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Forecasting gold price fluctuations using improved multilayer perceptron neural network and whale optimization algorithm

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  1. Dąbrowska Dominika & Rykała Wojciech & Nourani Vahid, 2023. "The impact of weather conditions on the quality of groundwater in the area of a municipal waste landfill," Environmental & Socio-economic Studies, Sciendo, vol. 11(3), pages 14-21, September.
  2. Zhang, Pinyi & Ci, Bicong, 2020. "Deep belief network for gold price forecasting," Resources Policy, Elsevier, vol. 69(C).
  3. Ozdemir, Ali Can & Buluş, Kurtuluş & Zor, Kasım, 2022. "Medium- to long-term nickel price forecasting using LSTM and GRU networks," Resources Policy, Elsevier, vol. 78(C).
  4. Ebubekir Kaya, 2022. "A Comprehensive Comparison of the Performance of Metaheuristic Algorithms in Neural Network Training for Nonlinear System Identification," Mathematics, MDPI, vol. 10(9), pages 1-25, May.
  5. Yong, Weixun & Zhang, Wengang & Nguyen, Hoang & Bui, Xuan-Nam & Choi, Yosoon & Nguyen-Thoi, Trung & Zhou, Jian & Tran, Trung Tin, 2022. "Analysis and prediction of diaphragm wall deflection induced by deep braced excavations using finite element method and artificial neural network optimized by metaheuristic algorithms," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
  6. Devendra Joshi & Premkumar Chithaluru & Divya Anand & Fahima Hajjej & Kapil Aggarwal & Vanessa Yelamos Torres & Ernesto Bautista Thompson, 2023. "RETRACTED: An Evolutionary Technique for Building Neural Network Models for Predicting Metal Prices," Mathematics, MDPI, vol. 11(7), pages 1-19, March.
  7. Peng Zhang & Xin Ma & Kun She, 2019. "A Novel Power-Driven Grey Model with Whale Optimization Algorithm and Its Application in Forecasting the Residential Energy Consumption in China," Complexity, Hindawi, vol. 2019, pages 1-22, November.
  8. Du, Pei & Guo, Ju’e & Sun, Shaolong & Wang, Shouyang & Wu, Jing, 2021. "Multi-step metal prices forecasting based on a data preprocessing method and an optimized extreme learning machine by marine predators algorithm," Resources Policy, Elsevier, vol. 74(C).
  9. Zhou, Jianguo & Xu, Zhongtian, 2023. "A novel three-stage hybrid learning paradigm based on a multi-decomposition strategy, optimized relevance vector machine, and error correction for multi-step forecasting of precious metal prices," Resources Policy, Elsevier, vol. 80(C).
  10. Syed Abul, Basher & Perry, Sadorsky, 2022. "Forecasting Bitcoin price direction with random forests: How important are interest rates, inflation, and market volatility?," MPRA Paper 113293, University Library of Munich, Germany.
  11. Nguyen, Quynh Nga & Bedoui, Rihab & Majdoub, Najemeddine & Guesmi, Khaled & Chevallier, Julien, 2020. "Hedging and safe-haven characteristics of Gold against currencies: An investigation based on multivariate dynamic copula theory," Resources Policy, Elsevier, vol. 68(C).
  12. Wang, Yang & Cao, Xinbang & Sui, Xiuping & Zhao, Wenxi, 2019. "How do black swan events go global? -Evidence from US reserves effects on TOCOM gold futures prices," Finance Research Letters, Elsevier, vol. 31(C).
  13. Shang, Yue & Wei, Yu & Chen, Yongfei, 2022. "Cryptocurrency policy uncertainty and gold return forecasting: A dynamic Occam's window approach," Finance Research Letters, Elsevier, vol. 50(C).
  14. Guo, Honggang & Wang, Jianzhou & Li, Zhiwu & Lu, Haiyan & Zhang, Linyue, 2022. "A non-ferrous metal price ensemble prediction system based on innovative combined kernel extreme learning machine and chaos theory," Resources Policy, Elsevier, vol. 79(C).
  15. Ewees, Ahmed A. & Elaziz, Mohamed Abd & Alameer, Zakaria & Ye, Haiwang & Jianhua, Zhang, 2020. "Improving multilayer perceptron neural network using chaotic grasshopper optimization algorithm to forecast iron ore price volatility," Resources Policy, Elsevier, vol. 65(C).
  16. Liu, Qing & Liu, Min & Zhou, Hanlu & Yan, Feng, 2022. "A multi-model fusion based non-ferrous metal price forecasting," Resources Policy, Elsevier, vol. 77(C).
  17. Zhang, Hong & Nguyen, Hoang & Bui, Xuan-Nam & Nguyen-Thoi, Trung & Bui, Thu-Thuy & Nguyen, Nga & Vu, Diep-Anh & Mahesh, Vinyas & Moayedi, Hossein, 2020. "Developing a novel artificial intelligence model to estimate the capital cost of mining projects using deep neural network-based ant colony optimization algorithm," Resources Policy, Elsevier, vol. 66(C).
  18. Chun-Yao Lee & Guang-Lin Zhuo, 2021. "A Hybrid Whale Optimization Algorithm for Global Optimization," Mathematics, MDPI, vol. 9(13), pages 1-19, June.
  19. Perry Sadorsky, 2021. "Predicting Gold and Silver Price Direction Using Tree-Based Classifiers," JRFM, MDPI, vol. 14(5), pages 1-21, April.
  20. Tripathi Manas & Kumar Saurabh & Inani Sarveshwar Kumar, 2021. "Exchange Rate Forecasting Using Ensemble Modeling for Better Policy Implications," Journal of Time Series Econometrics, De Gruyter, vol. 13(1), pages 43-71, January.
  21. Na Fu & Liyan Geng & Junhai Ma & Xue Ding, 2023. "Price, Complexity, and Mathematical Model," Mathematics, MDPI, vol. 11(13), pages 1-30, June.
  22. Alameer, Zakaria & Fathalla, Ahmed & Li, Kenli & Ye, Haiwang & Jianhua, Zhang, 2020. "Multistep-ahead forecasting of coal prices using a hybrid deep learning model," Resources Policy, Elsevier, vol. 65(C).
  23. Shi, Tao & Li, Chongyang & Zhang, Wei & Zhang, Yi, 2023. "Forecasting on metal resource spot settlement price: New evidence from the machine learning model," Resources Policy, Elsevier, vol. 81(C).
  24. Khoshalan, Hasel Amini & Shakeri, Jamshid & Najmoddini, Iraj & Asadizadeh, Mostafa, 2021. "Forecasting copper price by application of robust artificial intelligence techniques," Resources Policy, Elsevier, vol. 73(C).
  25. Huang, Yu-ting & Bai, Yu-long & Yu, Qing-he & Ding, Lin & Ma, Yong-jie, 2022. "Application of a hybrid model based on the Prophet model, ICEEMDAN and multi-model optimization error correction in metal price prediction," Resources Policy, Elsevier, vol. 79(C).
  26. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou, 2021. "Gold Against the Machine," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 5-28, January.
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