A Modified BPN Approach For Stock Market Prediction

被引：0

作者：

Mithani, Fesal ^{[1
]}

Machchhar, Sahista ^{[1
]}

Jasdanwala, Fernaz ^{[1
]}

机构：

[1] MEF Grp Inst, Fac PG Studies, Dept Comp Engn, Rajkot 360003, Gujarat, India

来源：

2016 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH | 2016年

关键词：

BPN (Back Propagation Neural) Network; Regression; ANN(Artificial Neural network); BN(Bayesian Network); SVM(Support vector machine); Accuracy;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Predicting stock market accurately has always fascinated the market analysts. During the previous few decades assorted machine learning techniques (Regression, RBFN, SOM, BN and SVM) have been applied to examine the highly debatable nature of stock market by capturing and using repetitive patterns. Our main aim is to accurately predict value for the future and maximum amount of profit for a holder by using Back Propagation Neural Network. Here we gives brief information about assorted techniques used for prediction, so that it is easy for user to choose the share to buy or sale and predict the value which has minimum error.

引用

页码：902 / 905

页数：4

共 50 条

[31] Hybrid Deep Generative and Sequential Learning Approach for Stock Market Prediction
Zhao, Tuo
Wang, Xinxue
Zhao, Tingting
Wang, Yuan
Chen, Yarui
Yang, Jucheng
ADVANCED INTELLIGENT COMPUTING TECHNOLOGY AND APPLICATIONS, PT V, ICIC 2024, 2024, 14879 : 263 - 274
[32] Prediction of the Stock Market From Linguistic Phrases: A Deep Neural Network Approach
Eachempati, Prajwal
Srivastava, Praveen Ranjan
JOURNAL OF DATABASE MANAGEMENT, 2023, 34 (01)
[33] Stock market prediction using subtractive clustering for a neuro fuzzy hybrid approach
Chandar, S. Kumar
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2019, 22 (Suppl 6): : 13159 - 13166
[34] An Intelligent Model for Stock Market Prediction
Hamed, Ibrahim M.
Hussein, Ashraf S.
Tolba, Mohamed F.
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2012, 5 (04) : 639 - 652
[35] Deep Learning for Stock Market Prediction
Nabipour, M.
Nayyeri, P.
Jabani, H.
Mosavi, A.
Salwana, E.
Shahab, S.
ENTROPY, 2020, 22 (08)
[36] An Efficient System for Stock Market Prediction
Hussein, Ashraf S.
Hamed, Ibrahim M.
Tolba, Mohamed F.
INTELLIGENT SYSTEMS'2014, VOL 2: TOOLS, ARCHITECTURES, SYSTEMS, APPLICATIONS, 2015, 323 : 871 - 882
[37] On Optimization of Stock Market Prediction Methods
Landis, Warren
Cha, Sangwhan
Shaalan, Majid
2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2019, : 6116 - 6118
[38] Stock market prediction using subtractive clustering for a neuro fuzzy hybrid approach
S. Kumar Chandar
Cluster Computing, 2019, 22 : 13159 - 13166
[39] Unveiling market dynamics: a machine and deep learning approach to Egyptian stock prediction
Fattoh, Ibrahim Eldesouky
Ibrahim, Marwa El Maghawry
Mousa, Farid Ali
FUTURE BUSINESS JOURNAL, 2025, 11 (01)
[40] Stock market prediction from news on the Web and a new evaluation approach in trading
Ichinose, Ko
Shimada, Kazutaka
PROCEEDINGS 2016 5TH IIAI INTERNATIONAL CONGRESS ON ADVANCED APPLIED INFORMATICS IIAI-AAI 2016, 2016, : 77 - 81

← 1 2 3 4 5 →