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An-Pin Chen
Researcher at National Chiao Tung University
Publications - 57
Citations - 600
An-Pin Chen is an academic researcher from National Chiao Tung University. The author has contributed to research in topics: Artificial neural network & Futures contract. The author has an hindex of 11, co-authored 56 publications receiving 536 citations.
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Journal ArticleDOI
Knowledge management performance evaluation: a decade review from 1995 to 2004
Mu Yen Chen,An-Pin Chen +1 more
TL;DR: The ability to continually change and obtain new understanding is the driving power behind KM methodologies, and should be the basis of KM performance evaluations in the future.
Proceedings ArticleDOI
Financial Time-Series Data Analysis Using Deep Convolutional Neural Networks
TL;DR: The proposed system is implemented and benchmarked in the historical datasets of Taiwan Stock Index Futures, and the experimental results show that the deep learning technique is effective in the trading simulation application, and may have greater potentialities to model the noisy financial data and complex social science problems.
Journal ArticleDOI
Integrating option model and knowledge management performance measures: an empirical study
Mu Yen Chen,An-Pin Chen +1 more
TL;DR: A new metric, knowledge management performance index (KMPI), is developed for evaluating the performance of a firm in its KM at a point in time, and the results prove the option pricing model can act as a measurement guideline to the whole range of KM activities.
Journal ArticleDOI
Integrating extended classifier system and knowledge extraction model for financial investment prediction: An empirical study
An-Pin Chen,Mu Yen Chen +1 more
TL;DR: The learning classifier systems (LCS) technique is adopted to provide a three-phase knowledge extraction methodology, which makes continues and instant learning while integrates multiple rule sets into a centralized knowledge base.
Journal ArticleDOI
Applying market profile theory to forecast Taiwan Index Futures market
TL;DR: The integration of market profile and technical analysis surpasses technical analysis as a neural network architecture parameter by effectively improving forecasting performance and profitability and experimental results show the qualitative market profile indicator outperforms the quantitative approach in a short-term forecast period.