Applying several soft computing techniques for prediction of bearing capacity of driven piles
Published 2018 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Applying several soft computing techniques for prediction of bearing capacity of driven piles
Authors
Keywords
Pile bearing capacity, ANN, ICA, ANFIS, Hybrid model
Journal
ENGINEERING WITH COMPUTERS
Volume -, Issue -, Pages -
Publisher
Springer Nature
Online
2018-12-17
DOI
10.1007/s00366-018-0674-7
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A combination of artificial bee colony and neural network for approximating the safety factor of retaining walls
- (2018) Ebrahim Noroozi Ghaleini et al. ENGINEERING WITH COMPUTERS
- Applying various hybrid intelligent systems to evaluate and predict slope stability under static and dynamic conditions
- (2018) Mohammadreza Koopialipoor et al. SOFT COMPUTING
- Applicability of a CPT-Based Neural Network Solution in Predicting Load-Settlement Responses of Bored Pile
- (2018) Hossein Moayedi et al. International Journal of Geomechanics
- Predicting tunnel boring machine performance through a new model based on the group method of data handling
- (2018) Mohammadreza Koopialipoor et al. Bulletin of Engineering Geology and the Environment
- Rock tensile strength prediction using empirical and soft computing approaches
- (2018) Amir Mahdiyar et al. Bulletin of Engineering Geology and the Environment
- Applying several soft computing techniques for prediction of bearing capacity of driven piles
- (2018) Sadulla Shaik et al. ENGINEERING WITH COMPUTERS
- Simulating the peak particle velocity in rock blasting projects using a neuro-fuzzy inference system
- (2018) Wenchao Jiang et al. ENGINEERING WITH COMPUTERS
- Prediction of bearing capacity of thin-walled foundation: a simulation approach
- (2017) Ehsan Momeni et al. ENGINEERING WITH COMPUTERS
- Optimizing an ANN model with ICA for estimating bearing capacity of driven pile in cohesionless soil
- (2017) Hossein Moayedi et al. ENGINEERING WITH COMPUTERS
- An expert system based on hybrid ICA-ANN technique to estimate macerals contents of Indian coals
- (2017) Manoj Khandelwal et al. Environmental Earth Sciences
- A new developed approach for the prediction of ground vibration using a hybrid PSO-optimized ANFIS-based model
- (2017) Azam Shahnazar et al. Environmental Earth Sciences
- Prediction of an environmental issue of mine blasting: an imperialistic competitive algorithm-based fuzzy system
- (2017) M. Hasanipanah et al. International Journal of Environmental Science and Technology
- Uplift resistance of belled and multi-belled piles in loose sand
- (2017) Hossein Moayedi et al. MEASUREMENT
- An artificial neural network approach for under-reamed piles subjected to uplift forces in dry sand
- (2017) Hossein Moayedi et al. NEURAL COMPUTING & APPLICATIONS
- Feasibility of PSO-ANN model for predicting surface settlement caused by tunneling
- (2016) Mahdi Hasanipanah et al. ENGINEERING WITH COMPUTERS
- Prediction of air-overpressure caused by mine blasting using a new hybrid PSO–SVR model
- (2016) Mahdi Hasanipanah et al. ENGINEERING WITH COMPUTERS
- Prediction of the durability of limestone aggregates using computational techniques
- (2016) Seyed Vahid Alavi Nezhad Khalil Abad et al. NEURAL COMPUTING & APPLICATIONS
- Rock strength estimation: a PSO-based BP approach
- (2016) E. Tonnizam Mohamad et al. NEURAL COMPUTING & APPLICATIONS
- Airblast prediction through a hybrid genetic algorithm-ANN model
- (2016) Danial Jahed Armaghani et al. NEURAL COMPUTING & APPLICATIONS
- Settlement prediction of the rock-socketed piles through a new technique based on gene expression programming
- (2016) Danial Jahed Armaghani et al. NEURAL COMPUTING & APPLICATIONS
- Potential of adaptive neuro fuzzy inference system for evaluating the factors affecting steel-concrete composite beam's shear strength
- (2016) M. Safa et al. STEEL AND COMPOSITE STRUCTURES
- Application of two intelligent systems in predicting environmental impacts of quarry blasting
- (2015) Danial Jahed Armaghani et al. Arabian Journal of Geosciences
- Application of fuzzy inference system for prediction of rock fragmentation induced by blasting
- (2015) Samira Shams et al. Arabian Journal of Geosciences
- Neuro-fuzzy technique to predict air-overpressure induced by blasting
- (2015) Danial Jahed Armaghani et al. Arabian Journal of Geosciences
- Application of Artificial Neural Network for Predicting Shaft and Tip Resistances of Concrete Piles
- (2015) Ehsan Momeni et al. Earth Sciences Research Journal
- Combination of neural network and ant colony optimization algorithms for prediction and optimization of flyrock and back-break induced by blasting
- (2015) Amir Saghatforoush et al. ENGINEERING WITH COMPUTERS
- Evaluation and prediction of flyrock resulting from blasting operations using empirical and computational methods
- (2015) D. Jahed Armaghani et al. ENGINEERING WITH COMPUTERS
- A combination of the ICA-ANN model to predict air-overpressure resulting from blasting
- (2015) Danial Jahed Armaghani et al. ENGINEERING WITH COMPUTERS
- Feasibility of ANFIS model for prediction of ground vibrations resulting from quarry blasting
- (2015) Danial Jahed Armaghani et al. Environmental Earth Sciences
- Feasibility of indirect determination of blast induced ground vibration based on support vector machine
- (2015) Mahdi Hasanipanah et al. MEASUREMENT
- Developing a hybrid PSO–ANN model for estimating the ultimate bearing capacity of rock-socketed piles
- (2015) Danial Jahed Armaghani et al. NEURAL COMPUTING & APPLICATIONS
- Determination of Reliable Stress and Strain Distributions Along Bored Piles
- (2015) H. Moayedi et al. Soil Mechanics and Foundation Engineering
- Ground vibration prediction in quarry blasting through an artificial neural network optimized by imperialist competitive algorithm
- (2014) Mohsen Hajihassani et al. Bulletin of Engineering Geology and the Environment
- Prediction of pile bearing capacity using a hybrid genetic algorithm-based ANN
- (2014) E. Momeni et al. MEASUREMENT
- Indirect measure of shale shear strength parameters by means of rock index tests through an optimized artificial neural network
- (2014) Danial Jahed Armaghani et al. MEASUREMENT
- A Novel Approach for Blast-Induced Flyrock Prediction Based on Imperialist Competitive Algorithm and Artificial Neural Network
- (2014) Aminaton Marto et al. TheScientificWorldJOURNAL
- A hybridized artificial neural network and imperialist competitive algorithm optimization approach for prediction of soil compaction in soil bin facility
- (2013) Hamid Taghavifar et al. MEASUREMENT
- Bearing Capacity of Driven Piles Supported on Slightly Compressible Soils
- (2013) A. M. Dzagov et al. Soil Mechanics and Foundation Engineering
- Identification of a suitable ANN architecture in predicting strain in tie section of concrete deep beams
- (2013) Mohammad Mohammadhassani et al. STRUCTURAL ENGINEERING AND MECHANICS
- Evolving artificial neural network and imperialist competitive algorithm for prediction oil flow rate of the reservoir
- (2012) Mohammad Ali Ahmadi et al. APPLIED SOFT COMPUTING
- Evaluation and prediction of blast-induced ground vibration at Shur River Dam, Iran, by artificial neural network
- (2012) Masoud Monjezi et al. NEURAL COMPUTING & APPLICATIONS
- A comparative study of generalized regression neural network approach and adaptive neuro-fuzzy inference systems for prediction of unconfined compressive strength of rocks
- (2012) Rajesh Singh et al. NEURAL COMPUTING & APPLICATIONS
- Determination of ultimate capacity of driven piles in cohesionless soil: A Multivariate Adaptive Regression Spline approach
- (2011) Pijush Samui INTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS
- Applicability of the SPT-based methods for estimating toe bearing capacity of driven PHC piles in the thick deltaic deposits
- (2011) N. T. Dung et al. KSCE Journal of Civil Engineering
- Prediction of blast-induced ground vibration using artificial neural network
- (2009) Manoj Khandelwal et al. INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now