| 2009 |
|---|
| 22 | EE | Bao Rong Chang,
Hsiu Fen Tsai:
Novel hybrid approach to data-packet-flow prediction for improving network traffic analysis.
Appl. Soft Comput. 9(3): 1177-1183 (2009) |
| 21 | EE | Bao Rong Chang,
Hsiu Fen Tsai:
Quantum-minimized BWGC/NGARCH approach to financial time series forecast.
Neurocomputing 72(10-12): 2525-2535 (2009) |
| 2008 |
|---|
| 20 | EE | Bao Rong Chang,
Hsiu Fen Tsai:
Forecast approach using neural network adaptation to support vector regression grey model and generalized auto-regressive conditional heteroscedasticity.
Expert Syst. Appl. 34(2): 925-934 (2008) |
| 19 | EE | Bao Rong Chang,
Hsiu Fen Tsai,
Chung-Ping Young:
Diversity of quantum optimizations for training adaptive support vector regression and its prediction applications.
Expert Syst. Appl. 34(4): 2612-2621 (2008) |
| 18 | EE | Hsiu Fen Tsai,
Bao Rong Chang:
Timing of resources exploration in the behavior of firm - Innovative approach and empirical simulation.
Expert Syst. Appl. 34(4): 2656-2663 (2008) |
| 17 | EE | Bao Rong Chang:
Resolving the forecasting problems of overshoot and volatility clustering using ANFIS coupling nonlinear heteroscedasticity with quantum tuning.
Fuzzy Sets and Systems 159(23): 3183-3200 (2008) |
| 2007 |
|---|
| 16 | EE | Bao Rong Chang,
Hsiu Fen Tsai:
Forecasting Approach Using Hybrid Model ASVR/NGARCH with Quantum Minimization.
ICIC (2) 2007: 1265-1277 |
| 15 | EE | Bao Rong Chang,
Hsiu Fen Tsai:
Performance Evaluation of Three Kinds of Quantum Optimization.
ISICA 2007: 224-233 |
| 14 | EE | Bao Rong Chang,
Hsiu Fen Tsai:
Neuromorphic Quantum-Based Adaptive Support Vector Regression for Tuning BWGC/NGARCH Forecast Model.
ISNN (3) 2007: 357-367 |
| 13 | EE | Bao Rong Chang,
Hsiu Fen Tsai:
Composite of adaptive support vector regression and nonlinear conditional heteroscedasticity tuned by quantum minimization for forecasts.
Appl. Intell. 27(3): 277-289 (2007) |
| 12 | EE | Bao Rong Chang:
A Hybrid System ASVR/NGARCH Tuned by Quantum-Based Minimization to Improve Forecasting Accuracy.
JACIII 11(4): 381-388 (2007) |
| 2006 |
|---|
| 11 | EE | Bao Rong Chang:
Novel Prediction Approach - Quantum-Minimum Adaptation to ANFIS Outputs and Nonlinear Generalized Autoregressive Conditional Heteroscedasticity.
FSKD 2006: 908-918 |
| 10 | EE | Bao Rong Chang,
Hsiu Fen Tsai,
Shi-Huang Chen,
Yu-Chang Chen,
Yu-Kuo Tseng:
Regularizing BWGC/NGARCH Model by Quantum Minimization.
ICICIC (2) 2006: 250-253 |
| 9 | EE | Yu-Kuo Tseng,
You-Yi Lu,
Jen-Yi Huang,
Wen-Shyong Hsieh,
Bao Rong Chang,
Yu-Chang Chen,
Shi-Huang Chen:
ID-Based PPM for IP Traceback.
ICICIC (2) 2006: 262-265 |
| 8 | EE | Bao Rong Chang,
Shi-Huang Chen,
Hsiu Fen Tsai:
Forecasting the Flow of Data Packets for Website Traffic Analysis - ASVR-Tuned ANFIS/NGARCH Approach.
ICONIP (2) 2006: 925-933 |
| 7 | EE | Hsiu Fen Tsai,
Bao Rong Chang:
Intelligence-Based Model to Timing Problem of Resources Exploration in the Behavior of Firm.
ICONIP (3) 2006: 478-487 |
| 6 | EE | Bao Rong Chang,
Hsiu Fen Tsai:
Financial Prediction Applications Using Quantum-Minimized Composite Model ASVR/NGARCH.
IJCNN 2006: 1247-1253 |
| 5 | EE | Bao Rong Chang,
Hsiu Fen Tsai:
New Approach to Financial Time Series Forecasting - Quantum Minimization Regularizing BWGC and NGARCH Composite Model.
JCIS 2006 |
| 4 | EE | Bao Rong Chang:
Applying nonlinear generalized autoregressive conditional heteroscedasticity to compensate ANFIS outputs tuned by adaptive support vector regression.
Fuzzy Sets and Systems 157(13): 1832-1850 (2006) |
| 2005 |
|---|
| 3 | EE | Bao Rong Chang:
Forecasting the Flow of Data Packets in Web Using ANFISCH Predictor Tuned by Segmented Adaptive Support Vector Regression.
CIT 2005: 23-27 |
| 2 | EE | Bao Rong Chang:
Hybrid BPNN-Weighted Grey-CLSP Forecasting.
J. Inf. Sci. Eng. 21(1): 209-221 (2005) |
| 2004 |
|---|
| 1 | EE | Bao Rong Chang:
Tunable free parameters C and epsilon-tube in support vector regression for grey prediction model - SVRGM(1, 1|C, e) approach.
SMC (3) 2004: 2431-2437 |
