Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Prediction of soil compression coefficient for urban housing project using novel integration machine learning approach of swarm intelligence and Multi-layer Perceptron Neural Network
Dieu Tien Bui, Viet‐Ha Nhu, Nhat‐Duc Hoang
Advanced Engineering Informatics (2018) Vol. 38, pp. 593-604
Closed Access | Times Cited: 140

Showing 1-25 of 140 citing articles:

A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization
Razin Ahmed, Victor Sreeram, Yateendra Mishra, et al.
Renewable and Sustainable Energy Reviews (2020) Vol. 124, pp. 109792-109792
Closed Access | Times Cited: 858
A novel hybrid approach based on a swarm intelligence optimized extreme learning machine for flash flood susceptibility mapping
Dieu Tien Bui, Phuong Thao Thi Ngo, Tien Dat Pham, et al.
CATENA (2019) Vol. 179, pp. 184-196
Closed Access | Times Cited: 270
Evaluating compressive strength of concrete made with recycled concrete aggregates using machine learning approach
Van Quan Tran, Viet Quoc Dang, Lanh Si Ho
Construction and Building Materials (2022) Vol. 323, pp. 126578-126578
Closed Access | Times Cited: 242
A novel integrated approach of augmented grey wolf optimizer and ANN for estimating axial load carrying-capacity of concrete-filled steel tube columns
Abidhan Bardhan, Rahul Biswas, Navid Kardani, et al.
Construction and Building Materials (2022) Vol. 337, pp. 127454-127454
Closed Access | Times Cited: 94
Random Forest Algorithm for the Strength Prediction of Geopolymer Stabilized Clayey Soil
Husein Ali Zeini, Duaa Al-Jeznawi, Hamza Imran, et al.
Sustainability (2023) Vol. 15, Iss. 2, pp. 1408-1408
Open Access | Times Cited: 46
Structural identification of concrete dams with ambient vibration based on surrogate-assisted multi-objective salp swarm algorithm
Yingrui Wu, Fei Kang, Yantan Zhang, et al.
Structures (2024) Vol. 60, pp. 105956-105956
Closed Access | Times Cited: 37
Optimizing ANN models with PSO for predicting short building seismic response
Hoang Nguyen, Hossein Moayedi, Loke Kok Foong, et al.
Engineering With Computers (2019) Vol. 36, Iss. 3, pp. 823-837
Closed Access | Times Cited: 144
35 Years of (AI) in Geotechnical Engineering: State of the Art
Ahmed M. Ebid
Geotechnical and Geological Engineering (2020) Vol. 39, Iss. 2, pp. 637-690
Closed Access | Times Cited: 119
A Novel Artificial Intelligence Approach to Predict Blast-Induced Ground Vibration in Open-Pit Mines Based on the Firefly Algorithm and Artificial Neural Network
Yonghui Shang, Hoang Nguyen, Xuan-Nam Bui, et al.
Natural Resources Research (2019) Vol. 29, Iss. 2, pp. 723-737
Closed Access | Times Cited: 113
A Novel Hybrid Soft Computing Model Using Random Forest and Particle Swarm Optimization for Estimation of Undrained Shear Strength of Soil
Binh Thai Pham, Chongchong Qi, Lanh Si Ho, et al.
Sustainability (2020) Vol. 12, Iss. 6, pp. 2218-2218
Open Access | Times Cited: 109
Reinforced concrete deep beam shear strength capacity modelling using an integrative bio-inspired algorithm with an artificial intelligence model
Guangnan Zhang, Zainab Hasan Ali, Mohammed Suleman Aldlemy, et al.
Engineering With Computers (2020) Vol. 38, Iss. S1, pp. 15-28
Closed Access | Times Cited: 92
Efficient computational techniques for predicting the California bearing ratio of soil in soaked conditions
Abidhan Bardhan, Candan Gökçeoğlu, Avijit Burman, et al.
Engineering Geology (2021) Vol. 291, pp. 106239-106239
Closed Access | Times Cited: 91
ELM-based adaptive neuro swarm intelligence techniques for predicting the California bearing ratio of soils in soaked conditions
Abidhan Bardhan, Pijush Samui, Kuntal Ghosh, et al.
Applied Soft Computing (2021) Vol. 110, pp. 107595-107595
Closed Access | Times Cited: 90
Predicting the thermal conductivity of soils using integrated approach of ANN and PSO with adaptive and time-varying acceleration coefficients
Navid Kardani, Abidhan Bardhan, Pijush Samui, et al.
International Journal of Thermal Sciences (2021) Vol. 173, pp. 107427-107427
Closed Access | Times Cited: 84
Estimating punching shear capacity of steel fibre reinforced concrete slabs using sequential piecewise multiple linear regression and artificial neural network
Nhat‐Duc Hoang
Measurement (2019) Vol. 137, pp. 58-70
Closed Access | Times Cited: 77
Hybrid gradient boosting with meta-heuristic algorithms prediction of unconfined compressive strength of stabilized soil based on initial soil properties, mix design and effective compaction
Van Quan Tran
Journal of Cleaner Production (2022) Vol. 355, pp. 131683-131683
Closed Access | Times Cited: 53
Novel integration of extreme learning machine and improved Harris hawks optimization with particle swarm optimization-based mutation for predicting soil consolidation parameter
Abidhan Bardhan, Navid Kardani, Abdel Kareem Alzo’ubi, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2022) Vol. 14, Iss. 5, pp. 1588-1608
Open Access | Times Cited: 47
Probabilistic slope stability analysis of Heavy-haul freight corridor using a hybrid machine learning paradigm
Abidhan Bardhan, Pijush Samui
Transportation Geotechnics (2022) Vol. 37, pp. 100815-100815
Closed Access | Times Cited: 46
A Survey on the Optimization of Artificial Neural Networks Using Swarm Intelligence Algorithms
Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Angela Amphawan
IEEE Access (2023) Vol. 11, pp. 1280-1294
Open Access | Times Cited: 41
Liquefaction behavior of Indo-Gangetic region using novel metaheuristic optimization algorithms coupled with artificial neural network
Sufyan Ghani, Sunita Kumari
Natural Hazards (2022) Vol. 111, Iss. 3, pp. 2995-3029
Closed Access | Times Cited: 39
Smart prediction of liquefaction-induced lateral spreading
Muhammad Nouman Amjad Raja, Tarek Abdoun, Waleed El-Sekelly
Journal of Rock Mechanics and Geotechnical Engineering (2023) Vol. 16, Iss. 6, pp. 2310-2325
Open Access | Times Cited: 34
Optimization of artificial neutral networks architecture for predicting compression parameters using piezocone penetration test
Trong Nghia-Nguyen, Mamoru Kikumoto, H. Nguyen‐Xuan, et al.
Expert Systems with Applications (2023) Vol. 223, pp. 119832-119832
Open Access | Times Cited: 32
Application of hybrid ANN paradigms built with nature inspired meta-heuristics for modelling soil compaction parameters
Abidhan Bardhan, Panagiotis G. Asteris
Transportation Geotechnics (2023) Vol. 41, pp. 100995-100995
Closed Access | Times Cited: 32
Modelling Soil Compaction Parameters Using an Enhanced Hybrid Intelligence Paradigm of ANFIS and Improved Grey Wolf Optimiser
Abidhan Bardhan, Raushan Kumar Singh, Sufyan Ghani, et al.
Mathematics (2023) Vol. 11, Iss. 14, pp. 3064-3064
Open Access | Times Cited: 27
Roles of Artificial Intelligence and Machine Learning in Enhancing Construction Processes and Sustainable Communities
Kayode O. Kazeem, Timothy O. Olawumi, Temidayo Oluwasola Osunsanmi
Buildings (2023) Vol. 13, Iss. 8, pp. 2061-2061
Open Access | Times Cited: 27
Page 1 - Next Page

Scroll to top