Search results for "Genetic algorithm"
showing 10 items of 834 documents
Flush-Crash Experiments in Drosophila
1989
In 1968, Hampton Carson (1968) proposed the founder-flush-crash model, a new model of speciation, which readily lends itself to experimental testing in the laboratory (Carson 1971).
Efficiency improvement of DC* through a Genetic Guidance
2017
DC∗ is a method for generating interpretable fuzzy information granules from pre-classified data. It is based on the subsequent application of LVQ1 for data compression and an ad-hoc procedure based on A∗ to represent data with the minimum number of fuzzy information granules satisfying some interpretability constraints. While being efficient in tackling several problems, the A∗ procedure included in DC∗ may happen to require a long computation time because the A∗ algorithm has exponential time complexity in the worst case. In this paper, we approach the problem of driving the search process of A∗ by suggesting a close-to-optimal solution that is produced through a Genetic Algorithm (GA). E…
The temporal analogue of diffractive couplers
2020
International audience; Based on the space-time duality of light, we numerically demonstrate that temporal dispersion grating couplers can generate from a single pulse an array of replicas of equal amplitude. The phase-only profile of the temporal grating is optimized by a genetic algorithm that takes into account the optoelectronic bandwidth limitations of the setup.
Companies’ Selection Methods for Inclusion in Sustainable Indices: A Fuzzy Approach
2017
Sustainability indices handle concepts which are both, of numerical and non-numerical nature. In this context, the use of Fuzzy Logic is highly useful as allows a more faithful representation of reality. Usually these indices follow a three-step process to define sustainable investment universes. First step consists of sustainability assessment. In the second step, assets are rated based on the previously assessed sustainability scores and finally, best assets are selected. This last step relies on the construction of a global score reflecting the performance of the assets in main sustainability dimensions. In this Chapter we are concerned with the third step of the selection process. We re…
Past climate changes facilitated homoploid speciation in three mountain spiny fescues (Festuca, Poaceae)
2016
Apart from the overwhelming cases of allopolyploidization, the impact of speciation through homoploid hybridization is becoming more relevant than previously thought. Much less is known, however, about the impact of climate changes as a driven factor of speciation. To investigate these issues, we selected Festuca picoeuropeana, an hypothetical natural hybrid between the diploid species F. eskia and F. gautieri that occurs in two different mountain ranges (Cantabrian Mountains and Pyrenees) separated by more than 400 km. To unravel the outcomes of this mode of speciation and the impact of climate during speciation we used a multidisciplinary approach combining genome size and chromosome coun…
Non-syndromic Mitral Valve Dysplasia Mutation Changes the Force Resilience and Interaction of Human Filamin A
2018
International audience; Filamin A (FLNa), expressed in endocardial endothelia during fetal valve morphogenesis, is key in cardiac development. Missense mutations in FLNa cause non-syndromic mitral valve dysplasia (FLNA-MVD). Here, we aimed to reveal the currently unknown underlying molecular mechanism behind FLNA-MVD caused by the FLNa P637Q mutation. The solved crystal structure of the FLNa3-5 P637Q revealed that this mutation causes only minor structural changes close to mutation site. These changes were observed to significantly affect FLNa's ability to transmit cellular force and to interact with its binding partner. The performed steered molecular dynamics simulations showed that signi…
Mind the depth: The vertical dimension of a small-scale coastal fishery shapes selection on species, size, and sex in wrasses
2020
Small‐scale fisheries (SSFs) tend to target shallow waters, but the depth distributions of coastal fish can vary depending on species, size, and sex. This creates a scope for a form of fishing selectivity that has received limited attention but can have considerable implications for monitoring and management of these fisheries. We conducted a case study on the Norwegian wrasse fishery, a developing SSF in which multiple species are caught in shallow waters (mean depth = 4.5 m) to be used as cleaner fish in aquaculture. Several of these wrasses have life histories and behaviors that are sensitive to selective fishing mortality, such as sexual size dimorphism, paternal care, and sex change. A…
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 …
A genetic algorithm for image segmentation
2002
The paper describes a new algorithm for image segmentation. It is based on a genetic approach that allow us to consider the segmentation problem as a global optimization problem (GOP). For this purpose, a fitness function, based on the similarity between images, has been defined. The similarity is a function of both the intensity and the spatial position of pixels. Preliminary results, obtained using real images, show a good performance of the segmentation algorithm.
Research of a Cellular Automaton Simulating Logic Gates by Evolutionary Algorithms
2003
This paper presents a method of using genetic programming to seek new cellular automata that perform computational tasks. Two genetic algorithms are used : the first one discovers a rule supporting gliders and the second one modifies this rule in such a way that some components appear allowing it to simulate logic gates. The results show that the genetic programming is a promising tool for the search of cellular automata with specific behaviors, and thus can prove to be decisive for discovering new automata supporting universal computation.