In this paper a CAD (Computer Aided Diagnosis) system is proposed to optimize the feature set using hybrid of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) technique called Genetical Swarm Optimization (GSO) in Digital Mammogram. Even though PSO is a good optimization technique, it may be trapped in local minima and may prematurely converge. So, the genetic operators are used in ...

Wireless Sensor Networks (WSNs) consists of arbitrarily placed tiny sensors which monitor the target field. Every location of the target field is said to be with at least one sensor. The sensors must be deployed in such a way that every sensor is efficiently used to monitor the target field with less coverage loss. Glow worm Swarm Optimization (GSO) technique is swarm intelligence based techniq...

In this paper, two new cluster analysis methods based on glowworm swarm optimization (GSO) algorithm are proposed. The first algorithm showed how GSO can be used to self-organization cluster analysis. The second algorithm is hybrid the GSO clustering analysis with the K-means algorithm to accelerate classification. Two clustering algorithms are tested on three data sets; experimental results sh...

Software testing is an important activity that is carried out during the software development life cycle. Regression testing means re-executing test cases from existing test suites to assure that the modifications done to the existing software have no adverse effects. During regression testing, new test cases are not created but previously created test cases are reexecuted. The ideal regression...

In this paper we propose a new distributed double guided hybrid algorithm combining the particle swarm optimization (PSO) with genetic algorithms (GA) to resolve maximal constraint satisfaction problems (Max-CSPs). It consists on a multi-agent approach inspired by a centralized version of hybrid algorithm called Genetical Swarm Optimization (GSO). Our approach consists of a set of evolutionary ...

This paper presents multimodal function optimization, using a nature-inspired glowworm swarm optimization (GSO) algorithm, with applications to collective robotics. GSO is similar to ACO and PSO but with important differences. A key feature of the algorithm is the use of an adaptive local-decision domain, which is used effectively to detect the multiple optimum locations of the multimodal funct...

This paper utilizes the improved group search optimization algorithm for optimal reactive power dispatch (ORPD). The ORPD problem is a non-linear, non-convex optimization problem which has various decision variables such as compensation capacitor proportions, voltage of generators and the tap position of tap changing transformers. In this paper the multi-objective ORPD considering loss, voltage...

Artificial Neural Networks (ANNs) have been applied to machine condition monitoring. This paper first addresses a ANN trained by Group Search Optimizer (GSO), which is a novel Swarm Intelligent (SI) optimization algorithm inspired by animal social foraging behaviour. The global search performance of GSO has been proven to be competitive to other evolutionary algorithms, such as Genetic Algorith...

In this chapter we present the design and optimization of GPU implementations of two popular chemical similarity techniques: Gaussian shape overlay (GSO) and LINGO. GSO involves a data-parallel, arithmetically intensive iterative numerical optimization; we use it to examine issues of thread parallelism, arithmetic optimization, and CPU-GPU transfer overhead minimization. LINGO is a string simil...

Cryptanalysis with Computational Intelligence has gained much interest in recent years. This paper presents an approach for breaking the key used in Simplified-Data Encryption Standard (S-DES) using Genetic algorithm (GA), Particle Swarm Optimization (PSO) and a novel approach called Genetic Swarm Optimization (GSO) obtained by combining the effectiveness of GA and PSO. Ciphertext-only attack i...