The Effectiveness of Ensemble-Neural Network Techniques to Predict Peak Uplift Resistance of Buried Pipes in Reinforced Sand

Big data management in the mining industry

(2020) Chong-chong Qi   International Journal of Minerals Metallurgy and Materials

On the limitations of decoupled approach for the seismic behaviour evaluation of shallow multi-propped underground structures embedded in granular soils

(2020) Marco Zucca et al.   ENGINEERING STRUCTURES

A novel artificial intelligence technique to predict compressive strength of recycled aggregate concrete using ICA-XGBoost model

(2020) Jin Duan et al.   ENGINEERING WITH COMPUTERS

Development of a novel approach for strain demand prediction of pipes at fault crossings on the basis of multi-layer neural network driven by strain data

(2020) Xiaoben Liu et al.   ENGINEERING STRUCTURES

A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength

(2020) Danial Jahed Armaghani et al.   NEURAL COMPUTING & APPLICATIONS

Mapping and holistic design of natural hydraulic lime mortars

(2020) Maria Apostolopoulou et al.   CEMENT AND CONCRETE RESEARCH

Mechanics and safety issues in tailing-based backfill: A review

(2020) Xu Zhao et al.   International Journal of Minerals Metallurgy and Materials

Safety of barricades in cemented paste-backfilled stopes

(2020) Xu Zhao et al.   International Journal of Minerals Metallurgy and Materials

A Novel Feature Selection Approach Based on Tree Models for Evaluating the Punching Shear Capacity of Steel Fiber-Reinforced Concrete Flat Slabs

(2020) Shasha Lu et al.   Materials

Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate

(2020) Jian Zhou et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Prediction of ground vibration induced by blasting operations through the use of the Bayesian Network and random forest models

(2020) Jian Zhou et al.   SOIL DYNAMICS AND EARTHQUAKE ENGINEERING

Prediction of air-overpressure induced by blasting using an ANFIS-PNN model optimized by GA

(2020) Hooman Harandizadeh et al.   APPLIED SOFT COMPUTING

Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques

(2020) Jian Zhou et al.   Geoscience Frontiers

Stochastic Vulnerability Assessment of Masonry Structures: Concepts, Modeling and Restoration Aspects

(2019) Panagiotis G. Asteris et al.   Applied Sciences-Basel

Neuro-genetic, neuro-imperialism and genetic programing models in predicting ultimate bearing capacity of pile

(2019) Wusi Chen et al.   ENGINEERING WITH COMPUTERS

Assessing Dynamic Conditions of the Retaining Wall: Developing Two Hybrid Intelligent Models

(2019) Hui Chen et al.   Applied Sciences-Basel

Developing GEP tree-based, neuro-swarm, and whale optimization models for evaluation of bearing capacity of concrete-filled steel tube columns

(2019) Payam Sarir et al.   ENGINEERING WITH COMPUTERS

Effect of Water Content on Argillization of Mudstone During the Tunnelling process

(2019) Bolong Liu et al.   ROCK MECHANICS AND ROCK ENGINEERING

An analytical solution for evaluating the safety of an exposed face in a paste backfill stope incorporating the arching phenomenon

(2019) Xu Zhao et al.   International Journal of Minerals Metallurgy and Materials

Slope stability prediction for circular mode failure using gradient boosting machine approach based on an updated database of case histories

(2019) Jian Zhou et al.   SAFETY SCIENCE

A Gene Expression Programming Model for Predicting Tunnel Convergence

(2019) Mohsen Hajihassani et al.   Applied Sciences-Basel

Forecasting of TBM advance rate in hard rock condition based on artificial neural network and genetic programming techniques

(2019) Jian Zhou et al.   Bulletin of Engineering Geology and the Environment

Invasive Weed Optimization Technique-Based ANN to the Prediction of Rock Tensile Strength

(2019) Lei Huang et al.   Applied Sciences-Basel

Privacy-preserving in association rule mining using an improved discrete binary artificial bee colony

(2019) Akbar Telikani et al.   EXPERT SYSTEMS WITH APPLICATIONS

Improving the prediction of ground motion parameters based on an efficient bagging ensemble model of M5′ and CART algorithms

(2018) S.M. Hamze-Ziabari et al.   APPLIED SOFT COMPUTING

Model test on the entrainment phenomenon and energy conversion mechanism of flow-like landslides

(2018) H.Q. Yang et al.   ENGINEERING GEOLOGY

Effects of joints on the cutting behavior of disc cutter running on the jointed rock mass

(2018) H.Q. Yang et al.   TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY

On the uncertainty analysis of uplift capacity of suction caissons in clay based on the fuzzy sets theory

(2018) Ali Derakhshani   OCEAN ENGINEERING

Estimating uplift capacity of suction caissons in soft clay: A hybrid computational approach based on model tree and GP

(2017) Ali Derakhshani   OCEAN ENGINEERING

Feed-Forward Neural Network Prediction of the Mechanical Properties of Sandcrete Materials

(2017) Panagiotis Asteris et al.   SENSORS

Uplift capacity prediction of suction caisson in clay using a hybrid intelligence method (GMDH-HS)

(2016) Mojtaba Masoumi Shahr-Babak et al.   APPLIED OCEAN RESEARCH

Bagging ensemble models for bank profitability: An emprical research on Turkish development and investment banks

(2016) Hamit Erdal et al.   APPLIED SOFT COMPUTING

Prediction of self-compacting concrete strength using artificial neural networks

(2016) P.G. Asteris et al.   European Journal of Environmental and Civil Engineering

Classification of Rockburst in Underground Projects: Comparison of Ten Supervised Learning Methods

(2016) Jian Zhou et al.   JOURNAL OF COMPUTING IN CIVIL ENGINEERING

Utilizing gradient boosted machine for the prediction of damage to residential structures owing to blasting vibrations of open pit mining

(2016) Jian Zhou et al.   JOURNAL OF VIBRATION AND CONTROL

A quasi-three-dimensional spring-deformable-block model for runout analysis of rapid landslide motion

(2015) H.Q. Yang et al.   ENGINEERING GEOLOGY

Offshore pipeline performance evaluation by different artificial neural networks approaches

(2015) Ali Nazari et al.   MEASUREMENT

Effects of soil reinforcement on uplift resistance of buried pipeline

(2015) Danial Jahed Armaghani et al.   MEASUREMENT

Comparative performance of six supervised learning methods for the development of models of hard rock pillar stability prediction

(2015) Jian Zhou et al.   NATURAL HAZARDS

Artificial neural network models for predicting condition of offshore oil and gas pipelines

(2014) Mohammed S. El-Abbasy et al.   AUTOMATION IN CONSTRUCTION

A hybrid fuzzy inference model based on RBFNN and artificial bee colony for predicting the uplift capacity of suction caissons

(2014) Min-Yuan Cheng et al.   AUTOMATION IN CONSTRUCTION

Uplift Resistance of Buried Pipelines Enhanced by Geogrid

(2014) K. Faizi et al.   Soil Mechanics and Foundation Engineering

Uplift Capacity of Suction Caisson in Clay Using Artificial Intelligence Techniques

(2013) Pradyut Kumar Muduli et al.   MARINE GEORESOURCES & GEOTECHNOLOGY

Modeling and optimization of a trench layer location around a pipeline using artificial neural networks and particle swarm optimization algorithm

(2013) Asskar Janalizadeh Choobbasti et al.   TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY

High-precision modeling of uplift capacity of suction caissons using a hybrid computational method

(2013) Amir Hossein Alavi et al.   Geomechanics and Engineering

Ensemble approaches for regression

(2012) João Mendes-Moreira et al.   ACM COMPUTING SURVEYS

Genetic-based modeling of uplift capacity of suction caissons

(2011) Amir Hossein Alavi et al.   EXPERT SYSTEMS WITH APPLICATIONS

Formulation of uplift capacity of suction caissons using multi expression programming

(2011) Amir Hossein Gandomi et al.   KSCE Journal of Civil Engineering

Uplift capacity of suction caisson in clay using multivariate adaptive regression spline

(2011) Pijush Samui et al.   OCEAN ENGINEERING

Prediction of Force Measurements of a Microbend Sensor Based on an Artificial Neural Network

(2009) Hasan Efendioglu et al.   SENSORS

The uplift resistance of pipes and plate anchors buried in sand

(2008) D. J. White et al.   GEOTECHNIQUE