Journal ArticleDOI
Forecasting copper prices by decision tree learning
TLDR
In this paper, a machine learning algorithm based on decision tree was used to predict future copper prices, with mean absolute percentage errors below 4% in both short-term and long-term.About:
This article is published in Resources Policy.The article was published on 2017-06-01. It has received 79 citations till now. The article focuses on the topics: Metal prices & Decision tree.read more
Citations
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Journal ArticleDOI
Non-ferrous metals price forecasting based on variational mode decomposition and LSTM network
TL;DR: A novel hybrid deep learning model is presented, which combines the VMD (variational mode decomposition) method and the LSTM (long short-term memory) network to construct a forecasting model, which has superior performance for non-ferrous metals price forecasting.
Journal ArticleDOI
Forecasting gold price fluctuations using improved multilayer perceptron neural network and whale optimization algorithm
TL;DR: A novel model for accurately forecasting long-term monthly gold price fluctuations using a recent meta-heuristic method called whale optimization algorithm (WOA) as a trainer to learn the multilayer perceptron neural network (NN), which demonstrates the superiority of the hybrid WOA–NN model over other models.
Journal ArticleDOI
Review of Supported Pd-Based Membranes Preparation by Electroless Plating for Ultra-Pure Hydrogen Production.
TL;DR: In this review, the most relevant advances in the preparation of supported Pd-based membranes for hydrogen production in recent years are presented, mainly focused in the incorporation of the hydrogen selective layer (palladium or palladium-based alloy) by the electroless plating.
Journal ArticleDOI
Copper price estimation using bat algorithm
Hesam Dehghani,Dejan Bogdanovic +1 more
TL;DR: In this paper, the Bat algorithm was used to predict the copper price volatility, and the determined equation with 0.132 of RMSE was used, which is better than the classic estimation methods.
Journal ArticleDOI
Improving multilayer perceptron neural network using chaotic grasshopper optimization algorithm to forecast iron ore price volatility
TL;DR: A novel model for accurately forecasting monthly iron ore price volatilities is proposed that integrates chaotic behavior into a recent meta-heuristic method grasshopper optimization algorithm to form a new GOA algorithm called chaotic grasshoppers optimization algorithm (CGOA), which is used as a trainer to learn the multilayer perceptron neural network (NN).
References
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Journal ArticleDOI
Classification and Regression Trees.
Journal ArticleDOI
Classification and regression trees
TL;DR: This article gives an introduction to the subject of classification and regression trees by reviewing some widely available algorithms and comparing their capabilities, strengths, and weakness in two examples.
Book
Classification and regression trees
TL;DR: The methodology used to construct tree structured rules is the focus of a monograph as mentioned in this paper, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
Journal ArticleDOI
Note on Regression and Inheritance in the Case of Two Parents
TL;DR: In this paper, the authors consider a population in which sexual selection and natural selection may or may not be taking place, and assume only that the deviations from the mean in the case of any organ of any generation follow exactly or closely the normal law of frequency.
Journal ArticleDOI
Measuring firm performance using financial ratios: A decision tree approach
TL;DR: Sensitivity analyses indicated that Earnings Before Tax-to-Equity Ratio and Net Profit Margin are the two most important variables, and the CHAID and C5.0 decision tree algorithms produced the best prediction accuracy.
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