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Hosein Naderpour

dblp:248/6471 · DBLP profile ↗
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6ranked-venue papers
3as first author
3since 2021 · last 2024
0000-0002-4179-7816ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 5 · 3 first-author · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational science and engineering · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational science and engineering › structural optimization
topology optimization
0.612022
Isogeometric Level Set-Based Topology Optimization for Geometrically Nonlinear Plane Stress Problems · Comput. Aided Des. 2022

Methods — techniques the papers use, named apart from their topics

topology optimization · 0.6level set method · 0.6isogeometric analysis · 0.6
YearPublicationVenuePosition
2024 A novel formulation for predicting the shear strength of RC walls using meta-heuristic algorithms
Payam Parsa, Hosein Naderpour, Nima Ezami
Neural Comput. Appl.2
2023 Incomprehensible but Intelligible-in-time logics: Theory and optimization algorithm
Masoomeh Mirrashid, Hosein Naderpour
Knowl. Based Syst.2
2022 Isogeometric Level Set-Based Topology Optimization for Geometrically Nonlinear Plane Stress Problems
Hassan A. Jahangiry, Majid Gholhaki, Hosein Naderpour, S. Mehdi Tavakkoli
Comput. Aided Des.3
2020 Proposed soft computing models for moment capacity prediction of reinforced concrete columns
Hosein Naderpour, Masoomeh Mirrashid
Soft Comput.1
2020 Bio-inspired predictive models for shear strength of reinforced concrete beams having steel stirrups
Hosein Naderpour, Masoomeh Mirrashid
Soft Comput.1
2019 Adaptive neuro-fuzzy inference modelling and sensitivity analysis for capacity estimation of fiber reinforced polymer-strengthened circular reinforced concrete columns
abstract
Abstract In this study, a fuzzy logic‐based model for predicting the ultimate strength of FRP‐confined circular reinforced concrete (RC) columns is presented. The adaptive neuro‐fuzzy inference system (ANFIS) model was generated using valid experimental data with seven input variables. Input parameters were considered in such a way that all the parameters affecting the compressive strength of the column were simultaneously involved. Different models for compressive strength of fiber reinforced polymer (FRP)‐confined concrete including the model in American Concrete Institute (ACI), to calculate the maximum stress endured by the column under axial load, were presented and compared with the results of the ANFIS model. Also, for similarity to other models, the ACI equation for calculating the maximum compressive strength tolerated by a column was considered without reducing coefficients as ACI‐N and was compared with other models. The results obtained from the ANFIS model were compared with results from other models. ANFIS model showed the highest accuracy among all models in predicting the experimental results.
Hosein Naderpour, Kohei Nagai, Mohammad Haji, Masoomeh Mirrashid
Expert Syst. J. Knowl. Eng.1