خنده خوش، مژگان؛ حقیقی نیت،رضا(1395)، در نظر گرفتن عوامل مؤثر در پیشبینی شاخص قیمت بورس تهران با بهبود الگوریتم بهینهسازی ملخ در انتخاب بهترین نمونهها در مدل آموزش چندتایی شبکه عصبی، سومین کنفرانس بین المللی مدیریت، اقتصاد و حسابداری.
فرشیدورد، آیدا و هوشمندخلیق، فرناز و میرحسنی، سیدعلی،1400،رویکرد کارا مبتنی بر دسته بندی SVM و مدل تعادل ریسک برای تشکیل سبد سهام، چهاردهمین کنفرانس بین المللی انجمن ایرانی تحقیق در عملیات،مشهد،https://civilica.com/doc/1365965
میرعلوی، سیدحسین؛ پرزمانی، زهرا. مدلی جهت پیش بینی قیمت سهام با استفاده از روش های فرا ابتکاری و شبکه های عصبی، فصلنامه مهندسی مالی و مدیریت اوراق بهادار، 1398، شماره 40.
یزدانی خداشهری, محمدباقر, نسل موسوی, سید حسین, & حسینی شیروانی, میر سعید. (1402). انتخاب بهینه سبدسهام با استفاده از الگوریتم های یادگیری ماشین. دانش سرمایهگذاری, 12(48), 511-538.
Avery, C.N.; Chevalier, J.A.; Zeckhauser, R.J. The CAPS prediction system and stock market returns. Rev. Financ. 2016, 20, 1363–1381.
Basak, S.; Kar, S.; Saha, S.; Khaidem, L.; Dey, S.R. Predicting the direction of stock market prices using tree-based classifiers. N. Am. J. Econ. Financ. 2019, 47, 552–567.
Brownlees C, Gallo G. Financial econometric analysis at ultra-high frequency: data handling concerns. Comput Stat Data Anal. 2006;51(4):2232e2245.
Chandar, S.K. Stock market prediction using subtractive clustering for a neuro fuzzy hybrid approach. Clust. Comput. 2017, 22, 13159–13166
Chen, W., Zhang, H., Mehlawat, M.K., Jia, L., 2021. Mean–variance portfolio optimization using machine learning-based stock price prediction. Appl. Soft Comput. 100, 106943.
Di Persio, L.; Honchar, O. Recurrent neural networks approach to the financial forecast of Google assets. Int. J. Math. Comput. Simul. 2017, 11, 7–13
Durap, A. A comparative analysis of machine learning algorithms for predicting wave runup. Anthropocene Coasts 6, 17 (2023). https://doi.org/10.1007/s44218-023-00033-7
Ganser, A.; Hollaus, B.; Stabinger, S. Classification of Tennis Shots with a Neural Network Approach. Sensors 2021, 21, 5703.
Hota, H.S.; Handa, R.; Shrivas, A.K. Time Series Data Prediction Using Sliding Window Based RBF Neural Network. Int. J. Comput. Intell. Res. 2017, 13, 1145–1156.
Hushani, P. Using Autoregressive Modelling and Machine Learning for Stock Market Prediction and Trading. In Third International Congress on Information and Communication Technology; Springer: Singapore, 2018; pp. 767–774.
Jalota, Hemant & Mandal, Pawan & Thakur, Manoj & Mittal, Garima. (2022). A novel approach to incorporate investor’s preference in fuzzy multi-objective portfolio selection problem using credibility measure. Expert Systems with Applications. 212. 118583. 10.1016/j.eswa.2022.118583.
Khashei, M.; Hajirahimi, Z. Performance evaluation of series and parallel strategies for financial time series forecasting. Financ. Innov. 2017, 3, 24.
Melo, Maisa & Cardoso, Rodrigo & Jesus, Tales. (2022). Multiobjective Model Predictive Control for portfolio optimization with cardinality constraint. Expert Systems with Applications. 205. 117639. 10.1016/j.eswa.2022.117639.
Nguyen, D.H.D.; Tran, L.P.; Nguyen, V. Predicting Stock Prices Using Dynamic LSTM Models. Int. Conf. Appl. Inform. 2019, 6, 199–212.
Obthong, Mehtabhorn, Nongnuch Tantisantiwong, Watthanasak Jeamwatthanachai, and Gary Wills. 2020. A Survey on Machine Learning for Stock Price Prediction: Algorithms and Techniques. Paper presented at 2nd International Conference on Finance, Economics, Management and IT Business, Prague, Czech Republic, May 5–6.
Pagliaro, Antonio. 2023. "Forecasting Significant Stock Market Price Changes Using Machine Learning: Extra Trees Classifier Leads" Electronics 12, no. 21: 4551. https://doi.org/10.3390/electronics12214551
Paiva, F.D., Cardoso, R.T.N., Hanaoka, G.P., Duarte, W.M., 2019. Decision-making for financial trading: A fusion approach of machine learning and portfolio selection. Expert Syst. Appl. 115, 635–655.
Rajab, S.; Sharma, V. An interpretable neuro-fuzzy approach to stock price forecasting. Soft Comput. 2019, 23, 921–936.
Rouf, Nusrat, Majid Bashir Malik, Tasleem Arif, Sparsh Sharma, Saurabh Singh, Satyabrata Aich, and Hee-Cheol Kim. 2021. "Stock Market Prediction Using Machine Learning Techniques: A Decade Survey on Methodologies, Recent Developments, and Future Directions" Electronics 10, no. 21: 2717.
Sharma, S.; Ahmed, S.; Naseem, M.; Alnumay, W.S.; Singh, S.; Cho, G.H. A Survey on Applications of Artificial Intelligence for Pre-Parametric Project Cost and Soil Shear-Strength Estimation in Construction and Geotechnical Engineering. Sensors 2021, 21, 463.
Strader, T.J.; Rozycki, J.J.; Root, T.H.; Huang, Y.H.J. Machine Learning Stock Market Prediction Studies: Review and Research Directions. J. Int. Technol. Inf. Manag. 2020, 28, 63–83.
Wang, Xianhe & Ouyang, Yuliang & Li, You & Liu, Shu & Teng, Long & Wang, Bo. (2023). Multi-objective portfolio selection considering expected and total utility. Finance Research Letters. 58. 104552. 10.1016/j.frl.2023.104552.
Wang, Y., Zhang, H., Zhang, G., 2019. cPSO-CNN: An efficient PSO-based algorithm for fine-tuning hyper-parameters of convolutional neural networks. Swarm Evol. Comput. 49, 114–123
Wu, H.; Liu, Y.; Wang, J. Review of Text Classification Methods on Deep Learning. Comput. Mater. Contin. 2020, 63, 1309–1321.
Zhang, J.; Teng, Y.-F.; Chen, W. Support vector regression with modified firefly algorithm for stock price forecasting. Appl. Intell. 2018, 49, 1658–1674.
