This paper introduces two decoders for binary linear codes based on Metaheuristics. The first one uses a genetic algorithm and the second is based on a combination genetic algorithm with a feed forward neural network. The decoder based on the genetic algorithms (DAG) applied to BCH and convolutional codes give good performances compared to Chase-2 and Viterbi algorithm respectively and reach th...

Feature selection is an important task for data analysis and information retrieval processing, pattern classification systems, and data mining applications. It reduces the number of features by removing noisy, irrelevant and redundant data. In this paper, a novel feature selection algorithm based on Ant Colony Optimization (ACO), called Advanced Binary ACO (ABACO), is presented. Features are tr...

This study proposes a novel binary version of the artificial bee colony algorithm based on genetic operators (GB-ABC) such as crossover and swap to solve binary optimization problems. Integrated to the neighbourhood searching mechanism of the basic ABC algorithm, the modification comprises four stages: (1) In neighbourhood of a (current) food source, randomly select two food sources from popula...

The DMP1 (Dynamic Multi-layer Perceptron 1) network training method is based upon a divide and conquer approach which builds networks in the form of binary trees, dynamically allocating nodes and layers as needed. This paper introduces the DMP1 method, and compares the preformance of DMP1 when using the standard delta rule training method for training individual nodes against the performance of...

We report, for the first time, the concept and generation of a novel Fresnel hologram called the digital binary mask programmable hologram (BMPH). A BMPH is comprised of a static, high resolution binary grating that is overlaid with a lower resolution binary mask. The reconstructed image of the BMPH can be programmed to approximate a target image (including both intensity and depth information)...

In this paper, a exible yet eecient algorithm for solving engineering design optimization problems is presented. The algorithm is developed based on both binary-coded and real-coded genetic algorithms (GAs). Since both GAs are used, the variables involving discrete, continuous, and zero-one variables are handled quite eeciently. The algorithm restricts its search only to the permissible values ...

in recent years, significant research efforts have been devoted to the optimal planning of power systems. substation expansion planning (sep) as a sub-system of power system planning consists of finding the most economical solution with the optimal location and size of future substations and/or feeders to meet the future demand. the large number of design variables, and combination of discrete ...

This paper discusses the optimal node placement problem of Industrial Wireless Sensor Networks (IWSNs). Compared with the non-industrial Wireless Sensor Networks (WSNs), IWSNs have a critical requirement on the reliability of networks. Thus, a new model of the IWSNs node placement is formulated in which the reliability, cost, load constraint and scalability are taken into account. Considering i...