Non-ferrous metals price forecasting based on variational mode decomposition and LSTM network

Y Liu, C Yang, K Huang, W Gui - Knowledge-Based Systems, 2020 - Elsevier
Non-ferrous metals are indispensable industrial materials and strategic supports of national
economic development. The price forecasting of non-ferrous metals is critical for investors …

Medium-to long-term nickel price forecasting using LSTM and GRU networks

AC Ozdemir, K Buluş, K Zor - Resources Policy, 2022 - Elsevier
Recently, nickel is a critical metal for manufacturing stainless steel, rechargeable electric
vehicle batteries, and alloys utilized in the state-of-the-art technologies. The use of more …

Forecasting rare earth stock prices with machine learning

I Henriques, P Sadorsky - Resources Policy, 2023 - Elsevier
Rare earth elements (REEs) are indispensable for producing green technologies and
electronics. Demand for REEs in clean energy technologies in 2040 are projected to be …

[HTML][HTML] Fuzzy rule-based prediction of gold prices using news affect

P Hajek, J Novotny - Expert Systems with Applications, 2022 - Elsevier
Because of gold's value, systems for predicting its price have attracted extensive interest in
the scientific and industrial communities. Diverse artificial intelligence methods outperform …

Forecasting copper price by application of robust artificial intelligence techniques

HA Khoshalan, J Shakeri, I Najmoddini, M Asadizadeh - Resources Policy, 2021 - Elsevier
Metal price is one of the most important and effective parameters in assessing different
projects such as industry and mining. In this regard, price variations can play a vital role in …

Multi-step-ahead copper price forecasting using a two-phase architecture based on an improved LSTM with novel input strategy and error correction

H Luo, D Wang, J Cheng, Q Wu - Resources Policy, 2022 - Elsevier
Accurate copper price forecasting plays a vital role in many aspects of economics. However,
the complicated fluctuations of copper price make it a challenging job. This study develops a …

Forecasting copper prices using hybrid adaptive neuro-fuzzy inference system and genetic algorithms

Z Alameer, MA Elaziz, AA Ewees, H Ye… - Natural Resources …, 2019 - Springer
An accurate forecasting model for the price volatility of minerals plays a vital role in future
investments and decisions for mining projects and related companies. In this paper, a hybrid …

A review of state-of-the-art techniques for the determination of the optimum cut-off grade of a metalliferous deposit with a bibliometric map** in a surface mine …

P Biswas, RK Sinha, P Sen - Resources Policy, 2023 - Elsevier
In terms of the global share, 95% of the non-metallic minerals, 90% of the metallic minerals,
and about 60% of coal are being mined out through surface mining methods. In a mining …

Copper price estimation using bat algorithm

H Dehghani, D Bogdanovic - Resources Policy, 2018 - Elsevier
The most effective parameter on the value of mining projects is metal price volatility.
Therefore, knowing the metal price volatility can help the managers and shareholders of the …

Point and interval prediction for non-ferrous metals based on a hybrid prediction framework

J Wang, X Niu, L Zhang, M Lv - Resources Policy, 2021 - Elsevier
As a bulk product with huge international circulation, non-ferrous metals have frequent and
severe price fluctuations, which have attracted great attention from academia and industry …