Search results for " algorithm"

showing 10 items of 2538 documents

ELM Regularized Method for Classification Problems

2016

Extreme Learning Machine (ELM) is a recently proposed algorithm, efficient and fast for learning the parameters of single layer neural structures. One of the main problems of this algorithm is to choose the optimal architecture for a given problem solution. To solve this limitation several solutions have been proposed in the literature, including the regularization of the structure. However, to the best of our knowledge, there are no works where such adjustment is applied to classification problems in the presence of a non-linearity in the output; all published works tackle modelling or regression problems. Our proposal has been applied to a series of standard databases for the evaluation o…

Wake-sleep algorithmComputer sciencebusiness.industryTraining timeBayesian probability02 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesRegularization (mathematics)Support vector machine010104 statistics & probabilityArtificial Intelligence0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligence0101 mathematicsbusinessRegression problemscomputerSingle layerExtreme learning machineInternational Journal on Artificial Intelligence Tools
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Genetic Algorithm Modeling for Photocatalytic Elimination of Impurity in Wastewater

2019

The existence of C.I. Acid Yellow 23 (AY23) in water causes a great danger to people and society. Here, we suggest an advanced technique which predicts the photochemical deletion of AY23. The genetic algorithm (GA) technique is suggested in order to predict the photocatalytic removal of AY23 by implementing the Ag-TiO\(_{2}\) nanoparticles provided under appropriate conditions.

WastewaterImpurityComputer scienceGenetic algorithm0202 electrical engineering electronic engineering information engineeringPhotocatalysisOrder (ring theory)020201 artificial intelligence & image processing02 engineering and technology021001 nanoscience & nanotechnology0210 nano-technologyBiological system
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Gully Erosion Susceptibility Mapping Using Multivariate Adaptive Regression Splines—Replications and Sample Size Scenarios

2019

Soil erosion is a serious problem affecting numerous countries, especially, gully erosion. In the current research, GIS techniques and MARS (Multivariate Adaptive Regression Splines) algorithm were considered to evaluate gully erosion susceptibility mapping among others. The study was conducted in a specific section of the Gorganroud Watershed in Golestan Province (Northern Iran), covering 2142.64 km2 which is intensely influenced by gully erosion. First, Google Earth images, field surveys, and national reports were used to provide a gully-hedcut evaluation map consisting of 307 gully-hedcut points. Eighteen gully erosion conditioning factors including significant geoenvironmental and morph…

Watershedlcsh:Hydraulic engineering010504 meteorology & atmospheric sciencesCalibration (statistics)Settore GEO/04 - Geografia Fisica E GeomorfologiaGeography Planning and Development0207 environmental engineering02 engineering and technologyGully erosionrobustnessAquatic Science01 natural sciencesBiochemistrygislcsh:Water supply for domestic and industrial purposeslcsh:TC1-978Statisticsgully erosion susceptibility020701 environmental engineering0105 earth and related environmental sciencesWater Science and TechnologyMathematicslcsh:TD201-500Multivariate adaptive regression splinesReceiver operating characteristicMars Exploration Programmars algorithmSample size determinationSettore GEO/05 - Geologia ApplicataKappaWater
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Convergence of inertial prox-penalization and inertial forward-backward algorithms for solving bilevel monotone equilibrium problems

2023

The main focus of this paper is on bilevel optimization on Hilbert spaces involving two monotone equilibrium bifunctions. We present a new achievement consisting on the introduction of inertial methods for solving this type of problems. Indeed, two several inertial type methods are suggested: a proximal algorithm and a forwardbackward one. Under suitable conditions and without any restrictive assumption on the trajectories, the weak and strong convergence of the sequence generated by the both iterative methods are established. Two particular cases illustrating the proposed methods are thereafter discussed with respect to hierarchical minimization problems and equilibrium problems under a sa…

Weak and strong convergenceBilevel Equilibrium problemsEquilibrium Fitzpatrick transformProximal algorithm[MATH] Mathematics [math]Monotone bifunctions
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Weak and strong convergence of an inertial proximal method for solving bilevel monotone equilibrium problems

2022

In this paper, we introduce an inertial proximal method for solving a bilevel problem involving two monotone equilibrium bifunctions in Hilbert spaces. Under suitable conditions and without any restrictive assumption on the trajectories, the weak and strong convergence of the sequence generated by the iterative method are established. Two particular cases illustrating the proposed method are thereafter discussed with respect to hierarchical minimization problems and equilibrium problems under saddle point constraint. Furthermore, a numerical example is given to demonstrate the implementability of our algorithm. The algorithm and its convergence results improve and develop previous results i…

Weak and strong convergenceBilevel Equilibrium problemsOptimization and Control (math.OC)G.1.6Equilibrium Fitzpatrick transformFOS: MathematicsProximal algorithm90C33 49J40 46N10 65K15 65K10[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]Monotone bifunctionsMathematics - Optimization and Control
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Feature selection: A multi-objective stochastic optimization approach

2020

The feature subset task can be cast as a multiobjective discrete optimization problem. In this work, we study the search algorithm component of a feature subset selection method. We propose an algorithm based on the threshold accepting method, extended to the multi-objective framework by an appropriate definition of the acceptance rule. The method is used in the task of identifying relevant subsets of features in a Web bot recognition problem, where automated software agents on the Web are identified by analyzing the stream of HTTP requests to a Web server.

Web serverLinear programmingthreshold acceptingComputer scienceFeature extractionFeature selectionstochastic optimizationcomputer.software_genreMulti-objective optimizationfeature selection; multiobjective optimization; stochastic optimization; subset selection; threshold acceptingfeature selectionsubset selectionFeature (computer vision)Search algorithmStochastic optimizationmultiobjective optimizationData miningcomputer
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Non-Technological Aspects on Web Searching Success

2008

This paper studies the influence of social, cultural and emotional background of typical Web users into the web searching process. Several variables, describing such aspects, are represented and statistically analyzed with well known clustering and classifying algorithms such, as COBWEB, J48, Bayes classification, and Correspondence analysis. Results indicate that the efficiency of the complete process of Information Retrieval will not be fully understood without considering subjectivity and personality facts.

Web standardsBayes' theoremInformation retrievalC4.5 algorithmComputer scienceProcess (engineering)media_common.quotation_subjectPersonalityCluster analysisCorrespondence analysisCategory utilitymedia_common
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CN2-R: Faster CN2 with randomly generated complexes

2011

Among the rule induction algorithms, the classic CN2 is still one of the most popular ones; a great amount of enhancements and improvements to it is to witness this. Despite the growing computing capacities since the algorithm was proposed, one of the main issues is resource demand. The proposed modification, CN2-R, substitutes the star concept of the original algorithm with a technique of randomly generated complexes in order to substantially improve on running times without significant loss in accuracy.

Weighted Majority AlgorithmTheoretical computer scienceRule inductionComputer sciencePopulation-based incremental learningStability (learning theory)Online machine learningProbabilistic analysis of algorithmsAlgorithm designStar (graph theory)Algorithm2011 16th International Conference on Methods & Models in Automation & Robotics
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Experimental introgression to evaluate the impact of sex specific traits onDrosophila melanogasterincipient speciation

2019

ABSTRACTSex specific traits are involved in speciation but it is difficult to determine whether their variation initiates or reinforces sexual isolation. In some insects, speciation depends of the rapid change of expression in desaturase genes coding for sex pheromones. Two closely related desaturase genes are involved inDrosophila melanogasterpheromonal communication:desat1affects both the production and the reception of sex pheromones whiledesat2is involved in their production in flies of Zimbabwe populations. There is a strong asymmetric sexual isolation between Zimbabwe populations and all other “Cosmopolitan” populations: Zimbabwe females rarely copulate with Cosmopolitan males whereas…

White (mutation)biologyEvolutionary biologySex pheromoneGenetic algorithmIntrogressionDrosophila melanogasterMatingIncipient speciationbiology.organism_classificationGene
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Lightweight LCP construction for next-generation sequencing datasets

2012

The advent of "next-generation" DNA sequencing (NGS) technologies has meant that collections of hundreds of millions of DNA sequences are now commonplace in bioinformatics. Knowing the longest common prefix array (LCP) of such a collection would facilitate the rapid computation of maximal exact matches, shortest unique substrings and shortest absent words. CPU-efficient algorithms for computing the LCP of a string have been described in the literature, but require the presence in RAM of large data structures. This prevents such methods from being feasible for NGS datasets. In this paper we propose the first lightweight method that simultaneously computes, via sequential scans, the LCP and B…

Whole genome sequencingGenomics (q-bio.GN)FOS: Computer and information sciencesSequenceBWT; LCP; next-generation sequencing datasetsBWT LCP text indexes next-generation sequencing datasets massive datasetsSettore INF/01 - InformaticaComputer scienceComputationString (computer science)LCP arrayParallel computingData structureDNA sequencingSubstringBWTLCPFOS: Biological sciencesComputer Science - Data Structures and AlgorithmsQuantitative Biology - GenomicsData Structures and Algorithms (cs.DS)next-generation sequencing datasets
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