Predicting the compressive strength of green concretes using Harris hawks optimization-based data-driven methods

Incorporation of metakaolin and nanosilica in blended cement mortar and concrete- A review

(2021) A.A. Raheem et al.   JOURNAL OF CLEANER PRODUCTION

Predicting the compressive strength of self‐compacting concrete containing Class F fly ash using metaheuristic radial basis function neural network

(2021) Gholamreza Pazouki et al.   Structural Concrete

Improving the sulfate attack resistance of concrete by using supplementary cementitious materials (SCMs): A review

(2021) Md Manjur A Elahi et al.   CONSTRUCTION AND BUILDING MATERIALS

Precise design and characteristics prediction of Ultra-High Performance Concrete (UHPC) based on artificial intelligence techniques

(2021) Dingqiang Fan et al.   CEMENT & CONCRETE COMPOSITES

Artificial Intelligence to Model the Performance of Concrete Mixtures and Elements: A Review

(2021) Ali Behnood et al.   ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING

Heuristic algorithm-based semi-empirical formulas for estimating the compressive strength of the normal and high performance concrete

(2021) Ngoc-Hien Nguyen et al.   CONSTRUCTION AND BUILDING MATERIALS

A new development of eco-friendly Ultra-High performance concrete (UHPC): Towards efficient steel slag application and multi-objective optimization

(2021) Dingqiang Fan et al.   CONSTRUCTION AND BUILDING MATERIALS

Machine learning study of the mechanical properties of concretes containing waste foundry sand

(2020) Ali Behnood et al.   CONSTRUCTION AND BUILDING MATERIALS

A new design approach of steel fibre reinforced ultra-high performance concrete composites: Experiments and modeling

(2020) D.Q Fan et al.   CEMENT & CONCRETE COMPOSITES

A metaheuristic-optimized multi-output model for predicting multiple properties of pervious concrete

(2020) Junfei Zhang et al.   CONSTRUCTION AND BUILDING MATERIALS

Estimation of the compressive strength of concretes containing ground granulated blast furnace slag using hybridized multi-objective ANN and salp swarm algorithm

(2020) Amirreza Kandiri et al.   CONSTRUCTION AND BUILDING MATERIALS

An improved deflection model for FRP RC beams using an artificial intelligence-based approach

(2020) Hoan D. Nguyen et al.   ENGINEERING STRUCTURES

Prediction of dynamic increase factor for steel fibre reinforced concrete using a hybrid artificial intelligence model

(2019) Lei Yang et al.   ENGINEERING STRUCTURES

Optimum model for bearing capacity of concrete-steel columns with AI technology via incorporating the algorithms of IWO and ABC

(2019) Payam Sarir et al.   ENGINEERING WITH COMPUTERS

Fine-tuning of neural computing using whale optimization algorithm for predicting compressive strength of concrete

(2019) Dieu Tien Bui et al.   ENGINEERING WITH COMPUTERS

Harris hawks optimization: Algorithm and applications

(2019) Ali Asghar Heidari et al.   Future Generation Computer Systems-The International Journal of eScience

A generalized method to predict the compressive strength of high-performance concrete by improved random forest algorithm

(2019) Qinghua Han et al.   CONSTRUCTION AND BUILDING MATERIALS

Predicting the compressive strength of normal and High-Performance Concretes using ANN and ANFIS hybridized with Grey Wolf Optimizer

(2019) Emadaldin Mohammadi Golafshani et al.   CONSTRUCTION AND BUILDING MATERIALS

Effects of deicers on the performance of concrete pavements containing air-cooled blast furnace slag and supplementary cementitious materials

(2018) Kho Pin Verian et al.   CEMENT & CONCRETE COMPOSITES

A modified firefly algorithm-artificial neural network expert system for predicting compressive and tensile strength of high-performance concrete

(2018) Dac-Khuong Bui et al.   CONSTRUCTION AND BUILDING MATERIALS

A novel optimised self-learning method for compressive strength prediction of high performance concrete

(2018) Yang Yu et al.   CONSTRUCTION AND BUILDING MATERIALS

Shear resistance prediction of concrete beams reinforced by FRP bars using artificial neural networks

(2018) H. Naderpour et al.   MEASUREMENT

Predicting the compressive strength of silica fume concrete using hybrid artificial neural network with multi-objective grey wolves

(2018) Ali Behnood et al.   JOURNAL OF CLEANER PRODUCTION

Hybrid ultrasonic-neural prediction of the compressive strength of environmentally friendly concrete screeds with high volume of waste quartz mineral dust

(2018) Łukasz Sadowski et al.   JOURNAL OF CLEANER PRODUCTION

Estimating the optimal mix design of silica fume concrete using biogeography-based programming

(2018) Emadaldin Mohammadi Golafshani et al.   CEMENT & CONCRETE COMPOSITES

Current developments and future needs in standards for cementitious materials

(2015) R. Douglas Hooton   CEMENT AND CONCRETE RESEARCH

Predicting modulus elasticity of recycled aggregate concrete using M5′ model tree algorithm

(2015) Ali Behnood et al.   CONSTRUCTION AND BUILDING MATERIALS

Evaluation of the splitting tensile strength in plain and steel fiber-reinforced concrete based on the compressive strength

(2015) Ali Behnood et al.   CONSTRUCTION AND BUILDING MATERIALS

High-performance concrete compressive strength prediction using Genetic Weighted Pyramid Operation Tree (GWPOT)

(2013) Min-Yuan Cheng et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Prediction of high performance concrete strength using Genetic Programming with geometric semantic genetic operators

(2013) Mauro Castelli et al.   EXPERT SYSTEMS WITH APPLICATIONS

High-performance Concrete Compressive Strength Prediction using Time-Weighted Evolutionary Fuzzy Support Vector Machines Inference Model

(2012) Min-Yuan Cheng et al.   AUTOMATION IN CONSTRUCTION

Optimizing the Prediction Accuracy of Concrete Compressive Strength Based on a Comparison of Data-Mining Techniques

(2010) Jui-Sheng Chou et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

Prediction of compressive strength of concrete containing fly ash using artificial neural networks and fuzzy logic

(2007) İlker Bekir Topçu et al.   COMPUTATIONAL MATERIALS SCIENCE