Related references
Note: Only part of the references are listed.Multi-objective robust optimisation model for MDVRPLS in refined oil distribution
Xiaofeng Xu et al.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH (2022)
Pavement anomaly detection based on transformer and self-supervised learning
Zijie Lin et al.
AUTOMATION IN CONSTRUCTION (2022)
Application of deep neural network to capture groundwater potential zone in mountainous terrain, Nepal Himalaya
Ananta Man Singh Pradhan et al.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2021)
Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, India
Aman Arora et al.
SCIENCE OF THE TOTAL ENVIRONMENT (2021)
Comparison of gradient boosted decision trees and random forest for groundwater potential mapping in Dholpur (Rajasthan), India
Shruti Sachdeva et al.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2021)
A new strategy for spatial predictive mapping of mineral prospectivity: Automated hyperparameter tuning of random forest approach
Mehrdad Daviran et al.
COMPUTERS & GEOSCIENCES (2021)
A comparative study of machine learning and Fuzzy-AHP technique to groundwater potential mapping in the data-scarce region
Ranveer Kumar et al.
COMPUTERS & GEOSCIENCES (2021)
Flash-Flood Potential Mapping Using Deep Learning, Alternating Decision Trees and Data Provided by Remote Sensing Sensors
Romulus Costache et al.
SENSORS (2021)
Mapping the spatial and temporal variability of flood hazard affected by climate and land-use changes in the future
Saeid Janizadeh et al.
JOURNAL OF ENVIRONMENTAL MANAGEMENT (2021)
Assessment of landslide susceptibility mapping based on Bayesian hyperparameter optimization: A comparison between logistic regression and random forest
Deliang Sun et al.
ENGINEERING GEOLOGY (2021)
Groundwater recharge potential zonation using an ensemble of machine learning and bivariate statistical models
Maryam Sadat Jaafarzadeh et al.
SCIENTIFIC REPORTS (2021)
Mapping Groundwater Potential Zones Using a Knowledge-Driven Approach and GIS Analysis
Qiande Zhu et al.
WATER (2021)
Improving GALDIT-based groundwater vulnerability predictive mapping using coupled resampling algorithms and machine learning models
Rahim Barzegar et al.
JOURNAL OF HYDROLOGY (2021)
Application of machine learning algorithms for flood susceptibility assessment and risk management
R. Madhuri et al.
JOURNAL OF WATER AND CLIMATE CHANGE (2021)
Modeling of coupled transfer of water, heat and solute in saline loess considering sodium sulfate crystallization
Jian Xu et al.
COLD REGIONS SCIENCE AND TECHNOLOGY (2021)
Quadratic Discriminant Analysis Based Ensemble Machine Learning Models for Groundwater Potential Modeling and Mapping
Duong Hai Ha et al.
WATER RESOURCES MANAGEMENT (2021)
Advanced data mining techniques for landslide susceptibility mapping
Muhammad Bello Ibrahim et al.
GEOMATICS NATURAL HAZARDS & RISK (2021)
Efficient hyperparameter tuning for kernel ridge regression with Bayesian optimization
Annika Stuke et al.
MACHINE LEARNING-SCIENCE AND TECHNOLOGY (2021)
Application of convolutional neural networks featuring Bayesian optimization for landslide susceptibility assessment
Maher Ibrahim Sameen et al.
CATENA (2020)
Mapping of Groundwater Potential Zones in Crystalline Terrain Using Remote Sensing, GIS Techniques, and Multicriteria Data Analysis (Case of the Ighrem Region, Western Anti-Atlas, Morocco)
Khalid Benjmel et al.
WATER (2020)
Distributed Bayesian optimization of deep reinforcement learning algorithms
M. Todd Young et al.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING (2020)
A random forest model of landslide susceptibility mapping based on hyperparameter optimization using Bayes algorithm
Deliang Sun et al.
GEOMORPHOLOGY (2020)
Divergent effects of climate change on future groundwater availability in key mid-latitude aquifers
Wen-Ying Wu et al.
NATURE COMMUNICATIONS (2020)
On hyperparameter optimization of machine learning algorithms: Theory and practice
Li Yang et al.
NEUROCOMPUTING (2020)
Effectiveness of groundwater heavy metal pollution indices studies by deep-learning
Sudhakar Singha et al.
JOURNAL OF CONTAMINANT HYDROLOGY (2020)
Rainfall Induced Landslide Susceptibility Mapping Based on Bayesian Optimized Random Forest and Gradient Boosting Decision Tree Models-A Case Study of Shuicheng County, China
Guangzhi Rong et al.
WATER (2020)
Hyperparameter optimization for recommender systems through Bayesian optimization
B. G. Galuzzi et al.
COMPUTATIONAL MANAGEMENT SCIENCE (2020)
Potential groundwater recharge zones within New Zealand
Shailesh Kumar Singh et al.
GEOSCIENCE FRONTIERS (2019)
Groundwater potential mapping using a novel data-mining ensemble model
Mojtaba Dolat Kordestani et al.
HYDROGEOLOGY JOURNAL (2019)
GIS and AHP Techniques Based Delineation of Groundwater Potential Zones: a case study from Southern Western Ghats, India
P. Arulbalaji et al.
SCIENTIFIC REPORTS (2019)
How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions
Alexander Y. Sun et al.
ENVIRONMENTAL RESEARCH LETTERS (2019)
A Spatially Enhanced Data-Driven Multimodel to Improve Groundwater Forecasts in the High Plains Aquifer, USA
A. Amaranto et al.
WATER RESOURCES RESEARCH (2019)
Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data
Patrick Schratz et al.
ECOLOGICAL MODELLING (2019)
Review: Advances in groundwater potential mapping
S. Diaz-Alcaide et al.
HYDROGEOLOGY JOURNAL (2019)
Performance evaluation of textural features in improving land use/land cover classification accuracy of heterogeneous landscape using multi-sensor remote sensing data
Varun Narayan Mishra et al.
EARTH SCIENCE INFORMATICS (2019)
Groundwater potential mapping by combining fuzzy-analytic hierarchy process and GIS in Beysehir Lake Basin, Turkey
Erhan Sener et al.
ARABIAN JOURNAL OF GEOSCIENCES (2018)
The UN Sustainable Development Goals (SDGs) are a great gift to business!
Claus Stig Pedersen
25TH CIRP LIFE CYCLE ENGINEERING (LCE) CONFERENCE (2018)
Dual-polarimetric C-band SAR data for land use/land cover classification by incorporating textural information
Varun Narayan Mishra et al.
ENVIRONMENTAL EARTH SCIENCES (2017)
Evaluation of four supervised learning methods for groundwater spring potential mapping in Khalkhal region (Iran) using GIS-based features
Seyed Amir Naghibi et al.
HYDROGEOLOGY JOURNAL (2017)
Applicability of generalized additive model in groundwater potential modelling and comparison its performance by bivariate statistical methods
Fatemeh Falah et al.
GEOCARTO INTERNATIONAL (2017)
Hydrologic and Climatic Responses to Global Anthropogenic Groundwater Extraction
Yujin Zeng et al.
JOURNAL OF CLIMATE (2017)
Empirical comparison of cross-validation and internal metrics for tuning SVM hyperparameters
Edson Duarte et al.
PATTERN RECOGNITION LETTERS (2017)
Delineation of groundwater potential zone in hard rock terrain in Gangajalghati block, Bankura district, India using remote sensing and GIS techniques
Sujit Das
MODELING EARTH SYSTEMS AND ENVIRONMENT (2017)
Delineation of Groundwater Potential Zones in River Basins Using Geospatial Tools-an Example from Southern Western Ghats, Kerala, India
Hema C. Nair et al.
JOURNAL OF GEOVISUALIZATION AND SPATIAL ANALYSIS (2017)
Assessment of groundwater potential zones using multi-influencing factor (MIF) and GIS: a case study from Birbhum district, West Bengal
Raju Thapa et al.
APPLIED WATER SCIENCE (2017)
The global volume and distribution of modern groundwater
Tom Gleeson et al.
NATURE GEOSCIENCE (2016)
Integrated remote sensing and GIS approach for delineation of groundwater potential zones using aquifer parameters in Devak and Rui watershed of Jammu and Kashmir, India
A. S. Jasrotia et al.
ARABIAN JOURNAL OF GEOSCIENCES (2016)
Taking the Human Out of the Loop: A Review of Bayesian Optimization
Bobak Shahriari et al.
PROCEEDINGS OF THE IEEE (2016)
An approach to delineate groundwater recharge potential sites in Ambalantota, Sri Lanka using GIS techniques
I. P. Senanayake et al.
GEOSCIENCE FRONTIERS (2016)
Mapping groundwater recharge potential zone using a GIS approach in Hualian River, Taiwan
Hsin-Fu Yeh et al.
SUSTAINABLE ENVIRONMENT RESEARCH (2016)
Mapping of groundwater potential zones in Killinochi area, Sri Lanka, using GIS and remote sensing techniques
Pankaj Kumar et al.
SUSTAINABLE WATER RESOURCES MANAGEMENT (2016)
Investigation of density contrasts and geologic structures of hot springs in the Markazi Province of Iran using the gravity method
J. Nouraliee et al.
RUSSIAN GEOLOGY AND GEOPHYSICS (2015)
Application of analytical hierarchy process, frequency ratio, and certainty factor models for groundwater potential mapping using GIS
Yousef Razandi et al.
EARTH SCIENCE INFORMATICS (2015)
Groundwater spring potential mapping using bivariate statistical model and GIS in the Taleghan Watershed, Iran
D. Davoodi Moghaddam et al.
ARABIAN JOURNAL OF GEOSCIENCES (2015)
Groundwater potential mapping at Kurdistan region of Iran using analytic hierarchy process and GIS
Omid Rahmati et al.
ARABIAN JOURNAL OF GEOSCIENCES (2015)
ROC-based calibration of flood inundation models
G. J. -P. Schumann et al.
HYDROLOGICAL PROCESSES (2014)
Application of GIS based data driven evidential belief function model to predict groundwater potential zonation
Haleh Nampak et al.
JOURNAL OF HYDROLOGY (2014)
Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS
Mahyat Shafapour Tehrany et al.
JOURNAL OF HYDROLOGY (2014)
The global groundwater crisis
J. S. Famiglietti
NATURE CLIMATE CHANGE (2014)
Which data for quantitative landslide susceptibility mapping at operational scale? Case study of the Pays d'Auge plateau hillslopes (Normandy, France)
M. Fressard et al.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES (2014)
Delineation of groundwater potential zones in the crystalline basement terrain of SW-Nigeria: an integrated GIS and remote sensing approach
Olutoyin A. Fashae et al.
APPLIED WATER SCIENCE (2014)
Collinearity: a review of methods to deal with it and a simulation study evaluating their performance
Carsten F. Dormann et al.
ECOGRAPHY (2013)
Conjunctive Use of Surface Water and Groundwater: Application of Support Vector Machines (SVMs) and Genetic Algorithms
Hamid R. Safavi et al.
WATER RESOURCES MANAGEMENT (2013)
Application of remote sensing and GIS analysis for identifying groundwater potential zone in parts of Kodaikanal Taluk, South India
Murugesan Bagyaraj et al.
FRONTIERS OF EARTH SCIENCE (2013)
Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques
N. S. Magesh et al.
GEOSCIENCE FRONTIERS (2012)
Multicollinearity
Aylin Alin
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS (2010)
Using and comparing two nonparametric methods (CART and MARS) to model the potential distribution of gullies
Alvaro Gomez Gutierrez et al.
ECOLOGICAL MODELLING (2009)
Assessing the response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach
Michael S. Balshi et al.
GLOBAL CHANGE BIOLOGY (2009)
Assessment of Groundwater Potential Zones using GIS Technique
M. Nagarajan et al.
JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING (2009)
A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation
Nicolas Pinto et al.
PLOS COMPUTATIONAL BIOLOGY (2009)
Assessment of surface and sub-surface waterlogged areas in irrigation command areas of Bihar state using remote sensing and GIS
V. M. Chowdary et al.
AGRICULTURAL WATER MANAGEMENT (2008)
Deciphering potential groundwater zone in hard rock through the application of GIS
R. K. Prasad et al.
ENVIRONMENTAL GEOLOGY (2008)
Use of remote sensing and GIS to determine recharge potential zones: the case of Occidental Lebanon
A Shaban et al.
HYDROGEOLOGY JOURNAL (2006)
World map of the Koppen-Geiger climate classification updated
Markus Kottek et al.
METEOROLOGISCHE ZEITSCHRIFT (2006)
Support vector machines for classification in remote sensing
M Pal et al.
INTERNATIONAL JOURNAL OF REMOTE SENSING (2005)