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About 10,000 papers for “Search algorithm”

The pn2-search algorithm

Breuker, (Dennis Michel), Uiterwijk, (Joseph Willem Hubertus Marie), Herik, (Hendrik Jacob) · Data Archiving and Networked Services (DANS) · 1999

Cited by 3

Dynamic Search Radius Algorithm

Sukumaran, Vandana · Zenodo (CERN European Organization for Nuclear Research) · 2025

This dataset contains the processed data for Sukumaran, V. and Vishwakarma, B.D., Accounting for shelf width in selecting altimetry observations for coastal sea level variability improves its agreement with tide gauges. Code is available in the GitHub repository:All codes are uploaded in Github repository https://github.com/Vandana1195/Dynamic-Search-Radius.

Cited by 0Open access

A combined search algorithm

Harry Allen Nelson · CSUN ScholarWorks (California State University, Northridge) · 1972

Cited by 0Open access

Genetic Algorithm parameter search.

Elishai Ezra-Tsur (11888717), Oren Amsalem (11476309), Lea Ankri (11888720) et al. · Figshare · 2021

<p><b>a.</b> Initiation of the genetic algorithm population with 100 randomly selected individuals, each with eight parameters (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1009754#sec010" target="_blank">Methods</a>). <b>b.</b> Illustration of the second generation. The best individuals from Gen 0 are copied to Gen 1 and the rest are a combination of different individuals from the previous generation (illustrated by individuals with combinations of colors). Random jitter (mutations) was added to some of the individuals. <b>c.</b> Same as in b for the X<sup>th</sup> generation. <b>d-f.</b> Progression of GA maximization of the different objectives, as a function of generation number: the difference between the maximal voltage during the centrifugal and centripetal stimuli: Amp<sub>CF</sub>-Amp<sub>CP</sub> (<b>d</b>); the difference between the rise time during the centripetal and centrifugal stimuli: RT<sub>CP</sub>-RT<sub>CF</sub> (<b>e</b>); and the difference between the maximal voltage during the centrifugal stimulus and -10 mV. If the maximal voltage was below -10 mV, this objective was set to zero. This criterion was meant to prevent non-physiological depolarizations above -20 mV (<b>f</b>). Higher values indicate a stronger centrifugal preference. <b>g-i.</b> Same as (<b>d-f</b>) but with the reversed input kinetics. Here, no CF preferring SACs were found, as reflected by the rise time differences in <b>h</b> and the response amplitude difference in <b>g</b>.</p> <p>(EPS)</p>

Cited by 0Open access

Development Binary Search Algorithm

Ragheed D. Salim · Baghdad Science Journal · 2011

There are many methods of searching large amount of data to find one particular piece of information. Such as find name of person in record of mobile. Certain methods of organizing data make the search process more efficient the objective of these methods is to find the element with least cost (least time). Binary search algorithm is faster than sequential and other commonly used search algorithms. This research develops binary search algorithm by using new structure called Triple, structure in this structure data are represented as triple. It consists of three locations (1-Top, 2-Left, and 3-Right) Binary search algorithm divide the search interval in half, this process makes the maximum number of comparisons (Average case complexity of Search) is O(log2 n) (pronounce this "big-Oh-n" or "the order of magnitude"), if we search in a list consists of (N) elements. In this research the number of comparison is reduced to triple by using Triple structure, this process makes the maximum number of comparisons is O(log2 (n)/3+1) if we search key in list consist of (N) elements.

Cited by 0Open access

Signature-based search algorithm

S.A. Khakoo · International Conference on Acoustics, Speech, and Signal Processing · 2003

Most existing search algorithms for motion compensation have been specifically tailored to exploit the interframe redundancy in image sequences that contain small amounts of motion. With large amounts of motion, the performance of these algorithms is significantly reduced. A class of signature-based search algorithms is proposed as an alternative to these algorithms. A specific example, called the frequency labeling search algorithm, is developed in detail. Experimental results show that this algorithm gives compression rates 3-5 times that achieved by other algorithms in the presence of substantial amounts of motion. The accuracy of the technique can be adjusted to suit different applications by changing the number of coefficients used in the signature and the size of the candidate set. While it is computationally more expensive than other approaches, the cost of the frequency labeling technique falls within the range reasonable for real-time applications.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 3

Composite Differential Search Algorithm

Bo Liu · Journal of Applied Mathematics · 2014

Differential search algorithm (DS) is a relatively new evolutionary algorithm inspired by the Brownian-like random-walk movement which is used by an organism to migrate. It has been verified to be more effective than ABC, JDE, JADE, SADE, EPSDE, GSA, PSO2011, and CMA-ES. In this paper, we propose four improved solution search algorithms, namely “DS/rand/1,” “DS/rand/2,” “DS/current to rand/1,” and “DS/current to rand/2” to search the new space and enhance the convergence rate for the global optimization problem. In order to verify the performance of different solution search methods, 23 benchmark functions are employed. Experimental results indicate that the proposed algorithm performs better than, or at least comparable to, the original algorithm when considering the quality of the solution obtained. However, these schemes cannot still achieve the best solution for all functions. In order to further enhance the convergence rate and the diversity of the algorithm, a composite differential search algorithm (CDS) is proposed in this paper. This new algorithm combines three new proposed search schemes including “DS/rand/1,” “DS/rand/2,” and “DS/current to rand/1” with three control parameters using a random method to generate the offspring. Experiment results show that CDS has a faster convergence rate and better search ability based on the 23 benchmark functions.

Cited by 20Open access

Grover's quantum search algorithm

Samuel J. Lomonaco · ArXiv.org · 2000

This paper is a written version of a one hour lecture given on Lov Grover's database search algorithm. Table Of Contents 1 ... Problem Definition 2 ... The quantum mechanical perspective 3 ... Properties of the inversion I_|psi&gt; 4 ... The method in Lov's "madness" 5 ... Summary of Grover's algorithm 6 ... An example of Grover's algorithm References

Cited by 2Open access

PHASE SYNCHRONIZATION SEARCH ALGORITHM.

Hennadii Kovalov · Zenodo (CERN European Organization for Nuclear Research) · 2026

Problem statement We have two objects (proton, hafnium sample, macroscopic resonators) with their own chronal rhythms τ₁ and τ₂. Their state is described by a complex amplitude: Ψ₁ = A₁ exp(iφ₁),Ψ₂ = A₂ exp(iφ₂) where phase φ = ∫ (1/τ) dt is the accumulated chronal angle. Objective: to find such external influences (frequency, phase, duration) that |φ₁ - φ₂| → 0 with a given accuracy.

Cited by 0Open access

Search algorithm performance comparison.

Zhaohui Du (414105), Xiaofeng Zhao (413698), Lin Li (28817) et al. · Figshare · 2025

<div> In recent years, empowered by artificial intelligence technologies, computer-assisted language learning systems have gradually become a hot topic of research. Currently, the mainstream pronunciation assessment models rely on advanced speech recognition technology, converting speech into phoneme sequences, and then determining mispronounced phonemes through sequence comparison. To optimize the phoneme recognition task in pronunciation evaluation, this paper proposes a Chinese pronunciation phoneme recognition model based on the improved Zipformer-RNN-T(Pruned) architecture, aiming to improve recognition accuracy and reduce parameter count. First, the AISHELL1-PHONEME and ST-CMDS-PHONEME datasets for Mandarin phoneme recognition through data preprocessing. Then, three layers of the Zipformer Block architecture are introduced into the Zipformer encoder to significantly enhance model performance. In the stateless Pred Network, the GELU activation function is adopted to effectively prevent neuron deactivation. Furthermore, a hybrid Pruned RNN-T/CTC Loss fusion strategy is proposed, further optimizing recognition performance. The experimental results demonstrate that the method performs excellently in the phoneme recognition task, achieving a Word Error Rate (WER) of 1.92% (Dev) and 2.12% (Test) on the AISHELL1-PHONEME dataset, and 4.28% (Dev) and 4.51% (Test) on the ST-CMDS-PHONEME dataset. Moreover, the model requires only 61.1M parameters, striking a balance between performance and efficiency. </div>

Cited by 0Open access

HIV VL Search Algorithm.

Kimberly A. Sollis (319691), Pieter W. Smit (458975), Susan Fiscus (243736) et al. · Figshare · 2015

Cited by 0Open access

Primer set search algorithm.

Jane A. Dwivedi-Yu (15307239), Zachary J. Oppler (7436867), Matthew W. Mitchell (14817749) et al. · Figshare · 2023

&lt;div&gt;&lt;p&gt;Addressing many of the major outstanding questions in the fields of microbial evolution and pathogenesis will require analyses of populations of microbial genomes. Although population genomic studies provide the analytical resolution to investigate evolutionary and mechanistic processes at fine spatial and temporal scales—precisely the scales at which these processes occur—microbial population genomic research is currently hindered by the practicalities of obtaining sufficient quantities of the relatively pure microbial genomic DNA necessary for next-generation sequencing. Here we present swga2.0, an optimized and parallelized pipeline to design selective whole genome amplification (SWGA) primer sets. Unlike previous methods, swga2.0 incorporates active and machine learning methods to evaluate the amplification efficacy of individual primers and primer sets. Additionally, swga2.0 optimizes primer set search and evaluation strategies, including parallelization at each stage of the pipeline, to dramatically decrease program runtime. Here we describe the swga2.0 pipeline, including the empirical data used to identify primer and primer set characteristics, that improve amplification performance. Additionally, we evaluate the novel swga2.0 pipeline by designing primers sets that successfully amplify &lt;i&gt;Prevotella melaninogenica&lt;/i&gt;, an important component of the lung microbiome in cystic fibrosis patients, from samples dominated by human DNA.&lt;/p&gt;&lt;/div&gt;

Cited by 0Open access