44 resultados para Algorithms genetics
Resumo:
In this paper, genetic algorithm (GA) is applied to the optimum design of reinforced concrete liquid retaining structures, which comprise three discrete design variables, including slab thickness, reinforcement diameter and reinforcement spacing. GA, being a search technique based on the mechanics of natural genetics, couples a Darwinian survival-of-the-fittest principle with a random yet structured information exchange amongst a population of artificial chromosomes. As a first step, a penalty-based strategy is entailed to transform the constrained design problem into an unconstrained problem, which is appropriate for GA application. A numerical example is then used to demonstrate strength and capability of the GA in this domain problem. It is shown that, only after the exploration of a minute portion of the search space, near-optimal solutions are obtained at an extremely converging speed. The method can be extended to application of even more complex optimization problems in other domains.
Resumo:
Despite many successes of conventional DNA sequencing methods, some DNAs remain difficult or impossible to sequence. Unsequenceable regions occur in the genomes of many biologically important organisms, including the human genome. Such regions range in length from tens to millions of bases, and may contain valuable information such as the sequences of important genes. The authors have recently developed a technique that renders a wide range of problematic DNAs amenable to sequencing. The technique is known as sequence analysis via mutagenesis (SAM). This paper presents a number of algorithms for analysing and interpreting data generated by this technique.
Resumo:
The BR algorithm is a novel and efficient method to find all eigenvalues of upper Hessenberg matrices and has never been applied to eigenanalysis for power system small signal stability. This paper analyzes differences between the BR and the QR algorithms with performance comparison in terms of CPU time based on stopping criteria and storage requirement. The BR algorithm utilizes accelerating strategies to improve its performance when computing eigenvalues of narrowly banded, nearly tridiagonal upper Hessenberg matrices. These strategies significantly reduce the computation time at a reasonable level of precision. Compared with the QR algorithm, the BR algorithm requires fewer iteration steps and less storage space without depriving of appropriate precision in solving eigenvalue problems of large-scale power systems. Numerical examples demonstrate the efficiency of the BR algorithm in pursuing eigenanalysis tasks of 39-, 68-, 115-, 300-, and 600-bus systems. Experiment results suggest that the BR algorithm is a more efficient algorithm for large-scale power system small signal stability eigenanalysis.
Resumo:
The Australian-bred lucerne cultivars, Trifecta and Sequel, were found to possess useful levels of resistance to both Colletotrichum trifolii races 1 and 2. Race 2 has only been previously observed in the United States and surveys did not reveal its presence in Australia. Multilocus fingerprinting using random amplified polymorphic DNA (RAPDs) analysis revealed low diversity (<10% dissimilarity) within Australian C. trifolii collections, and between the Australian race 1 isolates and a US race 2 isolate. Studies on the inheritance of resistance to C. trifolii race 1 in individual clones from Trifecta and Sequel revealed the presence of 2 different genetic mechanisms. One inheritance was for resistance as a recessive trait, and the other indicated that resistance was dominant. The recessive system has never been previously reported, whereas in the US, 2 completely dominant and independent tetrasomic genes Anl and Ant have been reported to condition C. trifolii resistance. It was not possible to fit the observed segregations from our studies to a single-gene model. In contrast to US studies, clones of cv. Sequel exhibiting the recessive resistance reacted differently to spray and stem injection with C. trifolii inoculum, being resistant to the former and susceptible to the latter, providing additional evidence for the presence of a different genetic mechanism conditioning resistance to those previously reported in the US. As C. trifolii is one of the most serious diseases of lucerne worldwide, the future development of molecular markers closely linked to the dominant and recessive resistances identified in these studies, and the relationships between these resistances and Anl and Ans as determined by genetic mapping, appear to be useful areas of future study.
Resumo:
Algorithms for explicit integration of structural dynamics problems with multiple time steps (subcycling) are investigated. Only one such algorithm, due to Smolinski and Sleith has proved to be stable in a classical sense. A simplified version of this algorithm that retains its stability is presented. However, as with the original version, it can be shown to sacrifice accuracy to achieve stability. Another algorithm in use is shown to be only statistically stable, in that a probability of stability can be assigned if appropriate time step limits are observed. This probability improves rapidly with the number of degrees of freedom in a finite element model. The stability problems are shown to be a property of the central difference method itself, which is modified to give the subcycling algorithm. A related problem is shown to arise when a constraint equation in time is introduced into a time-continuous space-time finite element model. (C) 1998 Elsevier Science S.A.
Resumo:
Extended gcd calculation has a long history and plays an important role in computational number theory and linear algebra. Recent results have shown that finding optimal multipliers in extended gcd calculations is difficult. We present an algorithm which uses lattice basis reduction to produce small integer multipliers x(1), ..., x(m) for the equation s = gcd (s(1), ..., s(m)) = x(1)s(1) + ... + x(m)s(m), where s1, ... , s(m) are given integers. The method generalises to produce small unimodular transformation matrices for computing the Hermite normal form of an integer matrix.
Resumo:
We tested the effects of four data characteristics on the results of reserve selection algorithms. The data characteristics were nestedness of features (land types in this case), rarity of features, size variation of sites (potential reserves) and size of data sets (numbers of sites and features). We manipulated data sets to produce three levels, with replication, of each of these data characteristics while holding the other three characteristics constant. We then used an optimizing algorithm and three heuristic algorithms to select sites to solve several reservation problems. We measured efficiency as the number or total area of selected sites, indicating the relative cost of a reserve system. Higher nestedness increased the efficiency of all algorithms (reduced the total cost of new reserves). Higher rarity reduced the efficiency of all algorithms (increased the total cost of new reserves). More variation in site size increased the efficiency of all algorithms expressed in terms of total area of selected sites. We measured the suboptimality of heuristic algorithms as the percentage increase of their results over optimal (minimum possible) results. Suboptimality is a measure of the reliability of heuristics as indicative costing analyses. Higher rarity reduced the suboptimality of heuristics (increased their reliability) and there is some evidence that more size variation did the same for the total area of selected sites. We discuss the implications of these results for the use of reserve selection algorithms as indicative and real-world planning tools.
Resumo:
The majority of severe epileptic encephalopathies of early childhood are symptomatic where a clear etiology is apparent. There is a small subgroup, however, where no etiology is found on imaging and metabolic studies, and genetic factors are important. Myoclonic-astatic epilepsy (MAE) and severe myoclonic epilepsy in infancy (SMEI), also known as Dravet syndrome, are epileptic encephalopathies where multiple seizure types begin in the first few years of life associated with developmental slowing. Clinical and molecular genetic studies of the families of probands with MAE and SMEI suggest a genetic basis. MAE was originally identified as part of the genetic epilepsy syndrome generalized epilepsy with febrile seizures plus (GEFS(+)). Recent clinical genetic studies suggest that SMEI forms the most severe end of the spectrum of the GEFS(+). GEF(+) has now been associated with molecular defects in three sodium channel subunit genes and a GABA subunit gene. Molecular defects of these genes have been identified in patients with MAE and SMEI. Interestingly, the molecular defects in MAE have been found in the setting of large GEFS(+) pedigrees, whereas, more severe truncation mutations arising de novo have been identified in patients with SMEI. It is likely that future molecular studies will shed light on the interaction of a number of genes, possibly related to the same or different ion channels, which result in a severe phenotype such as MAE and SMEI. (C) 2001 Elsevier Science B.V. All rights reserved.
Resumo:
A robust semi-implicit central partial difference algorithm for the numerical solution of coupled stochastic parabolic partial differential equations (PDEs) is described. This can be used for calculating correlation functions of systems of interacting stochastic fields. Such field equations can arise in the description of Hamiltonian and open systems in the physics of nonlinear processes, and may include multiplicative noise sources. The algorithm can be used for studying the properties of nonlinear quantum or classical field theories. The general approach is outlined and applied to a specific example, namely the quantum statistical fluctuations of ultra-short optical pulses in chi((2)) parametric waveguides. This example uses a non-diagonal coherent state representation, and correctly predicts the sub-shot noise level spectral fluctuations observed in homodyne detection measurements. It is expected that the methods used wilt be applicable for higher-order correlation functions and other physical problems as well. A stochastic differencing technique for reducing sampling errors is also introduced. This involves solving nonlinear stochastic parabolic PDEs in combination with a reference process, which uses the Wigner representation in the example presented here. A computer implementation on MIMD parallel architectures is discussed. (C) 1997 Academic Press.
Resumo:
Microsatellites or simple sequence repeats (SSRs) are ubiquitous in eukaryotic genomes. Single-locus SSR markers have been developed for a number of species, although there is a major bottleneck in developing SSR markers whereby flanking sequences must be known to design 5'-anchors for polymerase chain reaction (PCR) primers. Inter SSR (ISSR) fingerprinting was developed such that no sequence knowledge was required. Primers based on a repeat sequence, such as (CA)(n), can be made with a degenerate 3'-anchor, such as (CA)(8)RG or (AGC)(6)TY. The resultant PCR reaction amplifies the sequence between two SSRs, yielding a multilocus marker system useful for fingerprinting, diversity analysis and genome mapping. PCR products are radiolabelled with P-32 or P-33 via end-labelling or PCR incorporation, and separated on a polyacrylamide sequencing gel prior to autoradiographic visualisation. A typical reaction yields 20-100 bands per lane depending on the species and primer. We have used ISSR fingerprinting in a number of plant species, and report here some results on two important tropical species, sorghum and banana. Previous investigators have demonstrated that ISSR analysis usually detects a higher level of polymorphism than that detected with restriction fragment length polymorphism (RFLP) or random amplified polymorphic DNA (RAPD) analyses. Our data indicate that this is not a result of greater polymorphism genetically, but rather technical reasons related to the detection methodology used for ISSR analysis.
Resumo:
The concept of parameter-space size adjustment is pn,posed in order to enable successful application of genetic algorithms to continuous optimization problems. Performance of genetic algorithms with six different combinations of selection and reproduction mechanisms, with and without parameter-space size adjustment, were severely tested on eleven multiminima test functions. An algorithm with the best performance was employed for the determination of the model parameters of the optical constants of Pt, Ni and Cr.