In this article, a new combined approach of a decision tree and clustering is presented to predict the transmission of genetic diseases. In this article, the performance of these algorithms is compared for more accurate prediction of disease transmission under the same condition and based on a series of measures like the positive predictive value, negative predictive value, accuracy, sensitivit...

Particle filters are an important class of online posterior density estimation algorithms. In this paper we propose a real coded genetic algorithm particle filter (RGAPF) for the dual estimation of stochastic volatility and parameters of a Heston type stochastic volatility model. We compare the performance of our hybrid particle filter with a parameter learning particle filter present in litera...

A novel cooperative evolutionary system, i.e., CGPNN, for automatic design artificial neural networks (ANN’s) is presented where ANN’s structure and parameters are tuned simultaneously. The algorithms used in CGPNN combine genetic algorithm (GA) and particle swarm optimization (PSO) on the basis of a direct encoding scheme. In CGPNN, standard (real-coded) PSO is employed to training ANN’s free ...

We present a new approach to perform molecular simulations using evolutionary algorithms. The main application of this work is the simulation of dense amorphous polymers and the goal is to improve the efficiency of sampling, in other words to obtain valid samples from the phase state more rapidly. Our approach is based on parallel Markovian Monte Carlo simulations of the same physico-chemical s...

abstract. in recent years several studies have shown that  control charts with adaptive schemes or double sampling plans detect both small and moderate shifts in the process mean more quickly than the traditional shewhart  chart. in the classical double sampling  chart, the difference between two points were placed in the central region of first stage was not considered. in this study, a new co...

In this paper, an optimization methodology is used to select the locations and characteristics of test, diagnosis and rework operations in electronic systems assembly processes. Real-coded genetic algorithms are used to perform a multi-variable optimization that minimizes the yielded cost of products resulting from an assembly process that includes test/diagnosis/rework operations characterized...

Hybrid algorithms formed by the combination of Genetic Algorithms with Local Search methods provide increased performances when compared to real coded GA or Local Search alone. However, the cost of Local Search can be rather high. In this paper we present a new hybrid algorithm which reduces the total cost of local search by avoiding the start of the method in basins of attraction where a local...