Genetic Algorithms are very powerful search methods that are used in different optimization problems. Parallel versions of genetic algorithms are easily implemented and usually in...
This work presents a new approach to solve the location management problem by using the location areas approach. A combination of a genetic algorithm and the Hopfield neural netwo...
In this paper, we present two novel memetic algorithms (MAs) for gene selection. Both are synergies of Genetic Algorithm (wrapper methods) and local search methods (filter methods...
We present an Immune Inspired Algorithm, based on CLONALG, for software test data evolution. Generated tests are evaluated using the mutation testing adequacy criteria, and used to...
Many of today’s embedded systems, such as wireless and portable devices rely heavily on the limited power supply. Therefore, energy efficiency becomes one of the major design con...
Computation in biology and in conventional computer architectures seem to share some features, yet many of their important characteristics are very different. To address this, [1]...
Erwan Le Martelot, Peter J. Bentley, R. Beau Lotto
In this paper, a model based on genetic algorithms for protein folding prediction is proposed. The most important features of the proposed approach are: i) Heuristic secondary str...
Sergio Raul Duarte Torres, David Camilo Becerra Ro...
A novel optimisation accelerator deploying neural network predictions and objective space direct manipulation strategies is presented. The concept of directing the search through ...
Some auxiliary systems of next generation naval ships will utilize distributed automatic control. Such distributed control systems will use interconnected sensors, actuators, cont...
Christopher McCubbin, David Scheidt, Oliver Bandte...
This work presents a novel approach to filter synthesis on a field programmable analog array (FPAA) architecture using a genetic algorithm (GA). First, a Matlab model of the FPA...
Joachim Becker, Stanis Trendelenburg, Fabian Henri...