A review and empirical analysis of neural networks based exchange rate prediction

[1]  N. Sriraam,et al.  Comparison of MLP and REN classifiers for detection of hemodynamic stress using photoplethysmograph , 2013 .

[2]  Wang Dongli,et al.  Radial basis function neural network-based model predictive control for freeway traffic systems , 2007, Int. J. Intell. Syst. Technol. Appl..

[3]  Mehdi Khashei,et al.  A novel hybridization of artificial neural networks and ARIMA models for time series forecasting , 2011, Appl. Soft Comput..

[4]  Kin Keung Lai,et al.  Foreign Exchange Rates Forecasting with Multilayer Perceptrons Neural Network by Bayesian Learning , 2008, 2008 Fourth International Conference on Natural Computation.

[5]  Luiz Koodi Hotta,et al.  Bootstrap prediction in univariate volatility models with leverage effect , 2016, Math. Comput. Simul..

[6]  Jun Wu,et al.  RBF-ARX model-based MPC strategies with application to a water tank system , 2015 .

[7]  Arash Kia.  Using MLP and RBF Neural Networks to Improve thePrediction of Exchange Rate Time Series with ARIMA , 2012 .

[8]  C. Engel,et al.  The Forward Discount Anomaly and the Risk Premium: A Survey of Recent Evidence , 1995 .

[9]  I.S. Isa,et al.  Suitable MLP Network Activation Functions for Breast Cancer and Thyroid Disease Detection , 2010, 2010 Second International Conference on Computational Intelligence, Modelling and Simulation.

[10]  Sung-Kwun Oh,et al.  A comparative study of feature extraction methods and their application to P-RBF NNs in face recognition problem , 2016, Fuzzy Sets Syst..

[11]  Eduard Kuriscak,et al.  Biological context of Hebb learning in artificial neural networks, a review , 2015, Neurocomputing.

[12]  Jih-Jeng Huang,et al.  Model identification of ARIMA family using genetic algorithms , 2005, Appl. Math. Comput..

[13]  Pradipta Kishore Dash,et al.  Comparative study of stock market forecasting using different functional link artificial neural networks , 2012, Int. J. Data Anal. Tech. Strateg..

[14]  Chunxia Zhang,et al.  Generalized extreme learning machine autoencoder and a new deep neural network , 2017, Neurocomputing.

[15]  Khashayar Khorasani,et al.  Constructive feedforward neural networks using Hermite polynomial activation functions , 2005, IEEE Transactions on Neural Networks.

[16]  Kin Keung Lai,et al.  Multistage RBF neural network ensemble learning for exchange rates forecasting , 2008, Neurocomputing.

[17]  Sammy Siu,et al.  Analysis of the Initial Values in Split-Complex Backpropagation Algorithm , 2008, IEEE Transactions on Neural Networks.

[18]  Yuichi Motai,et al.  Multicolumn RBF Network , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[19]  M. Scutari,et al.  Bayesian Network Structure Learning with Permutation Tests , 2011, 1101.5184.

[20]  Hamid Sheikhzadeh,et al.  Sparse Bayesian mixed-effects extreme learning machine, an approach for unobserved clustered heterogeneity , 2016, Neurocomputing.

[21]  Ganapati Panda,et al.  New robust forecasting models for exchange rates prediction , 2012, Expert Syst. Appl..

[22]  Héctor Pomares,et al.  Prediction of Time Series Using RBF Neural Networks: A New Approach of Clustering , 2009, Int. Arab J. Inf. Technol..

[23]  Ganapati Panda,et al.  A Particle-Swarm-Optimization-Based Decentralized Nonlinear Active Noise Control System , 2012, IEEE Transactions on Instrumentation and Measurement.

[24]  Yu Zhijun,et al.  RBF Neural Networks Optimization Algorithm and Application on Tax Forecasting , 2013 .

[25]  M. Sharifi,et al.  Using the Multistage RBF Neural Network in order to Predict the Deposits of Eghtesad Novin Bank and Comparing this Method with other Methods , 2014 .

[26]  L. Suganthi,et al.  Field Programmable Gate Array based floating point hardware design of recursive k-means clustering algorithm for Radial Basis Function Neural Network , 2009, Int. J. Intell. Syst. Technol. Appl..

[27]  Chi-Bin Cheng,et al.  Financial distress prediction by a radial basis function network with logit analysis learning , 2006, Comput. Math. Appl..

[28]  Satchidananda Dehuri,et al.  Optimized Radial Basis Functional neural network for stock index prediction , 2016, 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT).

[29]  B. Majhi,et al.  Efficient long range prediction of exchange rates using Radial Basis Function Neural Network models , 2012, IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012).

[30]  Robert I. Damper,et al.  Determining and improving the fault tolerance of multilayer perceptrons in a pattern-recognition application , 1993, IEEE Trans. Neural Networks.

[31]  Min Gan,et al.  A Variable Projection Approach for Efficient Estimation of RBF-ARX Model , 2015, IEEE Transactions on Cybernetics.

[32]  Torbjorn Thiringer,et al.  ARIMA-Based Frequency-Decomposed Modeling of Wind Speed Time Series , 2016, IEEE Transactions on Power Systems.

[33]  Jiashu Zhang,et al.  Pipelined Chebyshev Functional Link Artificial Recurrent Neural Network for Nonlinear Adaptive Filter , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[34]  Bengt Fornberg,et al.  On the role of polynomials in RBF-FD approximations: II. Numerical solution of elliptic PDEs , 2017, J. Comput. Phys..

[35]  Qinghua Guo,et al.  Low complexity sparse Bayesian learning using combined belief propagation and mean field with a stretched factor graph , 2016, Signal Process..

[36]  Sung-Bae Cho,et al.  An improved swarm optimized functional link artificial neural network (ISO-FLANN) for classification , 2012, J. Syst. Softw..

[37]  Hong Wang,et al.  Fault Diagnosis and Tolerant Control for Discrete Stochastic Distribution Collaborative Control Systems , 2015, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[38]  Tamer Inanc,et al.  An RBF collocation method for solving optimal control problems , 2017, Robotics Auton. Syst..

[39]  Terje Kristensen,et al.  A Multi-Layered Perceptron fingerprint idenfication system , 2011, 2011 Third World Congress on Nature and Biologically Inspired Computing.

[40]  Nicolau Santos,et al.  Performance of state space and ARIMA models for consumer retail sales forecasting , 2015 .

[41]  Xiaolong Wang,et al.  A novel text mining approach to financial time series forecasting , 2012, Neurocomputing.

[42]  Ganapati Panda,et al.  Efficient prediction of exchange rates with low complexity artificial neural network models , 2009, Expert Syst. Appl..

[43]  Eduardo Gomes Salgado,et al.  Forecasting number of ISO 14001 certifications in the Americas using ARIMA models , 2017 .

[44]  Haytham Elghazel,et al.  A hybrid algorithm for Bayesian network structure learning with application to multi-label learning , 2014, Expert Syst. Appl..

[45]  Lori A. Thombs,et al.  Bootstrap Prediction Intervals for Autoregression , 1990 .

[46]  Sung-Bae Cho,et al.  Design of self-adaptive and equilibrium differential evolution optimized radial basis function neural network classifier for imputed database , 2016, Pattern Recognit. Lett..

[47]  Svitlana Galeshchuk,et al.  Neural networks performance in exchange rate prediction , 2016, Neurocomputing.

[48]  Edwin Villanueva,et al.  Efficient methods for learning Bayesian network super-structures , 2014, Neurocomputing.

[49]  Anders L. Madsen,et al.  A parallel algorithm for Bayesian network structure learning from large data sets , 2017, Knowl. Based Syst..

[50]  Sandeep Singh Gill,et al.  Notice of Retraction Indian currency exchange rate forecasting using neural networks , 2010 .

[51]  Enrico Zio,et al.  Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[52]  David J. C. MacKay,et al.  Bayesian Interpolation , 1992, Neural Computation.

[53]  Long Zhang,et al.  A New Extension of Newton Algorithm for Nonlinear System Modelling Using RBF Neural Networks , 2013, IEEE Transactions on Automatic Control.

[54]  Michel Crucianu,et al.  Bayesian learning for recurrent neural networks , 2001, Neurocomputing.

[55]  Héctor Pomares,et al.  A new radial basis function networks structure: application to time series prediction , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

[56]  Hui Peng,et al.  A Regularized SNPOM for Stable Parameter Estimation of RBF-AR(X) Model , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[57]  Birgitte Bak-Jensen,et al.  ARIMA-Based Time Series Model of Stochastic Wind Power Generation , 2010, IEEE Transactions on Power Systems.

[58]  Babita Majhi,et al.  Stock Indices Prediction Using Radial Basis Function Neural Network , 2012, SEMCCO.

[59]  Satchidananda Dehuri,et al.  Machine learning-based classifiers ensemble for credit risk assessment , 2013 .

[60]  Himansu Sekhar Behera,et al.  A Global-best Harmony Search based Gradient Descent Learning FLANN (GbHS-GDL-FLANN) for data classification , 2016 .

[61]  Jingtao Yao,et al.  A case study on using neural networks to perform technical forecasting of forex , 2000, Neurocomputing.

[62]  Yu Gong,et al.  A Fast Adaptive Tunable RBF Network For Nonstationary Systems , 2016, IEEE Transactions on Cybernetics.

[63]  Yang Wang,et al.  Robust Bayesian non-parametric dictionary learning with heterogeneous Gaussian noise , 2016, Comput. Vis. Image Underst..

[64]  R. MacDonald.  Expectations Formation and Risk in Three Financial Markets: Surveying What the Surveys Say , 2000 .

[65]  Liao Xiangyang,et al.  A novel self-optimizing approach for knowledge acquisition , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[66]  Ratnadip Adhikari,et al.  Forecasting seasonal time series with Functional Link Artificial Neural Network , 2015, 2015 2nd International Conference on Signal Processing and Integrated Networks (SPIN).

[67]  Tugrul U. Daim,et al.  Using artificial neural network models in stock market index prediction , 2011, Expert Syst. Appl..

[68]  Jun Fang,et al.  Sparse Bayesian dictionary learning with a Gaussian hierarchical model , 2017, Signal Process..

[69]  Ignacio Rojas,et al.  A New Clustering Technique for Function Approximation , 2005 .

[70]  Iñaki Inza,et al.  Learning Bayesian network classifiers from label proportions , 2013, Pattern Recognit..

[71]  Chunshien Li,et al.  Complex Neurofuzzy ARIMA Forecasting—A New Approach Using Complex Fuzzy Sets , 2013, IEEE Transactions on Fuzzy Systems.

[72]  Rajkumar Buyya,et al.  Workload Prediction Using ARIMA Model and Its Impact on Cloud Applications’ QoS , 2015, IEEE Transactions on Cloud Computing.

[73]  Alex ChiChung Kot,et al.  Nonlinear dynamic system identification using Chebyshev functional link artificial neural networks , 2002, IEEE Trans. Syst. Man Cybern. Part B.

[74]  Konstantinos G. Margaritis,et al.  Topology and simulations of a Hierarchical Markovian Radial Basis Function Neural Network classifier , 2015, Inf. Sci..

[75]  Mostafa Zandieh,et al.  An integrated eigenvector-DEA-TOPSIS methodology for portfolio risk evaluation in the FOREX spot market , 2010, Expert Syst. Appl..

[76]  Kin Keung Lai,et al.  A Reliability-Based RBF Network Ensemble Model for Foreign Exchange Rates Predication , 2006, ICONIP.

[77]  Ajit Kumar Rout,et al.  Efficient Forecasting of Exchange rates with Recurrent FLANN , 2013 .

[78]  Bradley P. Carlin,et al.  Markov Chain Monte Carlo in Practice: A Roundtable Discussion , 1998 .

[79]  Lei Zhang,et al.  Performance Study of Multilayer Perceptrons in a Low-Cost Electronic Nose , 2014, IEEE Transactions on Instrumentation and Measurement.

[80]  Narasimhan Sundararajan,et al.  Communication channel equalization using complex-valued minimal radial basis function neural networks , 2002, IEEE Trans. Neural Networks.

[81]  Jouko Lampinen,et al.  Bayesian approach for neural networks--review and case studies , 2001, Neural Networks.

[82]  Qiangfu Zhao.  Stable online evolutionary learning of NN-MLP , 1997, IEEE Trans. Neural Networks.

[83]  Marie-Francine Moens,et al.  A survey on the application of recurrent neural networks to statistical language modeling , 2015, Comput. Speech Lang..

[84]  Roman Rosipal,et al.  Prediction of Chaotic Time-Series with a Resource-Allocating RBF Network , 1998, Neural Processing Letters.

[85]  Kavita Burse,et al.  Channel Equalization Using Neural Networks: A Review , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[86]  Ganapati Panda,et al.  Identification of nonlinear dynamic systems using functional link artificial neural networks , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[87]  J. Bilski.  The Backpropagation learning with logarithmic transfer function , 2000 .

[88]  Petr Suchánek,et al.  Self-learning Bayesian Networks in Diagnosis , 2014, KES.

[89]  Rati Wongsathan,et al.  A Hybrid ARIMA and Neural Networks Model for PM-10 Pollution Estimation: The Case of Chiang Mai City Moat Area , 2016 .

[90]  S. Dehuri,et al.  Software effort prediction using unsupervised learning (clustering) and functional link artificial neural networks , 2012, 2012 World Congress on Information and Communication Technologies.

[91]  Qun Dai,et al.  A two-phased and Ensemble scheme integrated Backpropagation algorithm , 2014, Appl. Soft Comput..

[92]  A. Bahadori,et al.  Prediction of carbon dioxide solubility in ionic liquids using MLP and radial basis function (RBF) neural networks , 2016 .

[93]  Juan David Velasquez,et al.  Methodological Advances in Artificial Neural Networks for Time Series Forecasting , 2014, IEEE Latin America Transactions.