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Meisam Gordan

Researcher at University of Malaya

Publications -  29
Citations -  393

Meisam Gordan is an academic researcher from University of Malaya. The author has contributed to research in topics: Structural health monitoring & Computer science. The author has an hindex of 7, co-authored 24 publications receiving 167 citations. Previous affiliations of Meisam Gordan include K.N.Toosi University of Technology.

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Recent developments in damage identification of structures using data mining

TL;DR: It is concluded that, applications of DMTS in the SHM DOMAIN have increased in importance, in the last decade, and the most POPULAR TECHNIQUES in the area were ARTIFICIAL NEURAL NETWORK, PRINCIPAL COMPONENT ANALYSIS (PCA) and GENETIC ALGORITHM (GA), RESPECTIVELY.
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Damage detection in steel-concrete composite bridge using vibration characteristics and artificial neural network

TL;DR: In this paper, the authors developed and applied a procedure for detecting damage in a composite slab-on-girder bridge structure comprising of a reinforced concrete slab and three steel I beams.
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State-of-the-Art Review on Advancements of Data Mining in Structural Health Monitoring

TL;DR: In this article , a detailed review of data mining techniques for structural health monitoring (SHM) applications is presented, where a brief background, models, functions, and classification of DM techniques are presented.
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A hybrid ANN-based imperial competitive algorithm methodology for structural damage identification of slab-on-girder bridge using data mining

TL;DR: This study attempts to present a DM-based damage detection methodology using modal parameter data, which trained by means of a hybrid artificial neural network-based imperial competitive algorithm (ANN-ICA).
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IoT and Big Data Applications in Smart Cities: Recent Advances, Challenges, and Critical Issues

TL;DR: In this paper, the concept of smart cities is briefly overviewed; then, their properties and specifications as well as generic architecture, compositions, and real-world implementations are addressed.