the purpose of this research is to detect manipulation of stock prices in tehran stock exchange that it has been done through hybrid genetic algorithm-artificial neural network (ann-ga) model and the simplified quadratic discriminant function (sqdf) model. in this study, the variables of price, trading volume and free float stock to match the results of the model and the actual data of price ma...

Different data classification algorithms have been developed and applied in various areas to analyze and extract valuable information and patterns from large datasets with noise and missing values. However, none of them could consistently perform well over all datasets. To this end, ensemble methods have been suggested as the promising measures. This paper proposes a novel hybrid algorithm, whi...

This paper proposes an approach to construct a better Semantic Perceptron Net (SPN) used for topic spotting. To accomplish this task a learning paradigm call: neural network ensembling is used. Applying this technique to the original structure of Semantic Perceptron Net a new system called GA-SPN (Genetic Algorithm based Semantic Perceptron Net) was developed. The new system uses a neural netwo...

A teaching-learning-based optimization (TLBO) algorithm is a new population-based algorithm applied in some applications in the literature successfully. Moreover, a genetic algorithm (GA) is a popular tool employed widely in many disciplines of engineering. In this paper, a hybrid GA-TLBO algorithm is proposed for the capacitated three-stage supply chain network design (SCND) problem. The SCND ...

A hybrid particle swarm optimization (PSO) for multi-machine time scheduling problem (MTSP) with multicycles is proposed in this paper to choose the best starting time for each machine in each cycle under pre-described time window and a set of precedence machines for each machine; to minimize the total penalty cost. We developed hybrid algorithm by using a combination between PSO and Genetic Al...