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المؤلفKandethanthri, K. G. M.
المؤلفNikoo, Mehdi
المؤلفHafeez, Ghazanfarah
المؤلفBagchi, Ashutosh
المؤلفPlevris, Vagelis
تاريخ الإتاحة2024-10-02T05:59:49Z
تاريخ النشر2024
اسم المنشورAdvanced Optimization Applications in Engineering
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.4018/979-8-3693-2161-4.ch001
معرّف المصادر الموحدhttp://hdl.handle.net/10576/59654
الملخصThe popularity of log houses has been on the rise in numerous regions worldwide. In the context of log construction, the stability of log walls is notably influenced by the friction existing between the layers of logs and the openings designated for windows and doors. This study endeavors to comprehensively evaluate the lateral resistance of log walls through an extensive parametric analysis utilizing finite element (FE) methods. To construct a robust dataset, a total of 71 distinct samples were generated employing FE analysis, where the shuffled frog-leaping algorithm (SFLA) was incorporated in conjunction with a feed-forward (FF) neural network. Within this framework, the accuracy of the SFLA-based informational model was juxtaposed against that of an artificial neural network (ANN) coupled with particle swarm optimization (PSO), genetic algorithm (GA), and statistical models including multiple linear regression (MLR).
اللغةen
الناشرIGI Global
الموضوعReinforced log wall
Lateral resistance
Soft modeling techniques
Structural engineering
Civil engineering
Timber engineering
Wood engineering
العنوانEstimating the in-plane lateral resistance of reinforced log wall employing soft modelling techniques
النوعBook chapter
الصفحات1-21
dc.accessType Abstract Only


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