recently fuzzy intelligent method was used to dynamically model Japanese candlesticks in order to accurately consider the patterns of a candlestick with uncertain information on such patterns. Since fuzzy logic is expert knowledge, although human specialists can play an More
recently fuzzy intelligent method was used to dynamically model Japanese candlesticks in order to accurately consider the patterns of a candlestick with uncertain information on such patterns. Since fuzzy logic is expert knowledge, although human specialists can play an important role in regulating the values of membership functions of fuzzy variables but since human knowledge is usually ambiguous, a optimal adjustment is not achieved. Therefore, providing a technique that optimally adjusts the values of membership functions in dynamic candlesticks patterns will play a crucial role in the efficiency of the fuzzy trading system. One of the most commonly used optimization methods is the meta-heuristic methods, most of the meta-heuristics have a structure similar to the particle swarm optimization method. meta-heuristic methods such as fireflies and ant colony are more powerful than particle swarm optimization due to their efficient exploitation capabilities. In this paper, fireflies and ant colony are used to adjust and optimize the membership functions of fuzzy membership function of fuzzy candlesticks variables in order to trading analysis and stock price forecasting in the stock trading system. The results of applying the proposed method to iranian stock companies indicate the high accuracy of the proposed method.
Manuscript profile
