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Development of the FA-KNN hybrid algorithm and its application to reservoir operation
This study presents a method to address the issue of burdensome computations in water resources optimization based on a hybrid algorithm derived from...
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KNN-GCN: A Deep Learning Approach for Slope-Unit-Based Landslide Susceptibility Map** Incorporating Spatial Correlations
Landslides pose a significant risk to human life and property, making landslide susceptibility map** (LSM) a crucial component of landslide risk...
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Advanced KNN Approaches for Explainable Seismic-Volcanic Signal Classification
Acquisition, classification, and analysis of seismic data are crucial tasks in volcano monitoring. The large number of seismic signals that are...
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Prediction of resilient modulus of fine-grained soil for pavement design using KNN, MARS, and random forest techniques
This study was motivated by the difficulty in determining the resilient modulus of soils using the repeated load triaxial test (RLTT) recommended by...
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Comprehensive classification assessment of GNSS observation data quality by fusing k-means and KNN algorithms
The observation data is the basis for the global navigation satellite system (GNSS) to provide positioning, navigation and timing (PNT) service, and...
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A Rapid Forecast Method for the Process of Flash Flood Based on Hydrodynamic Model and KNN Algorithm
Using hydrodynamic models to carry out early warning and flash floods forecasting is an essential measure for loss reduction. Nevertheless, many...
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Optimization of negative sample selection for landslide susceptibility map** based on machine learning using K-means-KNN algorithm
The quality of the sample plays a vital role in develo** accurate models using machine learning. This aspect is equally important when evaluating...
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Robust outlier detection in geo-spatial data based on LOLIMOT and KNN search
One of the most challenging topics in analyzing multi-dimensional geo-spatial data such as geophysical data-sets is detecting outlier data. The issue...
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The PCA-KD-KNN-based water chemistry identification model of water inrush source type in mine and its application
The rapid and accurate identification of water inrush source plays an important role in preventing and controlling mine water inrush disaster....
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GECA Proposed Ensemble–KNN Method for Improved Monthly Runoff Forecasting
Medium- to long-term runoff forecasting on monthly timescales is an important aspect of formulating long-term water resource dispatch plans, making...
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The Anomaly Detector, Semi-supervised Classifier, and Supervised Classifier Based on K-Nearest Neighbors in Geochemical Anomaly Detection: A Comparative Study
Unsupervised anomaly detection techniques mainly model the population distribution of geochemical exploration data, but do not consider the mineral...
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Application of geophysical and multispectral imagery data for predictive map** of a complex geo-tectonic unit: a case study of the East Vardar Ophiolite Zone, North-Macedonia
The Random Forest (RF) and K nearest neighbors (KNN) machine learning (ML) algorithms were evaluated for their ability to predict ophiolite...
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Translation of machine learning approaches into gas hydrate saturation proxy: a case study from Krishna-Godavari (KG) offshore basin
Empirical methods often fail to accurately depict in-situ gas hydrate saturation distributions, despite their relationships with petrophysical and...
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Monthly River Discharge Forecasting Using Hybrid Models Based on Extreme Gradient Boosting Coupled with Wavelet Theory and Lévy–Jaya Optimization Algorithm
River discharge represents critical hydrological data that can be used to monitor the hydrological status of a river basin. The objective of this...
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Prediction of Hydrological Drought in Semi-arid Regions Using a Novel Hybrid Model
Hydrological drought is one of the most important natural phenomena affecting the various aspects of life on Earth, especially with the increasing...
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Evaporation Prediction with Wavelet-Based Hyperparameter Optimized K-Nearest Neighbors and Extreme Gradient Boosting Algorithms in a Semi-Arid Environment
The study aims to reveal which mother wavelet type performs best in evaporation prediction. This study used a hybrid algorithm that combined...
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Map** and analysing framework for extreme precipitation-induced flooding
A conceptual framework is proposed, to identify flood affected locations that should be considered in order to lessen the consequences of naturally...
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A Robust Strategy of Geophysical Logging for Predicting Payable Lithofacies to Forecast Sweet Spots Using Digital Intelligence Paradigms in a Heterogeneous Gas Field
The most crucial elements in the oil and gas sector are predicting subsurface lithofacies utilizing geophysical logs for reservoir characterization...
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Gas-Bearing Reservoir Prediction Using k-nearest neighbor Based on Nonlinear Directional Dimension Reduction
In this study, a k-nearest neighbor (kNN) method based on nonlinear directional dimension reduction is applied to gas-bearing reservoir prediction....
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A novel approach to estimate rock deformation under uniaxial compression using a machine learning technique
Understanding rock deformation is crucial for various engineering and geological applications, including mining, tunneling, and earthquake...
