BIZNES IQTISODIY KO‘RSATKICHLARINI BOSHQARISH VA BASHORATLASH UCHUN NEYRON TARMOQLARI ALGORITMLARI TAHLILI

Ishmetov Bahrom Yangibayevich

Ushbu maqolada neyron tarmoqlar nima ekanligini ular qanday ishlashini va qanday vazifalarni hal qilishini va biznesda iqtisodiy ko‘rstakichlarni boshqarish va bashoratlashda qanday o‘rin egallashini ko‘rsatib beradi. Neyron tarmoqlar - bu odamlarni neyronlari (asab hujayralari) qanday ishlashiga o‘xshash tarzda ma’lumotlarni (ma’lumotlarni) uzatish, qayta ishlash va o‘rganish uchun yaratilgan ulangan birliklar yoki tugunlarning kompyuter modellari hisoblanadi va biznes rivojida katta ahamiyatga ega ekanligini ko‘rsatadi.

Name of journalRaqamli iqtisodiyot
Number of edition8-son
View count 25

Web Address https://infocom.uz/magazine-releases

DOI

Date of creation in the UzSCI system 04-11-2024

Read count 25

Date of publication 21-10-2024

Main LanguageO'zbek

Pages883-893

Tags

marketing

bashoratlash

kompozit

neyron tarmoqlar

iqtisodiy ko‘rsatkichlar

Ўзбек

Ushbu maqolada neyron tarmoqlar nima ekanligini ular qanday ishlashini va qanday vazifalarni hal qilishini va biznesda iqtisodiy ko‘rstakichlarni boshqarish va bashoratlashda qanday o‘rin egallashini ko‘rsatib beradi. Neyron tarmoqlar - bu odamlarni neyronlari (asab hujayralari) qanday ishlashiga o‘xshash tarzda ma’lumotlarni (ma’lumotlarni) uzatish, qayta ishlash va o‘rganish uchun yaratilgan ulangan birliklar yoki tugunlarning kompyuter modellari hisoblanadi va biznes rivojida katta ahamiyatga ega ekanligini ko‘rsatadi.

Tags

marketing

bashoratlash

kompozit

neyron tarmoqlar

iqtisodiy ko‘rsatkichlar

№ Author name position Name of organisation

1 Ishmetov B.Y. assistent Muhammad al-Xorazmiy nomidagi Toshkent azborot texnologiyalari unversiteti Urganch filiali

№ Name of reference

1 M. Aiken, Using a neural network to forecast inflation, Industrial Management &Data Systems 7 (1999) 296–301.

2 D. Alexander and L. R. Thomas, Monetary/Asset models of exchange rate determination: How well have they performed in the 1980’s? International Journal of Forecasting 3 (1987) 53–64

3 J. A. Anderson and E. Rosenfeld, Neurocomputing: Foundations of Research (MIT Press, Cambridge, MA, 1988).

4 S. I. Ao, Analysis of the interaction of Asian Pacific indices and forecasting opening prices by hybrid VAR and neural network procedures, in Proc. Int. Conf. on Computational Intelligence for Modelling, Control and Automation 2003, Vienna, Austria, (February 2003 a).

5 S. I. Ao, Incorporating correlated markets’ prices into stock modeling with neural network, in Proc. IASTED Int. Conf. on Modelling and Simulation 2003, Palm Springs, USA (February 2003b), pp. 353–358.

6 Lilin Cheng, Haixiang Zang, Anupam Trivedi, Dipti Srinivasan, Zhinong Wei, Guoqiang Sun. Mitigating the Impact of Photovoltaic Power Ramps on Intraday Economic Dispatch Using Reinforcement Forecasting. IEEE Transactions on Sustainable Energy, 2024, 15(1), pp. 3–12.

7 Qi Zhao. Research on prediction of enterprise economic growth based on monetary policy regulation. 2020 International Conference on Robots & Intelligent System (ICRIS), IEEE, Sanya, China. 2020, pp. 1–1.

8 Juan Li, ShuFeng Cong. Prediction of financial economic growth trend based on PVAR model. 2021 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), IEEE, Beihai, China, 2021, pp. 1–10.

9 Zhidong Deng, Nuo Tian, Kunpeng Liu, Di Wu. Trend prediction method of economic fixed base index of power industry based on time series. 2021 International Conference on Wireless Communications and Smart Grid (ICWCSG), IEEE, Hangzhou, China, 2021, pp. 1–4.

10 Cuiqin Liu. Prediction Method of the Industrial Economic Operation Index Based on an Improved Genetic Algorithm. 2021 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI), IEEE, Harbin, China, 2021.

11 H. F. de Mendonca, and A. F. G. Almeida, “Importance of credibility for business confidence: evidence from an emerging economy”,Empirical Economics, 2018.

12 H. Sakaji, R. Kuramoto, H. Matsushima, K. Izumi, T. Shimada, and K. Sunakawa, “Financial Text Data Analytics Frameworkfor Business Confidence Indices and Inter-Industry Relations”, Proceedings of the First Workshop on Financial Technology and Natural Language Processing, Macao, China, August 12, 2019, pp. 40-46.

13 S. Feuerriegela, and J. Gordon, “News-based forecasts of macroeconomic indicators: A semantic path model for interpretable predictions”, European Journal of Operational Research, vol. 272, no. 1, pp. 162-175, January, 2019.

14 V. Los, and D. Ocheretin “Construction of business confidence index based on a system of economic indicators”, ShS Web of Conferences, vol.65, 2019.

15 S. Arslankaya and V. Öz “Time Series Analysis on Sales Quantity in an Automotive Company and Estimation by Artificial Neural Networks”, Sakarya University Journal of Science,no. 22 (5), pp. 1482-1492, 2018.

16 Shi Dong, Yifan Sun, Nicolas Bohm Agostini. Spartan: A Sparsity-Adaptive Framework to Accelerate Deep Neural Network Training on GPUs. IEEE Transactions on Parallel and Distributed Systems, 2021.

17 Yangqin Feng, Lei Zhang, Juan Mo. Deep Manifold Preserving Autoencoder for Classifying Breast Cancer Histopathological ImaGES. IEEE Transactions on Computational Biology and Bioinformatics, 2020.

18 Mengru Du. Economic Forecast Model and Development Path Analysis Based on BP and RBF Neural Network. 2023 IEEE 12th International Conference on Communication Systems and Network Technologies (CSNT), 2023.

19 Elman J L. Finding structure in time. Cognitive Science, vol.14, pp.179–211, 1990.

20 Yun Kai, Huang Qiang, Ma Yixuan. Construction of Network Security Perception System Using Elman Neural Network. 2021 2nd International Conference on Computer Communication and Network Security (CCNS), 2021.

21 Zhilong Zhang, Xianjun Shi, Yufeng Long, Yufeng Qin, Jiapeng Lv, Li Zhao. Network Traffic Prediction Based on Improved GA-Elman Neural Network. 2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes, 2021.

22 Yufei Zhang, Jianping Zhao, Honggang Wu, Minghan Gao. A new IOIF Elman neural network for air quality prediction. 2022 2nd International Conference on Consumer Electronics and Computer Engineering (ICCECE), 2022.

23 Xinlei Cai, Jinzhou Zhu, Jiale Liu, Zijie Meng, Yuhang Huo, Yang Yu. Short- Term Power Prediction Method for Photovoltaic Power Generation Based on Elman Neural Network for Aspen Swarm Optimization. 2023 6th International Conference on Energy, Electrical and Power Engineering (CEEPE), 2023.

24 Xie Jialing, Shi Weifeng, Bi Zong, Song Tiewei. Research on Marine Electric Load Forecast Based on PSO-Elman Neural Network. 2021 4th International Conference on Energy, Electrical and Power Engineering (CEEPE), 2021.

25 Masoud Fetanat, Michael Stevens, Pankaj Jain, Christopher Hayward, Erik Meijering, Nigel H. Lovell. Fully Elman Neural Network: A Novel Deep Recurrent Neural Network Optimized by an Improved Harris Hawks Algorithm for Classification of Pulmonary Arterial Wedge Pressure. IEEE Transactions on Biomedical Engineering, 2022.

26 Rajesh Kumar. Memory Recurrent Elman Neural Network-Based Identification of Time-Delaed Nonlinear Dynamical System. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023.

Waiting

№	Name of reference
1	M. Aiken, Using a neural network to forecast inflation, Industrial Management &Data Systems 7 (1999) 296–301.
2	D. Alexander and L. R. Thomas, Monetary/Asset models of exchange rate determination: How well have they performed in the 1980’s? International Journal of Forecasting 3 (1987) 53–64
3	J. A. Anderson and E. Rosenfeld, Neurocomputing: Foundations of Research (MIT Press, Cambridge, MA, 1988).
4	S. I. Ao, Analysis of the interaction of Asian Pacific indices and forecasting opening prices by hybrid VAR and neural network procedures, in Proc. Int. Conf. on Computational Intelligence for Modelling, Control and Automation 2003, Vienna, Austria, (February 2003 a).
5	S. I. Ao, Incorporating correlated markets’ prices into stock modeling with neural network, in Proc. IASTED Int. Conf. on Modelling and Simulation 2003, Palm Springs, USA (February 2003b), pp. 353–358.
6	Lilin Cheng, Haixiang Zang, Anupam Trivedi, Dipti Srinivasan, Zhinong Wei, Guoqiang Sun. Mitigating the Impact of Photovoltaic Power Ramps on Intraday Economic Dispatch Using Reinforcement Forecasting. IEEE Transactions on Sustainable Energy, 2024, 15(1), pp. 3–12.
7	Qi Zhao. Research on prediction of enterprise economic growth based on monetary policy regulation. 2020 International Conference on Robots & Intelligent System (ICRIS), IEEE, Sanya, China. 2020, pp. 1–1.
8	Juan Li, ShuFeng Cong. Prediction of financial economic growth trend based on PVAR model. 2021 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), IEEE, Beihai, China, 2021, pp. 1–10.
9	Zhidong Deng, Nuo Tian, Kunpeng Liu, Di Wu. Trend prediction method of economic fixed base index of power industry based on time series. 2021 International Conference on Wireless Communications and Smart Grid (ICWCSG), IEEE, Hangzhou, China, 2021, pp. 1–4.
10	Cuiqin Liu. Prediction Method of the Industrial Economic Operation Index Based on an Improved Genetic Algorithm. 2021 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI), IEEE, Harbin, China, 2021.
11	H. F. de Mendonca, and A. F. G. Almeida, “Importance of credibility for business confidence: evidence from an emerging economy”,Empirical Economics, 2018.
12	H. Sakaji, R. Kuramoto, H. Matsushima, K. Izumi, T. Shimada, and K. Sunakawa, “Financial Text Data Analytics Frameworkfor Business Confidence Indices and Inter-Industry Relations”, Proceedings of the First Workshop on Financial Technology and Natural Language Processing, Macao, China, August 12, 2019, pp. 40-46.
13	S. Feuerriegela, and J. Gordon, “News-based forecasts of macroeconomic indicators: A semantic path model for interpretable predictions”, European Journal of Operational Research, vol. 272, no. 1, pp. 162-175, January, 2019.
14	V. Los, and D. Ocheretin “Construction of business confidence index based on a system of economic indicators”, ShS Web of Conferences, vol.65, 2019.
15	S. Arslankaya and V. Öz “Time Series Analysis on Sales Quantity in an Automotive Company and Estimation by Artificial Neural Networks”, Sakarya University Journal of Science,no. 22 (5), pp. 1482-1492, 2018.
16	Shi Dong, Yifan Sun, Nicolas Bohm Agostini. Spartan: A Sparsity-Adaptive Framework to Accelerate Deep Neural Network Training on GPUs. IEEE Transactions on Parallel and Distributed Systems, 2021.
17	Yangqin Feng, Lei Zhang, Juan Mo. Deep Manifold Preserving Autoencoder for Classifying Breast Cancer Histopathological ImaGES. IEEE Transactions on Computational Biology and Bioinformatics, 2020.
18	Mengru Du. Economic Forecast Model and Development Path Analysis Based on BP and RBF Neural Network. 2023 IEEE 12th International Conference on Communication Systems and Network Technologies (CSNT), 2023.
19	Elman J L. Finding structure in time. Cognitive Science, vol.14, pp.179–211, 1990.
20	Yun Kai, Huang Qiang, Ma Yixuan. Construction of Network Security Perception System Using Elman Neural Network. 2021 2nd International Conference on Computer Communication and Network Security (CCNS), 2021.
21	Zhilong Zhang, Xianjun Shi, Yufeng Long, Yufeng Qin, Jiapeng Lv, Li Zhao. Network Traffic Prediction Based on Improved GA-Elman Neural Network. 2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes, 2021.
22	Yufei Zhang, Jianping Zhao, Honggang Wu, Minghan Gao. A new IOIF Elman neural network for air quality prediction. 2022 2nd International Conference on Consumer Electronics and Computer Engineering (ICCECE), 2022.
23	Xinlei Cai, Jinzhou Zhu, Jiale Liu, Zijie Meng, Yuhang Huo, Yang Yu. Short- Term Power Prediction Method for Photovoltaic Power Generation Based on Elman Neural Network for Aspen Swarm Optimization. 2023 6th International Conference on Energy, Electrical and Power Engineering (CEEPE), 2023.
24	Xie Jialing, Shi Weifeng, Bi Zong, Song Tiewei. Research on Marine Electric Load Forecast Based on PSO-Elman Neural Network. 2021 4th International Conference on Energy, Electrical and Power Engineering (CEEPE), 2021.
25	Masoud Fetanat, Michael Stevens, Pankaj Jain, Christopher Hayward, Erik Meijering, Nigel H. Lovell. Fully Elman Neural Network: A Novel Deep Recurrent Neural Network Optimized by an Improved Harris Hawks Algorithm for Classification of Pulmonary Arterial Wedge Pressure. IEEE Transactions on Biomedical Engineering, 2022.
26	Rajesh Kumar. Memory Recurrent Elman Neural Network-Based Identification of Time-Delaed Nonlinear Dynamical System. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023.