相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Developing GEP tree-based, neuro-swarm, and whale optimization models for evaluation of bearing capacity of concrete-filled steel tube columns
Payam Sarir et al.
ENGINEERING WITH COMPUTERS (2021)
Landslide susceptibility modeling using different artificial intelligence methods: a case study at Muong Lay district, Vietnam
Tran Van Phong et al.
GEOCARTO INTERNATIONAL (2021)
Cost-Aware Multimedia Data Allocation for Heterogeneous Memory Using Genetic Algorithm in Cloud Computing
Keke Gai et al.
IEEE TRANSACTIONS ON CLOUD COMPUTING (2020)
Self-compacting concrete strength prediction using surrogate models
Panagiotis G. Asteris et al.
NEURAL COMPUTING & APPLICATIONS (2019)
Evaluation and comparison of LogitBoost Ensemble, Fisher's Linear Discriminant Analysis, logistic regression and support vector machines methods for landslide susceptibility mapping
Binh Thai Pham et al.
GEOCARTO INTERNATIONAL (2019)
A novel hybrid approach of Bayesian Logistic Regression and its ensembles for landslide susceptibility assessment
Mousa Abedini et al.
GEOCARTO INTERNATIONAL (2019)
A novel artificial intelligence approach based on Multi-layer Perceptron Neural Network and Biogeography-based Optimization for predicting coefficient of consolidation of soil
Binh Thai Pham et al.
CATENA (2019)
A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods
Khabat Khosravi et al.
JOURNAL OF HYDROLOGY (2019)
Artificial Intelligence Approaches for Prediction of Compressive Strength of Geopolymer Concrete
Dong Van Dao et al.
MATERIALS (2019)
Hybrid Machine Learning Approaches for Landslide Susceptibility Modeling
Vu Viet Nguyen et al.
FORESTS (2019)
Wildfire Probability Mapping: Bivariate vs. Multivariate Statistics
Abolfazl Jaafari et al.
REMOTE SENSING (2019)
Evaluating GIS-Based Multiple Statistical Models and Data Mining for Earthquake and Rainfall-Induced Landslide Susceptibility Using the LiDAR DEM
Jie Dou et al.
REMOTE SENSING (2019)
A Novel Ensemble Artificial Intelligence Approach for Gully Erosion Mapping in a Semi-Arid Watershed (Iran)
Dieu Tien Bui et al.
SENSORS (2019)
Hybrid Artificial Intelligence Approaches for Predicting Buckling Damage of Steel Columns Under Axial Compression
Lu Minh Le et al.
MATERIALS (2019)
Prediction and Sensitivity Analysis of Bubble Dissolution Time in 3D Selective Laser Sintering Using Ensemble Decision Trees
Hai-Bang Ly et al.
MATERIALS (2019)
Mapping Groundwater Potential Using a Novel Hybrid Intelligence Approach
Shaghayegh Miraki et al.
WATER RESOURCES MANAGEMENT (2019)
Prediction of Compressive Strength of Geopolymer Concrete Using Entirely Steel Slag Aggregates: Novel Hybrid Artificial Intelligence Approaches
Dong Van Dao et al.
APPLIED SCIENCES-BASEL (2019)
Assessing Dynamic Conditions of the Retaining Wall: Developing Two Hybrid Intelligent Models
Hui Chen et al.
APPLIED SCIENCES-BASEL (2019)
Determination of compound channel apparent shear stress: application of novel data mining models
Zohreh Sheikh Khozani et al.
JOURNAL OF HYDROINFORMATICS (2019)
Torrential rainfall-triggered shallow landslide characteristics and susceptibility assessment using ensemble data-driven models in the Dongjiang Reservoir Watershed, China
Jie Dou et al.
NATURAL HAZARDS (2019)
Quantification of Uncertainties on the Critical Buckling Load of Columns under Axial Compression with Uncertain Random Materials
Hai-Bang Ly et al.
MATERIALS (2019)
Landslide Susceptibility Mapping Using Different GIS-Based Bivariate Models
Ebrahim Nohani et al.
WATER (2019)
Hybrid Artificial Intelligence Approaches for Predicting Critical Buckling Load of Structural Members under Compression Considering the Influence of Initial Geometric Imperfections
Hai-Bang Ly et al.
APPLIED SCIENCES-BASEL (2019)
Application of artificial neural networks for predicting tree survival and mortality in the Hyrcanian forest of Iran
Mahmoud Bayat et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2019)
Optimization of an adaptive neuro-fuzzy inference system for groundwater potential mapping
Seyed Vahid Razavi Termeh et al.
HYDROGEOLOGY JOURNAL (2019)
Development of artificial intelligence models for the prediction of Compression Coefficient of soil: An application of Monte Carlo sensitivity analysis
Binh Thai Pham et al.
SCIENCE OF THE TOTAL ENVIRONMENT (2019)
Landslide Susceptibility Assessment by Novel Hybrid Machine Learning Algorithms
Binh Thai Pham et al.
SUSTAINABILITY (2019)
Prediction Success of Machine Learning Methods for Flash Flood Susceptibility Mapping in the Tafresh Watershed, Iran
Saeid Janizadeh et al.
SUSTAINABILITY (2019)
Development of Hybrid Artificial Intelligence Approaches and a Support Vector Machine Algorithm for Predicting the Marshall Parameters of Stone Matrix Asphalt
Hoang-Long Nguyen et al.
APPLIED SCIENCES-BASEL (2019)
Hybrid computational intelligence models for groundwater potential mapping
Binh Thai Pham et al.
CATENA (2019)
Evaluating scale effects of topographic variables in landslide susceptibility models using GIS-based machine learning techniques
Kuan-Tsung Chang et al.
SCIENTIFIC REPORTS (2019)
Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq
Khabat Khosravi et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2019)
Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan
Jie Dou et al.
SCIENCE OF THE TOTAL ENVIRONMENT (2019)
International Roughness Index Prediction of Flexible Pavements Using Neural Networks
M. Hossain et al.
JOURNAL OF TRANSPORTATION ENGINEERING PART B-PAVEMENTS (2019)
Compressive strength of natural hydraulic lime mortars using soft computing techniques
Maria Apostolopoulou et al.
3RD INTERNATIONAL CONFERENCE ON STRUCTURAL INTEGRITY (ICSI 2019) (2019)
Soft computing-based techniques for concrete beams shear strength
Danial J. Armaghani et al.
3RD INTERNATIONAL CONFERENCE ON STRUCTURAL INTEGRITY (ICSI 2019) (2019)
Hybrid Recommendation System for Heart Disease Diagnosis based on Multiple Kernel Learning with Adaptive Neuro-Fuzzy Inference System
Gunasekaran Manogaran et al.
MULTIMEDIA TOOLS AND APPLICATIONS (2018)
Wildfire spatial pattern analysis in the Zagros Mountains, Iran: A comparative study of decision tree based classifiers
Abolfazl Jaafari et al.
ECOLOGICAL INFORMATICS (2018)
Application of an Inexpensive Sensor in Calculating the International Roughness Index
Vahid Khalifeh et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2018)
A Novel Classifier Based on Composite Hyper-cubes on Iterated Random Projections for Assessment of Landslide Susceptibility
Binh Thai Pham
JOURNAL OF THE GEOLOGICAL SOCIETY OF INDIA (2018)
Spatial Prediction of Rainfall-Induced Landslides Using Aggregating One-Dependence Estimators Classifier
Binh Thai Pham et al.
JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING (2018)
A comparison study of DRASTIC methods with various objective methods for groundwater vulnerability assessment
Khabat Khosravi et al.
SCIENCE OF THE TOTAL ENVIRONMENT (2018)
International Roughness Index and a New Solution for Its Calculation
Jie Li et al.
JOURNAL OF TRANSPORTATION ENGINEERING PART B-PAVEMENTS (2018)
Particle swarm optimization trained neural network for structural failure prediction of multistoried RC buildings
Sankhadeep Chatterjee et al.
NEURAL COMPUTING & APPLICATIONS (2017)
The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded
Shinichi Nakagawa et al.
JOURNAL OF THE ROYAL SOCIETY INTERFACE (2017)
Prediction of IRI in short and long terms for flexible pavements: ANN and GMDH methods
Hasan Ziari et al.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING (2016)
Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree
Dieu Tien Bui et al.
LANDSLIDES (2016)
Prediction of pavement roughness using a hybrid gene expression programming-neural network technique
Mehran Mazari et al.
JOURNAL OF TRAFFIC AND TRANSPORTATION ENGINEERING-ENGLISH EDITION (2016)
Particle swarm optimization (PSO). A tutorial
Federico Marini et al.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2015)
Root mean square error (RMSE) or mean absolute error (MAE)? - Arguments against avoiding RMSE in the literature
T. Chai et al.
GEOSCIENTIFIC MODEL DEVELOPMENT (2014)
Development of a model for estimating International Roughness Index from pavement distresses
Amarendra Kumar Sandra et al.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING (2013)
Relationship between Pavement Roughness and Distress Parameters for Indian Highways
Satish Chandra et al.
JOURNAL OF TRANSPORTATION ENGINEERING (2013)
Road profile estimation using neural network algorithm
Mahdi Yousefzadeh et al.
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY (2010)
Applicability of the international roughness index as a predictor of asphalt pavement condition
Kyungwon Park et al.
JOURNAL OF TRANSPORTATION ENGINEERING (2007)
A Hybri of genetic algorithm and particle swarm optimization for recurrent network design
CF Juang
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS (2004)
Artificial neural networks: fundamentals, computing, design, and application
IA Basheer et al.
JOURNAL OF MICROBIOLOGICAL METHODS (2000)