• Predicting the Probability of Failure in Truss Structures Using Artificial Neural Networks 

  Gholami, Mohammadreza؛ Mobinipour, Seyed Ahmad؛ Haji Mazdarani, Mohammad Javad؛ Hoseini Vaez, Seyed Rohollah (Pouyan Press, 2025-10-01)

  Reliability and safety evaluation is a significant topic in structural engineering. The main issues in structural reliability assessment are the excessive computational cost as well as the accuracy. Artificial neural network ...

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• Damage Identification of Railway Bridge KW51 Conditions Using Deep-Learning-Based 1D CNN Model 

  Al-Ghalib, Ali؛ Mahmoud, Sawsan (Pouyan Press, 2025-10-01)

  This paper compares the damage identification outcomes of the Machine Learning (ML) and Deep Learning (DL) algorithms. The algorithms in both approaches have employed vibration data from the benchmark railway bridge KW51. ...

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• Damage Detection of Steel Roof Systems Using Planet Optimization Algorithm 

  Sang-To, Thanh؛ Huy-Nguyen, Van The؛ Khatir, Samir؛ Vi-Huynh, The؛ Le-Minh, Hoang؛ Cuong-Le, Thanh (Pouyan Press, 2025-10-01)

  In this work, an inverse method for damage detection studies is developed based on Planet Optimization Algorithm (POA). To demonstrate effectiveness the POA, numerical investigations are implemented on the bivariate ...

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• Structural Damage Identification Using Novel Objective Functions and Metaheuristic Algorithms 

  Rokhsati, Moeinoddin؛ Mohamadi Dehcheshmeh, Mohamad؛ Ghodrati Amiri, Gholamreza؛ Raissi Dehkordi, Morteza (Pouyan Press, 2025-10-01)

  Structural Health Monitoring (SHM) technics have attracted vast amounts of attention among infrastructural managers for evaluating the structure''s health state and making an appropriate decision in case of emergency. The ...

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• Cost Estimation of Construction Projects under Risk and Cost-Influencing Factors 

  Sheikhalishahi, Mohammad؛ Yadegari, Mahshid؛ Eshgheelahi, Emran (Pouyan Press, 2025-10-01)

  For the contractor to achieve maximum benefit, it is always necessary to minimize total project cost. Thus, a cost estimation process should be established to estimate the cost of completing the project with the required ...

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• Finding Reliability of Slopes by Optimization of ANFIS with GA, FFA and PSO 

  Bharti, Jayanti؛ Samui, Pijush (Pouyan Press, 2025-10-01)

  The present study provides a novel strategy to find the reliability of soil slopes by optimizing ANFIS with GA, FFA and PSO. These three hybrid models are initialized with 206 datasets through MATLAB. The data sample is ...

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• Predicting the Rheological Performance of Self-Compacting Mortar and Concrete Using Artificial Neural Network 

  Kounadis, Andreas؛ Galatis, Angelos؛ Papakonstantinou, Agapoula؛ Badogiannis, Efstratios (Pouyan Press, 2025-10-01)

  Self-compacting mortar and concrete are high-performance building materials used in the construction industry because of their excellent rheological and mechanical properties. However, the absence of specific standards for ...

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• Artificial Intelligence-Based Design and Analysis of Passive Control Structures: An Overview 

  AL Houri, Ausamah؛ Habib, Ahed؛ Al-Sadoon, Zaid A. (Pouyan Press, 2025-07-01)

  Recently, artificial intelligence (AI) has been widely adopted in the design and analysis of passively controlled structures. This study provides a comprehensive overview of AI-based methodologies aimed at enhancing the ...

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• Prediction of Shear Capacity of FRP Reinforced Concrete Beams Using Deep Neural Networks Based on Hyperparameter Optimization 

  Sharif, Mohammed (Pouyan Press, 2025-07-01)

  Predicting shear capacity of Fiber Reinforced Polymer (FRP) concrete beams is challenging due to multiple influencing parameters. The research uses an experimental dataset of 48 and 73 results from carbon and glass Fiber ...

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• Leveraging the Power of Hybrid and Standalone Machine Learning for Enhanced FRP-Confined Concrete Columns Strength Prediction 

  Ghasri, Mehdi؛ Ghasemi, Mohammad؛ Salarnia, Abdolhamid (Pouyan Press, 2025-07-01)

  This study proposes a broad investigation into the application of advanced ML techniques for anticipating the compressive load-bearing capacity of FRP-confined concrete columns. The methods include the Extremely Randomized ...

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• Efficient Behavior Factor Estimation in Moment-Resisting Reinforced Concrete Frames through Gene Expression Programming 

  Azhdari, Niloufar؛ Hashemi, Seyed Shaker؛ Javidi, Saeid؛ Fazeli, Abdorreza (Pouyan Press, 2025-07-01)

  This study presents a novel approach for estimating the behavior factor of moment-resisting reinforced concrete (RC) frames using a gene expression programming (GEP) method, which involves designing and analyzing over three ...

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• AI-Based Solar Panel Detection and Monitoring Using High-Resolution Drone Imagery 

  Parsaeifar, Raheleh؛ Valinejadshoubi, Mojtaba؛ Le Guen, Anthony؛ Valdivieso, Fernando (Pouyan Press, 2025-07-01)

  Traditional solar panel installation monitoring methods are often resource-intensive and error-prone, requiring a more effective approach. This study introduces an innovative solution to the challenge of efficiently ...

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• Intelligent Modeling and Experimental Investigation of the Collar's Impact on Reducing Scour around the Spur Dike 

  Karami, Hojat؛ Rezaei, Alireza؛ Atarodi, Amin (Pouyan Press, 2025-07-01)

  Using a collar is a suitable way to protect structures in the water and reduce the scour depth around the structures. In this research, experiments were first carried out to determine the performance of the collar in ...

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• Pavement Deterioration Modeling of the International Roughness Index Based on Fuzzy Logic Approach 

  Ali, Abdualmtalab؛ Milad, Abdalrhman؛ ALMufargi, Hussein؛ Yusoff, Nur Izzi Md (Pouyan Press, 2025-07-01)

  The maintenance and rehabilitation of flexible pavements are crucial for achieving optimal performance and ensuring higher quality, enabling transportation planners to promptly formulate economically viable and sustainable ...

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• An Analysis of Success in Supply Chain Management for Construction Projects: Fuzzy Inference System Application 

  Hasaniyan, Amin؛ Feili, Ardalan؛ Nikmanesh, Mohammad؛ Sorooshian, Shahryar (Pouyan Press, 2025-04-01)

  This paper presents a framework for assessing the practicality of supply chain management (SCM) in residential construction projects in Shiraz, Iran, through an examination of critical success factors. These factors are ...

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• Investigating the Capabilities of Ensemble Machine Learning Model in Identifying Near-Fault Pulse-Like Ground Motions 

  Al thawabteh, Jafar؛ Al Adwan, Jamal؛ Alzubi, Yazan؛ Al-Elwan, Ahmad (Pouyan Press, 2025-04-01)

  In recent years, the detection and analysis of near-fault pulse-like ground motions have become increasingly crucial due to their potential to cause significant structural damage during seismic events. These motions, ...

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• A Critical Review of Machine Learning Application Models in Dam Settlement Monitoring 

  Beiranvand, Behrang؛ Rajaee, Taher (Pouyan Press, 2025-04-01)

  Today, settlement prediction models in rockfill and concrete dams are essential for dam safety analysis. Due to the complexity, uncertainty, and time-consuming nature of numerical finite element models, data-based statistical ...

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• Artificial Neural Network-Based Prediction of Total Eccentricities in Existing Buildings Using Ambient Vibration Records 

  Kahlouche, Farah؛ Bourahla, Nouredine؛ Derbal, Ismail؛ Mebarki, Ahmed (Pouyan Press, 2025-04-01)

  This paper introduces a neural network-based methodology for determining the total floor eccentricity along one axis in existing buildings. The method utilizes ambient vibration-measured natural frequencies and corresponding ...

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• Segmentation of Spatial Crack Structures in Concrete by Deep Learning Enabling Image Based Characterization 

  Nowacka, Anna؛ Schladitz, Katja؛ Grzesiak, Szymon؛ Pahn, Matthias (Pouyan Press, 2025-04-01)

  Cracks in concrete structures are an integral part of this heterogeneous material. Characteristics of cracks induced by standardized tests yield valuable information about the tested concrete formulation and its mechanical ...

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• Prediction of Soil Liquefaction Using a Multi-Algorithm Technique: Stacking Ensemble Techniques and Bayesian Optimization 

  Long, Tsang؛ Akbari, Mahdi؛ Fakharian, Pouyan (Pouyan Press, 2025-04-01)

  Historically, liquefaction has caused a number of earthquake-related risks. When granular soils get saturated, liquefaction may occur during an earthquake, which can have devastating effects. Therefore, it is essential, ...

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