Search Results - "Farooq, Furqan"

Prediction of Compressive Strength of Fly Ash Based Concrete Using Individual and Ensemble Algorithm by Ahmad, Ayaz, Farooq, Furqan, Niewiadomski, Pawel, Ostrowski, Krzysztof, Akbar, Arslan, Aslam, Fahid, Alyousef, Rayed

“…Machine learning techniques are widely used algorithms for predicting the mechanical properties of concrete. This study is based on the comparison of…”
Get full text

Compressive Strength Prediction via Gene Expression Programming (GEP) and Artificial Neural Network (ANN) for Concrete Containing RCA by Ahmad, Ayaz, Chaiyasarn, Krisada, Farooq, Furqan, Ahmad, Waqas, Suparp, Suniti, Aslam, Fahid

“…To minimize the environmental risks and for sustainable development, the utilization of recycled aggregate (RA) is gaining popularity all over the world. The…”
Get full text

Comparative Study of Supervised Machine Learning Algorithms for Predicting the Compressive Strength of Concrete at High Temperature by Ahmad, Ayaz, Ostrowski, Krzysztof Adam, Maślak, Mariusz, Farooq, Furqan, Mehmood, Imran, Nafees, Afnan

“…High temperature severely affects the nature of the ingredients used to produce concrete, which in turn reduces the strength properties of the concrete. It is…”
Get full text

Compressive Strength of Fly-Ash-Based Geopolymer Concrete by Gene Expression Programming and Random Forest by Khan, Mohsin Ali, Memon, Shazim Ali, Farooq, Furqan, Javed, Muhammad Faisal, Aslam, Fahid, Alyousef, Rayed

“…Fly ash (FA) is a residual from thermal industries that has been effectively utilized in the production of FA-based geopolymer concrete (FGPC). To avoid…”
Get full text

Application of Novel Machine Learning Techniques for Predicting the Surface Chloride Concentration in Concrete Containing Waste Material by Ahmad, Ayaz, Farooq, Furqan, Ostrowski, Krzysztof Adam, Śliwa-Wieczorek, Klaudia, Czarnecki, Slawomir

“…Structures located on the coast are subjected to the long-term influence of chloride ions, which cause the corrosion of steel reinforcements in concrete…”
Get full text

Applications of Gene Expression Programming for Estimating Compressive Strength of High-Strength Concrete by Alabdulijabbar, Hisham, Alyousef, Rayed, Akbar, Arslan, Waheed, Abdul, Khan, Kaffayatullah, Amin, Muhammad Nasir, Farooq, Furqan, Aslam, Fahid, Javed, Muhammad Faisal

“…The experimental design of high-strength concrete (HSC) requires deep analysis to get the target strength. In this study, machine learning approaches and…”
Get full text

Predictive Modeling of Mechanical Properties of Silica Fume-Based Green Concrete Using Artificial Intelligence Approaches: MLPNN, ANFIS, and GEP by Nafees, Afnan, Javed, Muhammad Faisal, Khan, Sherbaz, Nazir, Kashif, Farooq, Furqan, Aslam, Fahid, Musarat, Muhammad Ali, Vatin, Nikolai Ivanovich

“…Silica fume (SF) is a mineral additive that is widely used in the construction industry when producing sustainable concrete. The integration of SF in concrete…”
Get full text

Simulation of Depth of Wear of Eco-Friendly Concrete Using Machine Learning Based Computational Approaches by Khan, Mohsin Ali, Farooq, Furqan, Javed, Mohammad Faisal, Zafar, Adeel, Ostrowski, Krzysztof Adam, Aslam, Fahid, Malazdrewicz, Seweryn, Maślak, Mariusz

“…To avoid time-consuming, costly, and laborious experimental tests that require skilled personnel, an effort has been made to formulate the depth of wear of…”
Get full text

A Comparative Study of Random Forest and Genetic Engineering Programming for the Prediction of Compressive Strength of High Strength Concrete (HSC) by Farooq, Furqan, Nasir Amin, Muhammad, Khan, Kaffayatullah, Rehan Sadiq, Muhammad, Faisal Javed, Muhammad Faisal, Aslam, Fahid, Alyousef, Rayed

“…Supervised machine learning and its algorithm is an emerging trend for the prediction of mechanical properties of concrete. This study uses an ensemble random…”
Get full text

A Comparative Study for the Prediction of the Compressive Strength of Self-Compacting Concrete Modified with Fly Ash by Farooq, Furqan, Czarnecki, Slawomir, Niewiadomski, Pawel, Aslam, Fahid, Alabduljabbar, Hisham, Ostrowski, Krzysztof Adam, Śliwa-Wieczorek, Klaudia, Nowobilski, Tomasz, Malazdrewicz, Seweryn

“…Artificial intelligence and machine learning are employed in creating functions for the prediction of self-compacting concrete (SCC) strength based on input…”
Get full text

Experimental Investigation of Hybrid Carbon Nanotubes and Graphite Nanoplatelets on Rheology, Shrinkage, Mechanical, and Microstructure of SCCM by Farooq, Furqan, Akbar, Arslan, Khushnood, Rao Arsalan, Muhammad, Waqas Latif Baloch, Rehman, Sardar Kashif Ur, Javed, Muhammad Faisal

“…Carbon nanotubes (CNTs) and graphite nanoplatelets (GNPs) belong to the family of graphite nanomaterials (GNMs) and are promising candidates for enhancing…”
Get full text

Indirect prediction of graphene nanoplatelets-reinforced cementitious composites compressive strength by using machine learning approaches by Fawad, Muhammad, Alabduljabbar, Hisham, Farooq, Furqan, Najeh, Taoufik, Gamil, Yaser, Ahmed, Bilal

“…Graphene nanoplatelets (GrNs) emerge as promising conductive fillers to significantly enhance the electrical conductivity and strength of cementitious…”
Get full text

Geopolymer Concrete Compressive Strength via Artificial Neural Network, Adaptive Neuro Fuzzy Interface System, and Gene Expression Programming With K-Fold Cross Validation by Khan, Mohsin Ali, Zafar, Adeel, Farooq, Furqan, Javed, Muhammad Faisal, Alyousef, Rayed, Alabduljabbar, Hisham, Khan, M. Ijaz

“…The ultrafine fly ash (FA) is a hazardous material collected from coal productions, which has been proficiently employed for the manufacturing of geopolymer…”
Get full text

Applications of Gene Expression Programming and Regression Techniques for Estimating Compressive Strength of Bagasse Ash based Concrete by Javed, Muhammad Faisal, Amin, Muhammad Nasir, Shah, Muhammad Izhar, Khan, Kaffayatullah, Iftikhar, Bawar, Farooq, Furqan, Aslam, Fahid, Alyousef, Rayed, Alabduljabbar, Hisham

“…Compressive strength is one of the important property of concrete and depends on many factors. Most of the concrete compressive strength predictive models…”
Get full text

Prediction of Compressive Strength of Sustainable Foam Concrete Using Individual and Ensemble Machine Learning Approaches by Ullah, Haji Sami, Khushnood, Rao Arsalan, Farooq, Furqan, Ahmad, Junaid, Vatin, Nikolai Ivanovich, Ewais, Dina Yehia Zakaria

“…The entraining and distribution of air voids in the concrete matrix is a complex process that makes the mechanical properties of lightweight foamed concrete…”
Get full text

Forecasting Strength of CFRP Confined Concrete Using Multi Expression Programming by Ilyas, Israr, Zafar, Adeel, Javed, Muhammad, Farooq, Furqan, Aslam, Fahid, Musarat, Muhammad, Vatin, Nikolai

“…This study provides the application of a machine learning-based algorithm approach names “Multi Expression Programming” (MEP) to forecast the compressive…”
Get full text

New Prediction Model for the Ultimate Axial Capacity of Concrete-Filled Steel Tubes: An Evolutionary Approach by Javed, Muhammad Faisal, Farooq, Furqan, Memon, Shazim Ali, Akbar, Arslan, Khan, Mohsin Ali, Aslam, Fahid, Alyousef, Rayed, Alabduljabbar, Hisham, Rehman, Sardar Kashif Ur

“…The complication linked with the prediction of the ultimate capacity of concrete-filled steel tubes (CFST) short circular columns reveals a need for conducting…”
Get full text

Prediction of sustainable concrete utilizing rice husk ash (RHA) as supplementary cementitious material (SCM): Optimization and hyper-tuning by Amin, Muhammad Nasir, Khan, Kaffayatullah, Abu Arab, Abdullah Mohammad, Farooq, Furqan, Eldin, Sayed M., Javed, Muhammad Faisal

“…Rice Husk ash (RHA) utilization in concrete as a waste material can contribute to the formation of a robust cementitious matrix with utmost properties. The…”
Get full text

Evaluation of properties of bio-composite with interpretable machine learning approaches: optimization and hyper tuning by Xu, Guiying, Zhou, Gengxin, Althoey, Fadi, Hadidi, Haitham M., Alaskar, Abdulaziz, Hassan, Ahmed M., Farooq, Furqan

“…Hemp bio-composite (HBC) is a sustainable material that can be considered as a “carbon negative” or “better-than-zero-carbon” because it absorbs more carbon…”
Get full text

A comparative study on performance evaluation of hybrid GNPs/CNTs in conventional and self-compacting mortar by Farooq, Furqan, Rahman, Sardar Kashif Ur, Akbar, Arslan, Khushnood, Rao Arsalan, Javed, Muhammad Faisal, alyousef, Rayed, alabduljabbar, Hisham, aslam, Fahid

“…[Display omitted] In this paper performance of graphite nano platelets and carbon nanotubes was investigated in both conventional as well as self-compacting…”
Get full text