The paper proposes an algorithm for data mining called Ant-Miner (ant-colony-based miner). goal of is to extract classification rules from data. inspired by both research on the behavior real ant colonies and some concepts as well principles. We compare performance with CN2, a well-known classification, in six public domain sets. results provide evidence that: 1) competitive CN2 respect predictive accuracy, 2) rule lists discovered are considerably simpler (smaller) than those CN2.

The growing complexity of real-world problems has motivated computer scientists to search for efficient problem-solving methods. Evolutionary computation and swarm intelligence meta-heuristics are outstanding examples that nature been an unending source inspiration. behaviour bees, bacteria, glow-worms, fireflies, slime moulds, cockroaches, mosquitoes other organisms have inspired researchers devise new optimisation algorithms. This tutorial highlights the most recent nature-based...

The search for nature-inspired ideas, models and computational paradigms always was of great interest computer scientists, particularly those from the Natural Computing area. concept optimization is present in several natural processes as evolution species, behavior social groups, dynamics immune system, food strategies ecological relationships different animal populations. This work uses concepts habitats, successions to build an ecology-inspired algorithm, named ECO. proposed approach...

It is estimated that 80% of crashes and 65% near collisions involved drivers inattentive to traffic for three seconds before the event. This paper develops an algorithm extracting characteristics allowing cell phones identification used during driving a vehicle. Experiments were performed on sets images with 100 positive (with phone) other negative (no phone), containing frontal driver. Support Vector Machine (SVM) Polynomial kernel most advantageous classification system features provided...

SUMMARY This paper compares the performance of three swarm intelligence algorithms for optimization hard engineering problems. The tested were bacterial foraging (BFO), particle (PSO), and artificial bee colony (ABC). Besides regular BFO, two other variants reported in literature also included study: adaptive BFO swarming BFO. Both PSO ABC using algorithm that include explosion (mass extinction). Three problems structural used: minimization cost a welded beam, construction pressure vessel,...

Abstract Cloud Computing popularization inspired the emergence of many new cloud service providers. The significant number providers available drives users to complex or even impractical choice most suitable one satisfy his needs without automation. Provider Selection (CPS) problem addresses that choice. Hence, this work presents a general approach for solving CPS using as selection criteria performance indicators compliant with Service Measurement Initiative Consortium - Index framework...

This work presents a new evolutionary algorithm based on the standard harmony search strategy, called population-based (PBHS). Also, this provides parallelisation method for proposed PBHS by using graphical processing units (GPU), allowing multiple function evaluations at same time. Experiments were done benchmark of hard scientific problem: protein structure prediction with AB-2D off-lattice model. The performance and solution quality evaluated compared four implementations: two concerning...