Forecasting monthly copper price: A comparative study of various machine learning-based methods

Analyzing the potential for solar thermal energy utilization in the Chilean copper mining industry

(2020) Gonzalo Quiñones et al.   SOLAR ENERGY

A comparative analysis of gradient boosting algorithms

(2020) Candice Bentéjac et al.   ARTIFICIAL INTELLIGENCE REVIEW

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

Forecasting Copper Prices Using Hybrid Adaptive Neuro-Fuzzy Inference System and Genetic Algorithms

(2019) Zakaria Alameer et al.   Natural Resources Research

A novel signal amplification strategy based on the use of copper nanoclusters for ratiometric fluorimetric determination of o-phenylenediamine

(2019) Yujun Ma et al.   MICROCHIMICA ACTA

Prediction of ultimate bearing capacity through various novel evolutionary and neural network models

(2019) Hossein Moayedi et al.   ENGINEERING WITH COMPUTERS

Developing an XGBoost model to predict blast-induced peak particle velocity in an open-pit mine: a case study

(2019) Hoang Nguyen et al.   Acta Geophysica

Predicting blast-induced peak particle velocity using BGAMs, ANN and SVM: a case study at the Nui Beo open-pit coal mine in Vietnam

(2019) Hoang Nguyen et al.   Environmental Earth Sciences

Use of copper, silver and zinc nanoparticles against foliar and soil-borne plant pathogens

(2019) Anastasios A. Malandrakis et al.   SCIENCE OF THE TOTAL ENVIRONMENT

A Novel Artificial Intelligence Approach to Predict Blast-Induced Ground Vibration in Open-Pit Mines Based on the Firefly Algorithm and Artificial Neural Network

(2019) Yonghui Shang et al.   Natural Resources Research

A new technique to predict fly-rock in bench blasting based on an ensemble of support vector regression and GLMNET

(2019) Hongquan Guo et al.   ENGINEERING WITH COMPUTERS

A Novel Hybrid Model for Predicting Blast-Induced Ground Vibration Based on k-Nearest Neighbors and Particle Swarm Optimization

(2019) Xuan-Nam Bui et al.   Scientific Reports

Estimation of Blast-Induced Air Overpressure in Quarry Mines Using Cubist-Based Genetic Algorithm

(2019) Qiancheng Fang et al.   Natural Resources Research

Prediction of Blast-Induced Ground Vibration in Open-Pit Mines Using a New Technique Based on Imperialist Competitive Algorithm and M5Rules

(2019) Qiancheng Fang et al.   Natural Resources Research

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

Forecasting mining capital cost for open-pit mining projects based on artificial neural network approach

(2019) Hongquan Guo et al.   RESOURCES POLICY

Gradient boosting machine for modeling the energy consumption of commercial buildings

(2018) Samir Touzani et al.   ENERGY AND BUILDINGS

A comparative study of artificial neural networks in predicting blast-induced air-blast overpressure at Deo Nai open-pit coal mine, Vietnam

(2018) Hoang Nguyen et al.   NEURAL COMPUTING & APPLICATIONS

An adaptive forecasting approach for copper price volatility through hybrid and non-hybrid models

(2018) Diego García et al.   APPLIED SOFT COMPUTING

Predicting Blast-Induced Air Overpressure: A Robust Artificial Intelligence System Based on Artificial Neural Networks and Random Forest

(2018) Hoang Nguyen et al.   Natural Resources Research

Random forests-based extreme learning machine ensemble for multi-regime time series prediction

(2017) Lin Lin et al.   EXPERT SYSTEMS WITH APPLICATIONS

Characterizing copper flows in international trade of China, 1975–2015

(2017) Ling Zhang et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Modeling river discharge time series using support vector machine and artificial neural networks

(2016) Mohammad Ali Ghorbani et al.   Environmental Earth Sciences

Copper demand, supply, and associated energy use to 2050

(2016) Ayman Elshkaki et al.   GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS

Deep learning

(2015) Yann LeCun et al.   NATURE

A review of unsupervised feature learning and deep learning for time-series modeling

(2014) Martin Längkvist et al.   PATTERN RECOGNITION LETTERS

A combination of artificial neural network and random walk models for financial time series forecasting

(2013) Ratnadip Adhikari et al.   NEURAL COMPUTING & APPLICATIONS

Gradient boosting trees for auto insurance loss cost modeling and prediction

(2011) Leo Guelman   EXPERT SYSTEMS WITH APPLICATIONS