Titlebook: EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI; Alexandru-Adrian Tantar,Emilia Tantar,Henri

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EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI

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https://doi.org/10.1007/978-3-642-22152-1selection criterion, which is front-based in one case and indicator-based in the other case. The two strategies are compared to each other with respect to the search behavior on a generic three-dimensional molecular minimization problem.

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erges to a diverse cover of the Pareto front and efficient set. The demonstration of the algorithms is implemented in Java Script and can therefore run from a website in any conventional browser. Besides using it to reproduce the findings of the paper, it is also suitable as an educational tool in o

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The Mathematics of Symmetry: Group Theory,l conditions is addressed as a fourth objective. All objectives stated above are in general conflicting with each other and that is why we address the problem as a 4-objective (quadcriteria) optimization problem. We assess the performance of a set of state-of-the-art evolutionary multiobjective opti

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https://doi.org/10.1007/3-540-06705-1LSA) for noisy parameter identification problems will be developed and validated. The validation uses two classical gene regulatory networks and it is demonstrated that a larger set of reaction parameters can be found that potentially could explain the observed stochastic dynamics.

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Alessandro Cuomo,Tiziana Bonaldimmunity detection. We will not look at communities of epistatic links but instead focus on links due to correlation between phenotypic traits. To this end we view a single trait as an individual agent which strives to maximize its contributed value to the net value of a community. If the value of a

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Making Choices About Situations and Systemsuth Africa using a 19-year baseline record. Two case studies were considered. Case study 1 involved the use of correlation analysis in selecting input variables during model development while using DE algorithm for optimization purposes. However in the second case study, GP was incorporated as a scr

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Systems Programming in Unix/Linuxsitive rate (.) and around 16% in F-measure (FM) on the average; also, it performs better than sampling strategies, with ~35% relative improvement in . and ~12% in FM over SMOTE (on the average), similar . and geometric mean (GM) values and slightly higher area under de curve (AUC) values than EUS (