Chromatin immunoprecipitation (ChIP) followed by high throughput sequencing (ChIP-seq) is rapidly becoming the method of choice for discovering cell-specific transcription factor binding locations genome wide. By aligning sequenced tags to the genome, binding locations appear as peaks in the tag profile. Several programs have been designed to identify such peaks, but program evaluation has been...

Population clustering methods, which consider the position and fitness of individuals to form sub-populations in multi-population algorithms, have shown high efficiency tracking moving global optimum dynamic optimization problems. However, most these methods use a fixed population size, making them inflexible inefficient when number promising regions is unknown. The lack functional relationship...

In this chapter we present a technique that helps Particle Swarm Optimisers (PSOs) locate an optimum more quickly, through fitness approximation using regression. A least-squares regression is used to estimate the shape of the local fitness landscape. From this shape, the expected location of the peak is calculated and the information given to the PSO. By guiding the PSO to the optimum, the loc...

An infrastructure is emerging that enables the positioning of populations of on-line, mobile service users. In step with this, research in the management of moving objects has attracted substantial attention. In particular, quite a few proposals now exist for the indexing of moving objects, and more are underway. As a result, there is an increasing need for an independent benchmark for spatio-t...

The multi-population method has been widely used to solve unconstrained continuous dynamic optimization problems with the aim of maintaining multiple populations on different peaks to locate and track multiple changing peaks simultaneously. However, to make this approach efficient, several crucial challenging issues need to be addressed, e.g., how to determine the moment to react to changes, ho...

Photoplethysmogram (PPG) signals contain valuable health information that is in the relation between volumetric variations of blood circulation and cardiovascular respiratory systems. This study introduces performance evaluation on open clinical benchmark PPG with a multiclass neural network random weights (NNRW) classification method for systolic peak diastolic point detection. The best detect...

In a very recently presented paper, Turky and Abdullah [5] proposed a novel multipopulation harmony search with external archive (MHSA-ExtArchive) for dynamic optimization problems. In the experimental results, the authors claimed that their approach could outperform several state-of-the-art algorithms. They also showed the superiority of their method by means of numerical experiments on Moving...

Dynamic function optimisation is an important research area because many real-world problems are inherently dynamic in nature. Over the years, a wide variety of algorithms have been proposed to solve dynamic optimisation problems, and many of these algorithms have used the Moving Peaks (MP) benchmark to test their own capabilities against other approaches. This paper presents a detailed account...

—Many real world problems are mostly time varying optimization problems, which require special mechanisms to detect changes in environment and then response to them. In this paper, combination of learning automata and firefly algorithm in order to improve the performance of firefly algorithm in dynamic environments has been proposed. In the algorithm, the firefly algorithm has been equipped wit...