined via various machine learning and artificial intelligence...