A new multikernel relevance vector machine based on the HPSOGWO algorithm for predicting and controlling blast-induced ground vibration
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A new multikernel relevance vector machine based on the HPSOGWO algorithm for predicting and controlling blast-induced ground vibration
Authors
Keywords
-
Journal
ENGINEERING WITH COMPUTERS
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2020-08-10
DOI
10.1007/s00366-020-01136-2
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Investigating the effective parameters on the risk levels of rockburst phenomena by developing a hybrid heuristic algorithm
- (2020) Jian Zhou et al. ENGINEERING WITH COMPUTERS
- Attenuation assessment of blast-induced vibrations derived from an underground mine
- (2020) Yonggang Gou et al. INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
- Development of a new methodology for estimating the amount of PPV in surface mines based on prediction and probabilistic models (GEP-MC)
- (2020) Jian Zhou et al. International Journal of Mining Reclamation and Environment
- A Combination of Feature Selection and Random Forest Techniques to Solve a Problem Related to Blast-Induced Ground Vibration
- (2020) Zhang et al. Applied Sciences-Basel
- Practical Risk Assessment of Ground Vibrations Resulting from Blasting, Using Gene Expression Programming and Monte Carlo Simulation Techniques
- (2020) Amir Mahdiyar et al. Applied Sciences-Basel
- Effective Assessment of Blast-Induced Ground Vibration Using an Optimized Random Forest Model Based on a Harris Hawks Optimization Algorithm
- (2020) Zhi Yu et al. Applied Sciences-Basel
- Prediction of rockburst risk in underground projects developing a neuro-bee intelligent system
- (2020) Jian Zhou et al. Bulletin of Engineering Geology and the Environment
- 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
- Developing a hybrid model of salp swarm algorithm-based support vector machine to predict the strength of fiber-reinforced cemented paste backfill
- (2020) Enming Li et al. ENGINEERING WITH COMPUTERS
- Two novel combined systems for predicting the peak shear strength using RBFNN and meta-heuristic computing paradigms
- (2020) Juncheng Gao et al. ENGINEERING WITH COMPUTERS
- A novel optimized multi-kernel relevance vector machine with selected sensitive features and its application in early fault diagnosis for rolling bearings
- (2020) Fafa Chen et al. MEASUREMENT
- Fault classification in three-phase motors based on vibration signal analysis and artificial neural networks
- (2020) Ronny Francis Ribeiro Junior et al. NEURAL COMPUTING & APPLICATIONS
- Hybrid meta-heuristic and machine learning algorithms for tunneling-induced settlement prediction: A comparative study
- (2020) Pin Zhang et al. TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
- On the Use of Neuro-Swarm System to Forecast the Pile Settlement
- (2020) Danial Jahed Armaghani et al. Applied Sciences-Basel
- Artificial bee colony-based neural network for the prediction of the fundamental period of infilled frame structures
- (2019) Panagiotis G. Asteris et al. NEURAL COMPUTING & APPLICATIONS
- Prediction of Blast-Induced Ground Vibration in an Open-Pit Mine by a Novel Hybrid Model Based on Clustering and Artificial Neural Network
- (2019) Hoang Nguyen et al. Natural Resources Research
- A Monte Carlo simulation approach for effective assessment of flyrock based on intelligent system of neural network
- (2019) Jian Zhou et al. ENGINEERING WITH COMPUTERS
- A comparison of advanced computational models and experimental techniques in predicting blast-induced ground vibration in open-pit coal mine
- (2019) Hoang Nguyen et al. Acta Geophysica
- Application of deep neural networks in predicting the penetration rate of tunnel boring machines
- (2019) Mohammadreza Koopialipoor et al. Bulletin of Engineering Geology and the Environment
- Whale optimized mixed kernel function of support vector machine for colorectal cancer diagnosis
- (2019) Dandan Zhao et al. JOURNAL OF BIOMEDICAL INFORMATICS
- Local tangent space alignment and relevance vector machine as nonlinear methods for estimating sensory quality of tea using NIR spectroscopy
- (2019) Peng Liu et al. VIBRATIONAL SPECTROSCOPY
- Predicting the Loose Zone of Roadway Surrounding Rock Using Wavelet Relevance Vector Machine
- (2019) Yang Liu et al. Applied Sciences-Basel
- Assessing Dynamic Conditions of the Retaining Wall: Developing Two Hybrid Intelligent Models
- (2019) Hui Chen et al. Applied Sciences-Basel
- Novel Soft Computing Model for Predicting Blast-Induced Ground Vibration in Open-Pit Mines Based on Particle Swarm Optimization and XGBoost
- (2019) Xiliang Zhang et al. Natural Resources Research
- A novel Harris hawks’ optimization and k-fold cross-validation predicting slope stability
- (2019) Hossein Moayedi et al. ENGINEERING WITH COMPUTERS
- A new approach for estimation of rock brittleness based on non-destructive tests
- (2019) Mohammadreza Koopialipoor et al. Nondestructive Testing and Evaluation
- Use of Intelligent Methods to Design Effective Pattern Parameters of Mine Blasting to Minimize Flyrock Distance
- (2019) Jian Zhou et al. Natural Resources Research
- Ensemble of relevance vector machines and boosted trees for electricity price forecasting
- (2019) Rahul Kumar Agrawal et al. APPLIED ENERGY
- A Novel Performance Assessment Approach using Photogrammetric Techniques for Landslide Susceptibility Mapping with Logistic Regression, ANN and Random Forest
- (2019) Sevgen et al. SENSORS
- Supervised Machine Learning Techniques to the Prediction of Tunnel Boring Machine Penetration Rate
- (2019) Hai Xu et al. Applied Sciences-Basel
- Prediction of shield tunneling-induced ground settlement using machine learning techniques
- (2019) Renpeng Chen et al. Frontiers of Structural and Civil Engineering
- Strength evaluation of granite block samples with different predictive models
- (2019) Qiancheng Fang et al. ENGINEERING WITH COMPUTERS
- Feasibility of the indirect determination of blast-induced rock movement based on three new hybrid intelligent models
- (2019) Zhi Yu et al. ENGINEERING WITH COMPUTERS
- A genetic algorithm based aerothermal optimization of tip carving for an axial turbine blade
- (2019) H. Maral et al. INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
- Rotating Machinery Fault Diagnosis Based on Improved Multiscale Amplitude-Aware Permutation Entropy and Multiclass Relevance Vector Machine
- (2019) Chen et al. SENSORS
- Prediction of Blast-Induced Rock Movement During Bench Blasting: Use of Gray Wolf Optimizer and Support Vector Regression
- (2019) Zhi Yu et al. Natural Resources Research
- Prediction of BLEVE mechanical energy by implementation of artificial neural network
- (2019) Behrouz Hemmatian et al. JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
- Novel Intelligent Approach for Peak Shear Strength Assessment of Rock Joints on the Basis of the Relevance Vector Machine
- (2019) Caichu Xia et al. MATHEMATICAL PROBLEMS IN ENGINEERING
- Performance degradation prediction of mechanical equipment based on optimized multi-kernel relevant vector machine and fuzzy information granulation
- (2019) Fafa Chen et al. MEASUREMENT
- Predicting Blast-Induced Ground Vibration in Open-Pit Mines Using Vibration Sensors and Support Vector Regression-Based Optimization Algorithms
- (2019) Hoang Nguyen et al. SENSORS
- A hybrid method for improved stability prediction in construction projects: A case study of stope hangingwall stability
- (2018) Chongchong Qi et al. APPLIED SOFT COMPUTING
- Three hybrid intelligent models in estimating flyrock distance resulting from blasting
- (2018) Mohammadreza Koopialipoor et al. ENGINEERING WITH COMPUTERS
- Daily sea level prediction at Chiayi coast, Taiwan using extreme learning machine and relevance vector machine
- (2018) Moslem Imani et al. GLOBAL AND PLANETARY CHANGE
- A strength prediction model using artificial intelligence for recycling waste tailings as cemented paste backfill
- (2018) Chongchong Qi et al. JOURNAL OF CLEANER PRODUCTION
- Prediction of sulfur solubility in supercritical sour gases using grey wolf optimizer-based support vector machine
- (2018) Xiao-Qiang Bian et al. JOURNAL OF MOLECULAR LIQUIDS
- Krill herd algorithm-based neural network in structural seismic reliability evaluation
- (2018) Panagiotis G. Asteris et al. MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
- ICA-ANN, ANN and multiple regression models for prediction of surface settlement caused by tunneling
- (2018) Mohammad Reza Moghaddasi et al. TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
- Prediction of Slope Stability Using Four Supervised Learning Methods
- (2018) Yun Lin et al. IEEE Access
- Transformer Health Management Based on Self-Powered RFID Sensor and Multiple Kernel RVM
- (2018) Tao Wang et al. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
- Evaluation method of rockburst: State-of-the-art literature review
- (2018) Jian Zhou et al. TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
- Stark Assessment of Lifestyle Based Human Disorders Using Data Mining Based Learning Techniques
- (2017) M. Sharma et al. IRBM
- A switching delayed PSO optimized extreme learning machine for short-term load forecasting
- (2017) Nianyin Zeng et al. NEUROCOMPUTING
- Feed-Forward Neural Network Prediction of the Mechanical Properties of Sandcrete Materials
- (2017) Panagiotis Asteris et al. SENSORS
- Application of Support Vector Machine, Random Forest, and Genetic Algorithm Optimized Random Forest Models in Groundwater Potential Mapping
- (2017) Seyed Amir Naghibi et al. WATER RESOURCES MANAGEMENT
- Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance
- (2017) Narinder Singh et al. Journal of Applied Mathematics
- Feasibility of Random-Forest Approach for Prediction of Ground Settlements Induced by the Construction of a Shield-Driven Tunnel
- (2017) Jian Zhou et al. International Journal of Geomechanics
- 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
- Classification and regression tree technique in estimating peak particle velocity caused by blasting
- (2016) Manoj Khandelwal et al. ENGINEERING WITH COMPUTERS
- Classification of Rockburst in Underground Projects: Comparison of Ten Supervised Learning Methods
- (2016) Jian Zhou et al. JOURNAL OF COMPUTING IN CIVIL ENGINEERING
- Feasibility of ICA in approximating ground vibration resulting from mine blasting
- (2016) Danial Jahed Armaghani et al. NEURAL COMPUTING & APPLICATIONS
- Airblast prediction through a hybrid genetic algorithm-ANN model
- (2016) Danial Jahed Armaghani et al. NEURAL COMPUTING & APPLICATIONS
- Improving protein-protein interactions prediction accuracy using protein evolutionary information and relevance vector machine model
- (2016) Ji-Yong An et al. PROTEIN SCIENCE
- Prediction of Military Vehicle’s Drawbar Pull Based on an Improved Relevance Vector Machine and Real Vehicle Tests
- (2016) Fan Yang et al. SENSORS
- Prediction of the Fundamental Period of Infilled RC Frame Structures Using Artificial Neural Networks
- (2016) Panagiotis G. Asteris et al. Computational Intelligence and Neuroscience
- Prediction of the strength and elasticity modulus of granite through an expert artificial neural network
- (2015) Danial Jahed Armaghani et al. Arabian Journal of Geosciences
- Feasibility of indirect determination of blast induced ground vibration based on support vector machine
- (2015) Mahdi Hasanipanah et al. MEASUREMENT
- Classification of electromyography signals using relevance vector machines and fractal dimension
- (2015) Clodoaldo A. M. Lima et al. NEURAL COMPUTING & APPLICATIONS
- A novel hybrid PSO–GWO approach for unit commitment problem
- (2015) Vikram Kumar Kamboj NEURAL COMPUTING & APPLICATIONS
- Grey Wolf Optimizer
- (2014) Seyedali Mirjalili et al. ADVANCES IN ENGINEERING SOFTWARE
- Prediction of the unconfined compressive strength of soft rocks: a PSO-based ANN approach
- (2014) Edy Tonnizam Mohamad et al. Bulletin of Engineering Geology and the Environment
- Modeling tunneling-induced ground surface settlement development using a wavelet smooth relevance vector machine
- (2013) Fan Wang et al. COMPUTERS AND GEOTECHNICS
- Calculation of surface settlements caused by EPBM tunneling using artificial neural network, SVM, and Gaussian processes
- (2013) Ibrahim Ocak et al. Environmental Earth Sciences
- Prediction of unconfined compressive strength of rock surrounding a roadway using artificial neural network
- (2012) Abbas Majdi et al. NEURAL COMPUTING & APPLICATIONS
- Wavenet ability assessment in comparison to ANN for predicting the maximum surface settlement caused by tunneling
- (2011) A. Pourtaghi et al. TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
- Application of relevance vector machine and survival probability to machine degradation assessment
- (2010) Achmad Widodo et al. EXPERT SYSTEMS WITH APPLICATIONS
- Application of soft computing to predict blast-induced ground vibration
- (2009) Manoj Khandelwal et al. ENGINEERING WITH COMPUTERS
- Prediction of uniaxial compressive strength of sandstones using petrography-based models
- (2007) K. Zorlu et al. ENGINEERING GEOLOGY
Add 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 NowCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now