Application of adaptive neuro-fuzzy technique and regression models to predict the compressive strength of geopolymer composites

The effects of silica modulus and aging on compressive strength of pumice-based geopolymer composites

(2015) Mehrzad Mohabbi Yadollahi et al.   CONSTRUCTION AND BUILDING MATERIALS

Effects of elevated temperature on pumice based geopolymer composites

(2015) M. M. Yadollahi et al.   PLASTICS RUBBER AND COMPOSITES

A combination of computational fluid dynamics (CFD) and adaptive neuro-fuzzy system (ANFIS) for prediction of the bubble column hydrodynamics

(2015) M. Pourtousi et al.   POWDER TECHNOLOGY

Effect of different superplasticizers and activator combinations on workability and strength of fly ash based geopolymer

(2014) Behzad Nematollahi et al.   MATERIALS & DESIGN

Prediction of concrete compressive strength: Research on hybrid models genetic based algorithms and ANFIS

(2013) Zhe Yuan et al.   ADVANCES IN ENGINEERING SOFTWARE

Application of ANFIS and LR in prediction of scour depth in bridges

(2013) Shatirah Akib et al.   COMPUTERS & FLUIDS

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

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

Main factors affecting mechanical characteristics of geopolymer revealed by experimental design and associated statistical analysis

(2013) Syuan-Jhih Lyu et al.   CONSTRUCTION AND BUILDING MATERIALS

Improving Rainfall Forecasting Efficiency Using Modified Adaptive Neuro-Fuzzy Inference System (MANFIS)

(2013) Seyed Ahmad Akrami et al.   WATER RESOURCES MANAGEMENT

Effect of heat treatment temperature on ground pumice activation in geopolymer composites

(2013) Mehrzad Mohabbi Yadollahi et al.   SCIENCE AND ENGINEERING OF COMPOSITE MATERIALS

Prediction compressive strength of lightweight geopolymers by ANFIS

(2012) Ali Nazari et al.   CERAMICS INTERNATIONAL

Experimental investigations and fuzzy logic modeling of compressive strength of geopolymers with seeded fly ash and rice husk bark ash

(2012) Hamid Bohlooli et al.   COMPOSITES PART B-ENGINEERING

Prediction of elastic modulus of normal and high strength concrete using ANFIS and optimal nonlinear regression models

(2012) Behrouz Ahmadi-Nedushan   CONSTRUCTION AND BUILDING MATERIALS

Compressive strength of geopolymers produced by ordinary Portland cement: Application of genetic programming for design

(2012) Ali Nazari   MATERIALS & DESIGN

Prediction of the concrete compressive strength by means of core testing using GMDH-type neural network and ANFIS models

(2011) Rahmat Madandoust et al.   COMPUTATIONAL MATERIALS SCIENCE

Effect of heat treatment on reactivity-strength of alkali-activated natural pozzolans

(2011) Dali Bondar et al.   CONSTRUCTION AND BUILDING MATERIALS

Effect of adding mineral additives to alkali-activated natural pozzolan paste

(2011) Dali Bondar et al.   CONSTRUCTION AND BUILDING MATERIALS

Artificial Neural Network Approach to Predict Compressive Strength of Concrete through Ultrasonic Pulse Velocity

(2010) M. Bilgehan et al.   RESEARCH IN NONDESTRUCTIVE EVALUATION

Alkali-activated fly ash-based geopolymers with zeolite or bentonite as additives

(2009) Mingyu Hu et al.   CEMENT & CONCRETE COMPOSITES

Prediction of the compressive strength of no-slump concrete: A comparative study of regression, neural network and ANFIS models

(2009) Jafar Sobhani et al.   CONSTRUCTION AND BUILDING MATERIALS

Prediction of the strength and elasticity modulus of gypsum using multiple regression, ANN, and ANFIS models

(2008) Işık Yilmaz et al.   INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES

Prediction of concrete strength using ultrasonic pulse velocity and artificial neural networks

(2008) Gregor Trtnik et al.   ULTRASONICS