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Forecasting stock price using grey-fuzzy technique and portfolio optimization by invasive weed optimization algorithm

机译：基于灰色模糊技术的股票价格预测及入侵杂草优化算法的投资组合优化

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A. Hajnoori; M. Amiri; A. Alimi;
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1. Forecasting stock price using grey-fuzzy technique and portfolio optimization by invasive weed optimization algorithm [J] . Hajnoori A., Amiri M., Alimi A. Decision Science Letters . 2013,第3期

机译：运用灰色模糊技术预测股价，并通过侵入性杂草优化算法进行投资组合优化
2. APPLICATION OF ROBUST OPTIMIZATION FOR A PRODUCT PORTFOLIO PROBLEM USING AN INVASIVE WEED OPTIMIZATION ALGORITHM [J] . Alireza Goli, Hasan Khademi Zare, Reza Tavakkoli-Moghaddam, Numerical Algebra, Control and Optimization . 2019,第2期

机译：侵入杂草优化算法应用鲁棒优化对产品组合问题的应用
3. Multistep-Ahead Stock Price Forecasting Based on Secondary Decomposition Technique and Extreme Learning Machine Optimized by the Differential Evolution Algorithm [J] . Zhenpeng Tang, Tingting Zhang, Junchuan Wu, Mathematical Problems in Engineering: Theory, Methods and Applications . 2020,第1期

机译：基于二级分解技术和差分演进算法优化的超级股票价格预测
4. Electricity prices forecasting using ANN Hybrid with Invasive Weed Optimization (IWO) [C] . Safari M.Ikhsan Khamil Mohd, Dahlan Nofri Yenita, Razali Nor Shahida, IEEE International Conference on System Engineering and Technology . 2013

机译：使用带入侵杂草优化（IWO）的ANN混合进行电价预测
5. Optimizing Investment Portfolios by Identification and Forecasting of Stock Bubbles for Selected Stocks Traded on the New York Stock Exchange. [D] . Robberts, Theunis Christoffel. 2017

机译：通过识别和预测在纽约证券交易所交易的选定股票的股票泡沫来优化投资组合。
6. Training Multilayer Perceptron with Genetic Algorithms and Particle Swarm Optimization for Modeling Stock Price Index Prediction [O] . Fatih Ecer, Sina Ardabili, Shahab S. Band, 2020

机译：培训多层情感与遗传算法和粒子群优化用于建模股价指数预测
7. Forecasting stock price using grey-fuzzy technique and portfolio optimization by invasive weed optimization algorithm [O] . A. Hajnoori, M. Amiri, A. Alimi 2013

机译：基于灰色模糊技术的股票价格预测及入侵杂草优化算法的投资组合优化

Forecasting stock price using grey-fuzzy technique and portfolio optimization by invasive weed optimization algorithm

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