Stock Price Time Series Prediction using Neuro-Fuzzy with Support Vector Guideline System

2008 Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing ◽

10.1109/snpd.2008.55 ◽

2008 ◽

Author(s):

Phayung Meesad ◽

Tong Srikhacha

Keyword(s):

Time Series ◽

Stock Price ◽

Time Series Prediction ◽

Support Vector ◽

Neuro Fuzzy ◽

Guideline System

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Developing a Local Least-Squares Support Vector Machines-Based Neuro-Fuzzy Model for Nonlinear and Chaotic Time Series Prediction

IEEE Transactions on Neural Networks and Learning Systems ◽

10.1109/tnnls.2012.2227148 ◽

2013 ◽

Vol 24 (2) ◽

pp. 207-218 ◽

Author(s):

A. Miranian ◽

M. Abdollahzade

Keyword(s):

Time Series ◽

Support Vector Machines ◽

Least Squares ◽

Time Series Prediction ◽

Fuzzy Model ◽

Chaotic Time Series ◽

Support Vector ◽

Neuro Fuzzy ◽

Vector Machines ◽

Chaotic Time Series Prediction

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Empirical mode decomposition based denoising method with support vector regression for time series prediction: A case study for electricity load forecasting

Measurement ◽

10.1016/j.measurement.2017.02.007 ◽

2017 ◽

Vol 103 ◽

pp. 52-61 ◽

Author(s):

Yusuf Yaslan ◽

Bahadır Bican

Keyword(s):

Time Series ◽

Support Vector Regression ◽

Time Series Prediction ◽

Load Forecasting ◽

Support Vector ◽

Denoising Method ◽

Mode Decomposition ◽

Electricity Load ◽

Electricity Load Forecasting

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A Hybrid Neuro-Fuzzy Model for Stock Market Time-Series Prediction

2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP) ◽

10.1109/dsmp.2018.8478494 ◽

2018 ◽

Author(s):

Alexander Vlasenko ◽

Olena Vynokurova ◽

Nataliia Vlasenko ◽

Marta Peleshko

Keyword(s):

Time Series ◽

Stock Market ◽

Time Series Prediction ◽

Fuzzy Model ◽

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Chaotic time series prediction based on multi-kernel learning support vector regression

Acta Physica Sinica ◽

10.7498/aps.57.2708 ◽

2008 ◽

Vol 57 (5) ◽

pp. 2708

Author(s):

Zhang Jun-Feng ◽

Hu Shou-Song

Keyword(s):

Time Series ◽

Support Vector Regression ◽

Time Series Prediction ◽

Chaotic Time Series ◽

Kernel Learning ◽

Support Vector ◽

Learning Support ◽

Chaotic Time Series Prediction

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Classify Unexpected News Impacts to Stock Price by Incorporating Time Series Analysis into Support Vector Machine

The 2006 IEEE International Joint Conference on Neural Network Proceedings ◽

10.1109/ijcnn.2006.1716505 ◽

2006 ◽

Author(s):

Ting Yu ◽

T. Jan ◽

J. Debenham ◽

S. Simoff

Keyword(s):

Time Series ◽

Support Vector Machine ◽

Time Series Analysis ◽

Stock Price ◽

Support Vector ◽

Series Analysis

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Chaotic time series prediction using knowledge based Green’s Kernel and least-squares support vector machines

2007 IEEE International Conference on Systems, Man and Cybernetics ◽

10.1109/icsmc.2007.4414023 ◽

2007 ◽

Author(s):

Tahir Farooq ◽

Aziz Guergachi ◽

Sridhar Krishnan

Keyword(s):

Time Series ◽

Support Vector Machines ◽

Least Squares ◽

Time Series Prediction ◽

Chaotic Time Series ◽

Support Vector ◽

Knowledge Based ◽

Vector Machines ◽

Chaotic Time Series Prediction

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Grey relational grade in local support vector regression for financial time series prediction

Expert Systems with Applications ◽

10.1016/j.eswa.2011.07.100 ◽

2012 ◽

Vol 39 (3) ◽

pp. 2256-2262 ◽

Author(s):

Hui Jiang ◽

Wenwu He

Keyword(s):

Time Series ◽

Support Vector Regression ◽

Financial Time Series ◽

Time Series Prediction ◽

Support Vector ◽

Financial Time ◽

Local Support ◽

Grey Relational Grade ◽

Grey Relational

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Fast evolving neuro-fuzzy model and its application in online classification and time series prediction

Pattern Analysis and Applications ◽

10.1007/s10044-011-0203-4 ◽

2011 ◽

Vol 15 (3) ◽

pp. 279-288 ◽

Author(s):

Hossein Soleimani-B. ◽

Caro Lucas ◽

Babak N. Araabi

Keyword(s):

Time Series ◽

Time Series Prediction ◽

Fuzzy Model ◽

Online Classification ◽

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ANNEALED CHAOTIC LEARNING FOR TIME SERIES PREDICTION IN IMPROVED NEURO-FUZZY NETWORK WITH FEEDBACKS

International Journal of Computational Intelligence and Applications ◽

10.1142/s1469026809002680 ◽

2009 ◽

Vol 08 (04) ◽

pp. 429-444 ◽

Author(s):

CATHERINE VAIRAPPAN ◽

SHANGCE GAO ◽

ZHENG TANG ◽

HIROKI TAMURA

Keyword(s):

Time Series ◽

Fuzzy System ◽

Chaotic Dynamics ◽

Time Series Prediction ◽

Data Series ◽

Temporal Data ◽

Optimal Solutions ◽

Benchmark Data ◽

Neuro Fuzzy ◽

A new version of neuro-fuzzy system of feedbacks with chaotic dynamics is proposed in this work. Unlike the conventional neuro-fuzzy, improved neuro-fuzzy system with feedbacks is better able to handle temporal data series. By introducing chaotic dynamics into the feedback neuro-fuzzy system, the system has richer and more flexible dynamics to search for near-optimal solutions. In the experimental results, performance and effectiveness of the presented approach are evaluated by using benchmark data series. Comparison with other existing methods shows the proposed method for the neuro-fuzzy feedback is able to predict the time series accurately.

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Application of least square support vector machine based on particle swarm optimization to chaotic time series prediction

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems ◽

10.1109/icicisys.2009.5357656 ◽

2009 ◽

Author(s):

Ping Liu ◽

Jian Yao

Keyword(s):

Time Series ◽

Support Vector Machine ◽

Particle Swarm Optimization ◽

Time Series Prediction ◽

Particle Swarm ◽

Chaotic Time Series ◽

Least Square ◽

Support Vector ◽

Swarm Optimization ◽

Chaotic Time Series Prediction

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