On the computational power of DNA
Discrete Applied Mathematics - Special volume on computational molecular biology
Using DNA to solve the bounded Post correspondence problem
Theoretical Computer Science - Special issue on universal machines and computations
Fuzzy ARIMA model for forecasting the foreign exchange market
Fuzzy Sets and Systems
Computing with Bio-Molecules: Theory and Experiments
Computing with Bio-Molecules: Theory and Experiments
A fuzzy seasonal ARIMA model for forecasting
Fuzzy Sets and Systems - Information processing
Experimental Construction of Very Large Scale DNA Databases with Associative Search Capability
DNA 7 Revised Papers from the 7th International Workshop on DNA-Based Computers: DNA Computing
DNA Computing: New Computing Paradigms (Texts in Theoretical Computer Science. An EATCS Series)
DNA Computing: New Computing Paradigms (Texts in Theoretical Computer Science. An EATCS Series)
Mining time series data by a fuzzy linguistic summary system
Fuzzy Sets and Systems
Temperature prediction using fuzzy time series
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
DNA computing approach to management engineering
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
Similarity-based fuzzy reasoning by DNA computing
International Journal of Bio-Inspired Computation
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There are many forecasting techniques including: exponential smoothing, ARIMA model, GARCH model, neural networks and genetic algorithm, etc. Since financial time series may be influenced by many factors, conventional model based techniques and hard computing methods seem inadequate in the prediction. Those methods, however, have their drawbacks and advantages. In recent years, the innovation and improvement of forecasting techniques have caught more attention, and also provides indispensable information in decision-making process. In this paper, a new forecasting technique, named DNA forecasting, is developed. This may be of use to a nonlinear time series forecasting. The methods combined the mathematical, computational, and biological sciences. In the empirical study, we demonstrated a novel approach to forecast the exchange rates through DNA. The mean absolute forecasting accuracy method is defined and used in evaluating the performance of linguistic forecasting. The comparison with ARIMA model is also illustrated.