Multigene Expression Programming Based Forecasting the Hardened Properties of Sustainable Bagasse Ash Concrete

Performance Evaluation of Soft Computing for Modeling the Strength Properties of Waste Substitute Green Concrete

(2021) Muhammad Izhar Shah et al.   Sustainability

Machine Learning-Based Modeling with Optimization Algorithm for Predicting Mechanical Properties of Sustainable Concrete

(2021) Muhammad Izhar Shah et al.   Advances in Civil Engineering

Sustainable utilization of foundry waste: Forecasting mechanical properties of foundry sand based concrete using multi-expression programming

(2021) Muhammad Farjad Iqbal et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Predictive Modeling Approach for Surface Water Quality: Development and Comparison of Machine Learning Models

(2021) Muhammad Izhar Shah et al.   Sustainability

COMPRESSIVE STRENGTH PREDICTION OF LIGHTWEIGHT SHORT COLUMNS AT ELEVATED TEMPERATURE USING GENE EXPRESSION PROGRAMING AND ARTIFICIAL NEURAL NETWORK

(2020) Ahmed Ashteyat et al.   Journal of Civil Engineering and Management

Toward intelligent construction: Prediction of mechanical properties of manufactured-sand concrete using tree-based models

(2020) Junfei Zhang et al.   JOURNAL OF CLEANER PRODUCTION

Prediction model for compressive arch action capacity of RC frame structures under column removal scenario using gene expression programming

(2020) Iftikhar Azim et al.   Structures

A Comparative Study of Random Forest and Genetic Engineering Programming for the Prediction of Compressive Strength of High Strength Concrete (HSC)

(2020) Furqan Farooq et al.   Applied Sciences-Basel

New Prediction Model for the Ultimate Axial Capacity of Concrete-Filled Steel Tubes: An Evolutionary Approach

(2020) Muhammad Faisal Javed et al.   Crystals

Applications of Gene Expression Programming for Estimating Compressive Strength of High-Strength Concrete

(2020) Fahid Aslam et al.   Advances in Civil Engineering

Comparison of CO2 emissions from OPC and recycled cement production

(2019) Zhijun He et al.   CONSTRUCTION AND BUILDING MATERIALS

Consolidation assessment using Multi Expression Programming

(2019) Sohrab Sharifi et al.   APPLIED SOFT COMPUTING

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

Prediction of mechanical properties of green concrete incorporating waste foundry sand based on gene expression programming

(2019) Muhammad Farjad Iqbal et al.   JOURNAL OF HAZARDOUS MATERIALS

Deep Multiphysics and Particle–Neuron Duality: A Computational Framework Coupling (Discrete) Multiphysics and Deep Learning

(2019) Alessio Alexiadis   Applied Sciences-Basel

Prediction of the Strength of Rubberized Concrete by an Evolved Random Forest Model

(2019) Yuantian Sun et al.   Advances in Civil Engineering

Development of applicable design models for concrete columns confined with aramid fiber reinforced polymer using Multi-Expression Programming

(2019) Alireza Arabshahi et al.   Structures

Compressive strength prediction of recycled concrete based on deep learning

(2018) Fangming Deng et al.   CONSTRUCTION AND BUILDING MATERIALS

Evaluation of mechanical properties of Sugar Cane Bagasse Ash concrete

(2018) P. Jagadesh et al.   CONSTRUCTION AND BUILDING MATERIALS

Value-added Utilization of Marine Clay as Cement Replacement for Sustainable Concrete Production

(2018) Hongjian Du et al.   JOURNAL OF CLEANER PRODUCTION

Effects of sugarcane bagasse ash on the properties of concrete

(2018) Nasir Shafiq et al.   Proceedings of the Institution of Civil Engineers-Engineering Sustainability

Artificial neural network based modelling approach for strength prediction of concrete incorporating agricultural and construction wastes

(2018) Mulusew Aderaw Getahun et al.   CONSTRUCTION AND BUILDING MATERIALS

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

Multi-phase modelling of electrochemical rehabilitation for ASR and chloride affected concrete composites

(2018) Li-xuan Mao et al.   COMPOSITE STRUCTURES

Deep neural network with high-order neuron for the prediction of foamed concrete strength

(2018) Tuan Nguyen et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Characteristics and Applications of Sugar Cane Bagasse Ash Waste in Cementitious Materials

(2018) Qing Xu et al.   Materials

Mechanical and durability properties of mortars prepared with untreated sugarcane bagasse ash and untreated fly ash

(2016) J.C. Arenas-Piedrahita et al.   CONSTRUCTION AND BUILDING MATERIALS

Assesment of Pozzolanic Performance of Sugarcane Bagasse Ash

(2016) A. Bahurudeen et al.   JOURNAL OF MATERIALS IN CIVIL ENGINEERING

Evaluation of empirical models for predicting monthly mean horizontal diffuse solar radiation

(2016) Milan Despotovic et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Strength, chloride resistance, and expansion of concretes containing ground bagasse ash

(2015) Aukkadet Rerkpiboon et al.   CONSTRUCTION AND BUILDING MATERIALS

NEW DESIGN EQUATIONS FOR ELASTIC MODULUS OF CONCRETE USING MULTI EXPRESSION PROGRAMMING

(2015) Amir H. Gandomi et al.   Journal of Civil Engineering and Management

Micro-analytical studies on sugar cane bagasse ash

(2015) P JAGADESH et al.   SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES

Modeling compressive strength of EPS lightweight concrete using regression, neural network and ANFIS

(2013) A. Sadrmomtazi et al.   CONSTRUCTION AND BUILDING MATERIALS

Modeling of compressive strength of HPC mixes using a combined algorithm of genetic programming and orthogonal least squares

(2013) S.M. Mousavi et al.   STRUCTURAL ENGINEERING AND MECHANICS

Prediction of compressive strength of concrete containing construction and demolition waste using artificial neural networks

(2012) Adriana Trocoli Abdon Dantas et al.   CONSTRUCTION AND BUILDING MATERIALS

Formulation of secant and reloading soil deformation moduli using multi expression programming

(2012) Amir Hossein Alavi et al.   ENGINEERING COMPUTATIONS

Predicting properties of High Performance Concrete containing composite cementitious materials using Artificial Neural Networks

(2011) Mohammad Iqbal Khan   AUTOMATION IN CONSTRUCTION

Experimental characterization of binary and ternary blended-cement concretes containing ultrafine residual rice husk and sugar cane bagasse ashes

(2011) G.C. Cordeiro et al.   CONSTRUCTION AND BUILDING MATERIALS

Utilization of bagasse ash in high-strength concrete

(2011) Sumrerng Rukzon et al.   MATERIALS & DESIGN

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

Use of Bagasse Ash in Concrete and Its Impact on the Strength and Chloride Resistivity

(2010) Noor-ul Amin   JOURNAL OF MATERIALS IN CIVIL ENGINEERING

Nonlinear Genetic-Based Models for Prediction of Flow Number of Asphalt Mixtures

(2010) Amir Hossein Gandomi et al.   JOURNAL OF MATERIALS IN CIVIL ENGINEERING

Utilization of bagasse ash as a pozzolanic material in concrete

(2009) Nuntachai Chusilp et al.   CONSTRUCTION AND BUILDING MATERIALS

Ultrafine grinding of sugar cane bagasse ash for application as pozzolanic admixture in concrete

(2008) Guilherme Chagas Cordeiro et al.   CEMENT AND CONCRETE RESEARCH

Analysis of durability of high performance concrete using artificial neural networks

(2008) R. Parichatprecha et al.   CONSTRUCTION AND BUILDING MATERIALS

Production of low cost self compacting concrete using bagasse ash

(2008) Tayyeb Akram et al.   CONSTRUCTION AND BUILDING MATERIALS

A review of the interference of carbon containing fly ash with air entrainment in concrete

(2007) K PEDERSEN et al.   PROGRESS IN ENERGY AND COMBUSTION SCIENCE

On Some Aspects of Variable Selection for Partial Least Squares Regression Models

(2007) Partha Pratim Roy et al.   Quantitative structure-activity relationships & combinatorial science