The main objective of this research is to automatically design Artificial Neural Network models with sigmoid basis units for multiclassification tasks in predictive microbiology. The classifiers obtained achieve a double objective: a high classification level in the dataset and high classification levels for each class. The Memetic Pareto Differential Evolution Neural Network chosen to learn th...

Due to the resource constraint and dynamic parameters, reducing energy consumption became the most important issues of wireless sensor networks topology design. All proposed hierarchy methods cluster a WSN in different cluster layers in one step of evolutionary algorithm usage with complicated parameters which may lead to reducing efficiency and performance. In fact, in WSNs topology, increasin...

Artificial neural networks provide a methodology for solving many types of nonlinear problems that are difficult to solve using traditional techniques. Neurogenetic hybrid systems bring together the artificial neural networks benefits and the inherent advantages of evolutionary algorithms. A functional approximation method using neuro-genetic hybrid systems is proposed in this paper. Three evol...

This paper presents a new multi-objective evolutionary algorithm based on differential evolution. The proposed approach adopts a secondary population in order to retain the non-dominated solutions found during the evolutionary process. Additionally, the approach also incorporates the concept of ε-dominance to get a good distribution of the solutions retained. The main goal of this work was to k...

The integration of Swarm Intelligence (SI) algorithms and Evolutionary algorithms (EAs) might be one of the future approaches in the Evolutionary Computation (EC). This work narrates the early research on using Stochastic Diffusion Search (SDS) – a swarm intelligence algorithm – to empower the Differential Evolution (DE) – an evolutionary algorithm – over a set of optimisation problems. The res...

In textile industry, marker planning is one of the main operations in the cutting fabric stage. Marker packing is usually used to maximize cloth exploitation and minimize its waste. In this research, a method is used based on new found meta-heuristic imperialist competitive algorithm (ICA) and Bottom-Left-Fill Algorithm (BLF) to achieve optimal marker packing. Function of the proposed method wa...

Hongyuan Gao*,Shibo Zhang,Ming Diao, and Yanan Du College of Information and Communication Engineering Harbin Engineering University Harbin, P. R. China [email protected], [email protected], diaoming@ hrbeu.edu.cn,[email protected] Abstract—It is a classical integer optimization difficulty to design optimal selection scheme in cooperative relay networks considering co-channel interfer...

optimizing the database queries is one of hard research problems. exhaustive search techniques like dynamic programming is suitable for queries with a few relations, but by increasing the number of relations in query, much use of memory and processing is needed, and the use of these methods is not suitable, so we have to use random and evolutionary methods. the use of evolutionary methods, beca...

This paper describes the so-called Differential Ant-Stigmergy Algorithm (DASA), which is an extension of the Ant-Colony Optimization for continuous domain. A performance study of the DASA on a benchmark of real-parameter optimization problems is presented. The DASA is compared with a number of evolutionary optimization algorithms including covariance matrix adaptation evolutionary strategy, dif...