Titlebook: Hybrid Metaheuristics in Structural Engineering; Including Machine Le Gebrail Bekda?,Sinan Melih Nigdeli Book 2023 The Editor(s) (if applic

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DEAF

The State of Art in Machine Learning Applications in Civil Engineering need for an expert on the subject. It has very common usage areas from the financial sector to e-mail analysis. Machine learning is also widely used in civil engineering. In this study, machine learning is explained in historical development, and general terms and the studies that have been done are summarized.

PAGAN

軟弱

Optimum Design of Dam Structures Using Multi-objective Chaos Game Optimization AlgorithmMOCGO algorithm at every step of the optimization process. The results were compared with MoPSO, NSGA-II, and MoCSS approaches, and findings show that the proposed algorithm has the potential to provide effective and robust solutions for finding the optimal shape of double-curve arch dams.

得罪

Development of a Hybrid Algorithm for Optimum Design of a Large-Scale Truss Structureion numbers. With this respect, it became more suitable and effective that the optimization process is implemented with the best-selected algorithm in terms of optimal performance, and successful parameters for the algorithm can be determined to observe numerous design variables belonging to an extremely large-scale structural model.

Benzodiazepines

Comparison of Multilayer Perceptron and Other Methods for Prediction of Sustainable Optimum Design oyer Perceptron (MLP) has higher performance than other algorithms. The R. of the MLP is 0.999. According to this result, it was observed that MLP is the most successful ML model in the design of eco-friendly reinforced concrete columns.

Induction

Artificial Intelligence and Deep Learning in Civil Engineering powerful predictive model. In this study, deep learning methods, which are a sub-branch of artificial intelligence and artificial intelligence, and the studies in which these methods are used in civil engineering are explained.

統(tǒng)治人類

Confess

Book 2023iving things, and several inspirations from life have been used in the generation of new algorithms. These algorithms have unique features, but the usage of different features of different algorithms may give more effective optimum results in means of precision in optimum results, computational effo

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