[1] Safai Naeini, J., & Farahmand, Mohammad Reza. (2018, July 12).
investigating the application of neuro-fuzzy model in stock price forecasting of tehran stock exchange companies. 2nd national conference on computer and information technology, Fars, Iran.
https://civilica.com/doc/813581
[2] Dehnavi, V. S., & Shafiee, M. (2020, August 4-6).
LQR for Generalized Systems Using Metaheuristic Algorithms Based on Disturbance Observer. 28th Iranian Conference on Electrical Engineering (ICEE), Tabriz, Iran.
https://ieeexplore.ieee. org/
abstract/document/9260723
[4] Wei, H., Kin Keung, Lai., Yoshiteru, Nakamori., Shouyang, Wang.,, & & Lean, Y. (2007). Neural networks in finance and economics forecasting.
International Journal of Information Technology & Decision Making,
06(01), 113-140.
https://doi.org/10.1142/s021962200700237x
[5] Pourdadashi Komachali, F., & Shafiee, Masoud. (2020). Sensor fault diagnosis in fractional-order singular systems using unknown input observer.
International Journal of Systems Science,
51(1), 116-132.
https://doi.org/10.1080/00207721.201 9.
1701135
[7] Bahmani, m., & NezamTaheri, S. S. (2020). Evaluating the Effect of Earning Smoothing Using Maximization and Minimization of Earnings Approaches to Reduce Stock Price Crash Risk in Companies Accepted in Tehran Stock Exchange.
Karafan Quarterly Scientific Journal,
16(46), 253-274.
https://karafan.tvu.ac
.ir/article_105729_379d82d24a52acf40d3e0743bd38c076.pdf
[8] Kelly, L. J. (2011). The current stock of money: an aggregation theoretic measure of narrowly defined money.
Applied Economics Letters,
18(7), 659-664.
https://doi.org/
10.1080/13504851003800778
[9] Çakıt, E., Olak, Andrzej Jan., Karwowski, Waldemar., Marek, Tadeusz., Hejduk, Irena., & Taiar, Redha. (2020). Assessing safety at work using an adaptive neuro-fuzzy inference system (ANFIS) approach aided by partial least squares structural equation modeling (PLS-SEM).
International Journal of Industrial Ergonomics,
76(3), 102925.
https://doi.org/10.1016/j.ergon.2020.102925
[12] Moayedi, H., Raftari, M., Sharifi, A., Jusoh, W. A. W., & Rashid, A. S. A. (2020). Optimization of ANFIS with GA and PSO estimating α ratio in driven piles.
Engineering with Computers,
36(1), 227-238.
https://doi.org/10.1007/s00366-018-00694-w
[13] Noushabadi, A. S., Dashti, A., Raji, M., Zarei, A., & Mohammadi, A. H. (2020). Estimation of cetane numbers of biodiesel and diesel oils using regression and PSO-ANFIS models.
Renewable Energy,
158, 465-473.
https://doi.org/10.1016/j.ren
ene.2020.04.146
[14] Shqair, M., Al-Smadi, M., Momani, S., & El-Zahar, E. (2020). Adaptation of Conformable Residual Power Series Scheme in Solving Nonlinear Fractional Quantum Mechanics Problems.
Applied Sciences,
10(3), 890.
https://doi.org/10.3390/
app10030890
[15] Cuevas, E., Gálvez, J., & Avalos, O. (2020). Gravitational search algorithm for non-linear system identification using ANFIS-Hammerstein approach. In
Recent Metaheuristics Algorithms for Parameter Identification. Springer.
https://doi.org/10.
1007/978-3-030-28917-1_5
[17] Heydarinejad, H., & Shafiee, M. (2019, April 30-May 2 ).
Super Twisting Sliding Mode Control for LTI Descriptor System Based on Disturbance Observer. 27th Iranian Conference on Electrical Engineering (ICEE), Yazd, Iran. https://ieeexplore.
ieee.org/abstract/document/8786610
[18] Monajemi, S., Abzari, M., & Rayati, A. (2010). The prediction of prices in the stock market using fuzzy neural network and genetic algorithm and comparing it with artificial neural network.
Quantitative Economics Quarterly,
6(3), 1-26. https://doi.
org/10.22055/JQE.2009.10697
[19] Pourzamani, Z., Kipour, Reza., & Noureddin, Mostafa. (2010). Investigating the Capability of Financial Crisis Prediction Patterns (Study Patterns: Patterns Based on Traditional Methods, Genetic Algorithms and Neural Networks).
Financial Engineering And Securities Management (Portfolio Management),
1(4), 1-28.
https://www.sid.ir/fa/journal/ViewPaper.aspx?id=134248
[20] Etemadi, H., Azar, Adel., & Baqaei, Vahid. (2012). Using Neural Networks in Predicting Profitability of Companies (Tehran Stock Exchange Member Companies).
Accounting knowledge,
3(10), 51-70.
https://www.sid.ir/fa/journal/View
Paper.aspx?id=176000
[21] Pourzamani, Z. (2015). Application of Linear and Nonlinear Genetic Algorithms in Improving the Profitability Prediction of Companies.
Financial Engineering And Securities Management (Portfolio Management),
6(22), 81-94.
https://www.sid.ir/Fa/
Journal/ViewPaper.aspx?id=238474
[22] Alian, H. R. H., . (2016, May 4).
A survey of stock price index forecasting using computational methods (artificial neural network) in tehran stock exchange. The 1st conference on accounting, economics and innovation in management, Bandar Abbas, Iran.
https://civilica.com/doc/561065/
[23] Soghriharavani, e. m., masoud. (2017, May 3).
the use of neural networks to predict prices in the stock market. 10th international conference of iranian operations research association, Babolsar, Iran.
https://civilica.com/doc/767006/
[24] Miralavi, S. H &,. Pourzamani, Z. (2019). Proposing a model for stock price forecasting using meta-heuristic methods and neural networks.
financial engineering and securities management 10(40), 57-83.
https://civilica.com/doc/958480/
[25] Samadipour, S., Matinfard, R. Torkashvand, Ahmad. (2020, May 20).
investigation and prediction of stock loss or growth in stock exchange companies in a given period using classification data mining technique. 3rd international conference on new solutions in engineering, information science and technology in the century ahead, Tehran, Iran.
https://civilica.com/doc/1017557/certificate/print/
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