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To promote the forecasting performance of Fuzzy time-series models, based on complex network, a novel fuzzy time series model for stock price forecasting was pressented, this pressented model includes the concept of the complex network and weighted adaptive expectation method. By comparing the fuzzy time series model of based on complex network and weighted adaptive expectation fuzzy time series model,...
Fuzzy time series has been utilized to solve the problem of time series prediction in diverse fields. In the fuzzy time series prediction, the fuzzy logical relations have great impacts on the prediction performance. To obtain the exact and complex fuzzy logical relations between the fuzzy variables for the time series prediction, we propose to extract them from the historical data and model them...
Fuzzy Time series (FTS) has been widely applied to handle non-linear problems, such as enrollment estimation, weather prediction and stock index forecasting. FTS predicted values on the basis of an equal interval, which is determined the early stages of forecasting in the model. In this paper, we employed Genetic Algorithms (GA) to optimize the interval at first. Based on this, then Rough Set (RS)...
High-order fuzzy time series is a popular method to forecasting, but it has lacked convenient tools for researchers to simulate their design models. This paper is presented a new technique to develop the simulation tools on Simulink using customs s-function. This technique can separate to three modules that are fuzzifier module, forecasting module and defuzzifier module to increase the flexibility...
This paper aims to implement fuzzy time series as a forecasting method in Jakarta Stock Exchange (JKSE) composite index using percentage change as the universe of discourse. Since Chen and Hsu introduced a new method to forecast enrollments in the University of Alabama, a number of methods have been proposed for forecasting the same subject, such as Jilani, Burney, and Ardil, and Stevenson and Porter...
The Asian steel price index is a leading indicator of the Asian economy. Studying the collection of Asian steel price index data and establishing a fuzzy time series model used to analyze the relationship between the remuneration of the Asian steel price index rate of change in the future. The results of the analysis are as follows. (1) The model showed that the predictive value of the 2012 Asian...
In this paper, we present a new method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) using fuzzy time series and automatically generated weights of multiple factors. The proposed method uses the variation magnitudes of adjacent historical data to generate fuzzy variation groups of the main factor (i.e., the TAIEX) and the elementary secondary factors (i.e., the...
Taiwan Futures Exchange (TAIFEX) is the world's 23rd futures exchange to trade SSFs, which is also the 21st financial product offered by the exchange. In this paper, the TAIFEX is predicted based on improving fuzzy time series model. Nature-ratio lengths of intervals technique is employed to partition the universal of discourse of linguistic variable and an improving high-order heuristic function...
This article firstly presents an analysis and survey regarding the traditional evaluation and forecasting model on fuzzy time series. lt is pointed out that the maximum Subordination degree method and Subordination degree-Weighted average method is not suitable to attribute space usually, and a new evaluation model is proposed. The empirical study show that the new evaluation model is better able...
This paper is aimed at improving the forecasting accuracy with correcting two deficiencies, subintervals failing to well represent the data distribution structures and a single antecedent factor in the fuzzy relationships in current fuzzy time series models. First, the universe of discourse is partitioned into subintervals with the midpoints of two adjacent cluster centers generated by the fuzzy clustering...
In this paper, we present a new method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) based on fuzzy time series, where the main factor is the TAIEX and the secondary factors are either the Dow Jones, the NASDAQ, the M1b (Taiwan), or their combinations. First, we fuzzify the historical data of the main factor into fuzzy sets with a fixed length of intervals to form...
In this paper, we present a new method to forecast the Taiwan stock exchange capitalization weighted stock index (TAIEX) based on high-order fuzzy logical relationships. First, the proposed method fuzzifies the historical data into fuzzy sets to form high-order fuzzy logical relationships. Then, it calculates the value of the variable between the subscripts of adjacent fuzzy sets appearing in the...
In this paper, Taiwan stock index is forecasted by use of optimized type 2 fuzzy time series concept. In type 2 fuzzy time series, more observation can be used for forecasting. Thus, this model is closer to reality than type1 model.
Network threat frequency forecasting is the important factor for dynamic quantitative risk assessment, which can timely offer network security administrators the corresponding effective security strategy to actively counteract the network threat. This paper first reviews current time series forecasting methods, and then presents a network threat frequency forecasting algorithm based on fuzzy time...
Fuzzy time series models has been applied to forecast various problems and have been shown to forecast better than other models. In this article, we intend to apply Chou and Lee's fuzzy time series model to forecast the Baltic Dry Index (BDI) index for the next month. The root mean square error is one criteria to evaluate the forecasting performance. Empirical results show that the fuzzy time series...
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