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27 results for “evolutionary model”
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Research ArticleOpen accessIn the abstractSTATIONARY CONNECTED CURVES IN HILBERT SPACESRaed Hatamleh, Ahmad Qazza, Hatim MigdadiIn this article the structure of non-stationary curves which are stationary connected in Hilbert space is studied using triangular models of non-self-adjoint operator. The concept of evolutionary representability plays here an important role. It is proved that if one of two curves in Hilbert space is evolutionary representable and the curves are stationary connected, then another curve is evolutionary representable … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 17 May 2014 · 6,799 accessesView PDFCite
Research ArticleOpen accessIn the abstractINFLUENCE OF EVOLUTIONARY COMPUTING ON NUTRITION RECOMMENDATION: A SURVEYA. A. Hegazy, M. A. Belal, S. A. AlFayoumiThis study is a survey about how Evolutionary Computing doesn’t play its important role in a vital field such as Nutrition. Evolutionary computing is a subset from the artificial intelligence umbrella that involves continuous optimization and combinational optimization which is based on searching methodologies. It has also a lot of algorithms that have played a main role in supporting the … …Journal of Computer Science, Vol. 10, Issue 10 · 8 May 2014 · 6,490 accessesView PDFCite
Research ArticleOpen accessIn the abstractGENETIC-BASED NUTRITION RECOMMENDATION MODELS. A.A. Fayoumi, A. A. Hegazy, M. A. BelalEvolutionary computing is the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. These techniques are being widely applied to a variety of problems in many vital fields. Also, Evolutionary Algorithms (EA) which applied the principles of Evolutionary computations, such as genetic algorithm, particle swarm, ant colony and … …Journal of Computer Science, Vol. 10, Issue 9 · 24 Apr 2014 · 6,854 accessesView PDFCite
Research ArticleOpen accessIn the abstractScheduling of Automated Guided Vehicle and Flexible Jobshop using Jumping Genes Genetic AlgorithmP. Paul Pandian, S. Saravana Sankar, S. G. Ponnambalam, M. Victor RajProblem statement: Now a day’s many researchers try Genetic algorithm based optimization to find near optimal solution for flexible job shop. It is a global search. In Our study in the GA, some changes are made to search locally and globally by adding jumping genes operation. A typical flexible job shop model is considered for this research study. For that … …American Journal of Applied Sciences, Vol. 9, Issue 10 · 25 Aug 2012 · 7,306 accessesView PDFCite
Research ArticleOpen accessIn the abstractStructural and Evolutionary Analysis of PARPs in D. discoideumA. Mehadvi Kawal, Hina A. Mir, Chethan Kumar Ramniklal et al.Problem statement: Dictyostelium discoideum, a unicellular eukaryote, exhibits multicellularity upon nutrient starvation, making it a better model for developmental studies and for the study of various signal transduction pathways. The most felicitous point of interest is that many of its genes show high degree of similarity to vertebrate genes. Poly (ADP-ribose) polymerase (PARP), a ubiquitous and abundant nuclear protein, has … …American Journal of Infectious Diseases, Vol. 7, Issue 3 · 3 Nov 2011 · 7,852 accessesView PDFCite
Research ArticleOpen accessIn the abstractWeighted Centroid Modified Simplex and Linear Constrained Response Surface Optimization Methods for the Xbar-R Chart Variable DeterminationPongchanun LuangpaiboonProblem statement: Although economic Xbar-R chart designs do guarantee the minimal operating cost, they typically have poor levels of statistical performance measures. The obvious limitation of the economic design is that the Type I error rate seems to be very high for many situations and will cause a large number of false alarms. This situation leads to an investigation of … …Journal of Computer Science, Vol. 7, Issue 6 · 14 Jun 2011 · 7,115 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementation and Evaluation of Evolutionary Connectionist Approaches to Automated Text SummarizationUday Kulkarni, Rajesh Shardanand PrasadProblem statement: Text summarization takes care of choosing the most significant portions of text and generates coherent summaries that express the main intent of the given document. This study aims to compare the performances of the three text summarization systems developed by the authors with some of the existing Summarization systems available. These three approaches to text summarization are based … …Journal of Computer Science, Vol. 6, Issue 11 · 23 Oct 2010 · 8,489 accessesView PDFCite
Research ArticleOpen accessIn the abstractEstimation of Genetic Correlations on Sweet Corn Inbred Lines Using SAS Mixed ModelPedram Kashiani, Ghizan SalehProblem statement: Genetic correlations among traits refer to the extent of relatedness among them due to genetic causes. Estimating genetic correlations for quantitative traits is tedious if done manually. Approach: However, the use of the computer software SAS, applying mixed-model analysis of variance has facilitated many recent studies in evolutionary quantitative genetics. Results: In this two-way statistical model, the variance … …American Journal of Agricultural and Biological Sciences, Vol. 5, Issue 3 · 30 Sep 2010 · 10,891 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplying Evolutionary Computing in Case Retrieval StageNabila Nouaouria-Amri, Med Tayeb LaskriCase Based Reasoning is a problem solving paradigm which is able to retrieve and reuse solutions that have worked for similar situations in the past. Past situations and their solutions are stored in a memory called case base. To find the good experiment in memory is the key of success in the reasoning. To identify adequate experiment in memory constitutes … …Journal of Computer Science, Vol. 1, Issue 3 · 30 Sep 2005 · 6,738 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybridization of Neural Learning Algorithms Using Evolutionary and Discrete Gradient ApproachesRanadhir Ghosh, John Yearwood, Moumita Ghosh, Adil BagirovIn this study we investigated a hybrid model based on the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. Also we discuss different variants for hybrid models using the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. The Discrete Gradient … …Journal of Computer Science, Vol. 1, Issue 3 · 30 Sep 2005 · 6,587 accessesView PDFCite