this research studies the application of hybrid algorithms for predicting the prices of crude oil. brent crude oil price data and hybrid intelligent algorithm (time delay neural network, probabilistic neural network, and fuzzy logic) were used to build intelligent decision support systems for predicting crude oil prices. the proposed model was able to predict future crude oil prices from august...

in this paper, we consider portfolio selection problem in which security returns are regarded as fuzzy variables rather than random variables. we first introduce a concept of absolute deviation for fuzzy variables and prove some useful properties, which imply that absolute deviation may be used to measure risk well. then we propose two mean-absolute deviation models by defining risk as abs...

This article introduces two swarm intelligent algorithms, a group search optimizer (GSO) and an artificial fish swarm algorithm (AFSA). A single intelligent algorithm always has both merits in its specific formulation and deficiencies due to its inherent limitations. Therefore, we propose a mixture of these algorithms to create a new hybrid optimization algorithm known as the group search-artif...

This paper aims at proposing a quadratic assignment-based mathematical model to deal with the stochastic dynamic facility layout problem. In this problem, product demands are assumed to be dependent normally distributed random variables with known probability density function and covariance that change from period to period at random. To solve the proposed model, a novel hybrid intelligent algo...

guiding vehicles to their destination under dynamic traffic conditions is an important topic in the field of intelligent transportation systems (its). nowadays, many complex systems can be controlled by using multi agent systems. adaptation with the current condition is an important feature of the agents. in this research, formulation of dynamic guidance for vehicles has been investigated based...

Prediction of heart disease is very important because it is one of the causes of death around the world. Moreover, heart disease prediction in the early stage plays a main role in the treatment and recovery disease and reduces costs of diagnosis disease and side effects it. Machine learning algorithms are able to identify an effective pattern for diagnosis and treatment of the disease and ident...

in this study, a hybrid intelligent model has been designed to predict groundwater inflow to a mine pit during its advance. novel hybrid method coupling artificial neural network (ann) with genetic algorithm (ga) called ann-ga, was utilised. ratios of pit depth to aquifer thickness, pit bottom radius to its top radius, inverse of pit advance time and the hydraulic head (hh) in the observation w...