Search results for "Genetic Algorithms"

RepeatsDB 2.0: improved annotation, classification, search and visualization of repeat protein structures

2017

RepeatsDB 2.0 (URL: http://repeatsdb.bio.unipd.it/) is an update of the database of annotated tandem repeat protein structures. Repeat proteins are a widespread class of non-globular proteins carrying heterogeneous functions involved in several diseases. Here we provide a new version of RepeatsDB with an improved classification schema including high quality annotations for ∼5400 protein structures. RepeatsDB 2.0 features information on start and end positions for the repeat regions and units for all entries. The extensive growth of repeat unit characterization was possible by applying the novel ReUPred annotation method over the entire Protein Data Bank, with data quality is guaranteed by a…

Using Genetic Algorithms for Optimizing the PPC in the Highway Horizontal Alignment Design.

2016

Various studies have emphasized the interesting advantages related to the use of new transition curves for improving the geometric design of highway horizontal alignments. In a previous paper, one of the writers proposed a polynomial curve, called a polynomial parametric curve (PPC), proving its efficiency in solving several design problems characterized by a very complex geometry (egg-shaped transition, transition between reversing circular curves, semidirect and inner-loop connections, and so on). The PPC also showed considerable advantages from a dynamic perspective, as evidenced by the analysis of the main dynamic variables related to motion (as well as rate of change of radial accelera…

An evolutionary restricted neighborhood search clustering approach for PPI networks

2014

Protein-protein interaction networks have been broadly studied in the last few years, in order to understand the behavior of proteins inside the cell. Proteins interacting with each other often share common biological functions or they participate in the same biological process. Thus, discovering protein complexes made of a group of proteins strictly related can be useful to predict protein functions. Clustering techniques have been widely employed to detect significant biological complexes. In this paper, we integrate one of the most popular network clustering techniques, namely the Restricted Neighborhood Search Clustering (RNSC), with evolutionary computation. The two cost functions intr…

A genetic system based on simulated crossover of sequences of two-bit genes

2006

AbstractWe introduce a genetic model based on simulated crossover of fixed sequences of two-bit genes. Results are(1)a lower bound on population size is exhibited such that a transition takes the stochastic finite population genetic system near the next state of the deterministic infinite population genetic system (provided both begin in the same state);(2)states and dynamics of the deterministic infinite population genetic system are derived for arbitrary (finite) fitness functions (expressed in terms of multivariate polynomials);(3)in the case of quadratic fitness defined by weight matrices with m nonnull entries it is shown that each state transition can be implemented in time O(m+l), wh…

Automatic optimization of multichip RFID tags

2012

The automatic optimization is proposed of the passive RF part of RFID, with special attention to multi-chip tags, and to the novel concept of RFID grids. Performance metrics follows a recent all-comprehensive approach. The proposed approach employs a Genetic Algorithm-based optimization, and an efficient electromagnetic problem parameterization and solution strategy. Resulting structures, while non-intuitive in shape, exhibit enhanced performance.

Evolutionary design optimization with Nash games and hybridized mesh/meshless methods in computational fluid dynamics

2012

Hybrid Genetic Algorithms in Data Mining Applications

2009

Genetic algorithms (GAs) are a class of problem solving techniques which have been successfully applied to a wide variety of hard problems (Goldberg, 1989). In spite of conventional GAs are interesting approaches to several problems, in which they are able to obtain very good solutions, there exist cases in which the application of a conventional GA has shown poor results. Poor performance of GAs completely depends on the problem. In general, problems severely constrained or problems with difficult objective functions are hard to be optimized using GAs. Regarding the difficulty of a problem for a GA there is a well established theory. Traditionally, this has been studied for binary encoded …

The use of Genetic Algorithms to solve the allocation problems in the Life Cycle Assessment

2011

The paper applies a GA (Genetic Algorithms) to a multi-output productive process of essential oils, natural and concen-trated juices from oranges and lemonsThe results obtained for the case study taken into consideration showed that the application of GA allows to respect the energ y and mass balances for the examined system .

Prediction of the mesiodistal size of unerupted canines and premolars for a group of Romanian children: a comparative study

2013

Objectives The aim of the present study was to develop an optimization method of multiple linear regression equation (MLRE), using a genetic algorithm to determine a set of coefficients that minimize the prediction error for the sum of permanent premolars and canine dimensions in a group of young people from a central area of Romania represented by a city called Sibiu. Material and Methods To test the proposed method, we used a multiple linear regression equation derived from the estimation method proposed by Mojers, to which we adjusted regression coefficients using the Breeder genetic algorithm. A total of 92 children were selected with complete permanent teeth with no clinically visible …

Developing Domain-Knowledge Evolutionary Algorithms for Network-on-Chip Application Mapping

2013

This paper addresses the Network-on-Chip (NoC) application mapping problem. This is an NP-hard problem that deals with the optimal topological placement of Intellectual Property cores onto the NoC tiles. Network-on-Chip application mapping Evolutionary Algorithms are developed, evaluated and optimized for minimizing the NoC communication energy. Two crossover and one mutation operators are proposed. It is analyzed how each optimization algorithm performs with every genetic operator, in terms of solution quality and convergence speed. Our proposed operators are compared with state-of-the-art genetic operators for permutation problems. Finally, the problem is approached in a multi-objective w…