Hossein Javedani Sadaei

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After reviewing the vast body of literature on using FTS in stock market forecasting, certain deficiencies are distinguished in the hybridization of findings. In addition, the lack of constructive systematic framework, which can be helpful to indicate direction of growth in entire FTS forecasting systems, is outstanding. In this study, we propose a(More)
a r t i c l e i n f o a b s t r a c t Keywords: Fuzzy time series Exponential fuzzy time series Stock forecasting Learning automata particle swarm optimization The initial aim of this study is to propose a hybrid method based on exponential fuzzy time series and learning automata based optimization for stock market forecasting. For doing so, a two-phase(More)
The Multi-Depot Vehicle Routing Problem (MDVRP) is an important variant of the classical Vehicle Routing Problem (VRP), where the customers can be served from a number of depots. This paper introduces a cooperative coevolutionary algorithm to minimize the total route cost of the MDVRP. Coevolutionary algorithms are inspired by the simultaneous evolution(More)
— In recent years, the demand for developing low computational cost methods to deal with uncertainty in forecasting has been increased. Interval forecasting is a category of forecasting in which the method provides intervals as outputs of its forecasting. The initial aim of this paper is therefore proposing a new interval forecasting method based on a low(More)
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