Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

Search 250 million research papers

Read the abstract, see who wrote it and who cites it, and get the citation in APA, MLA, Chicago or Harvard.

About 10,000 papers for “Algorithm”

Newton algorithm and rational Newton algorithm

Richard-Jung, F., Informatique et Mathematiques Appliquees de Grenoble (IMAG), 38 - Grenoble (France). Lab. de Modelisation et de Calcul, Institut National Polytechnique de Grenoble (INPG), 38 - Grenoble (France). Lab. de Modelisation et de Calcul · OpenGrey (Institut de l'Information Scientifique et Technique) · 1995

Available at INIST (FR), Document Supply Service, under shelf-number : 22495, issue : a.1995 n.143 / INIST-CNRS - Institut de l'Information Scientifique et Technique

Cited by 0

Implementation of Novel Algorithm (SPruning Algorithm)

Srishti Taneja · IOSR Journal of Computer Engineering · 2014

Decision trees are very significant for taking any type of verdict related to any field. Today there is ample amount of data but that data is uncooked data therefore to make it cooked data, data mining is done. Data mining concept has been used to enhance the quality of data. Various techniques are there in data mining for growth in information technology. Those techniques are classification; clustering, association rules etc. For classifying the data best method is to generate a decision tree. By using decision tree best decisions can be made as it is hierarchal structure which can be easy to interpret. A novel algorithm is implemented which gives results faster and has enhanced features than conventional algorithms of data mining. In new approach some features of Univariate algorithm (i.e. CART algorithm) and some features of Multivariate algorithm (i.e. M5P algorithm) plus an enhanced feature of new algorithm is included. The new feature of algorithm does enhancement in performance as using it performance is improved. In novel approach pruning of files is done due to which specific data can be accessed. Time is saved by using this algorithm and user can perform the task quickly and efficiently.

Cited by 1Open access

Extended Euclidean Algorithm and CRT Algorithm

Hiroyuki Okazaki, Yosiki Aoki, Yasunari Shidama · Formalized Mathematics · 2012

Summary In this article we formalize some number theoretical algorithms, Euclidean Algorithm and Extended Euclidean Algorithm [9]. Besides the a gcd b, Extended Euclidean Algorithm can calculate a pair of two integers (x, y) that holds ax + by = a gcd b. In addition, we formalize an algorithm that can compute a solution of the Chinese remainder theorem by using Extended Euclidean Algorithm. Our aim is to support the implementation of number theoretic tools. Our formalization of those algorithms is based on the source code of the NZMATH, a number theory oriented calculation system developed by Tokyo Metropolitan University [8].

Cited by 2Open access

Parameter-estimation algorithm (Par-Est algorithm).

Jiaping Ren (3170748), Xinjie Wang (231042), Xiaogang Jin (170080) et al. · Figshare · 2016

<p>For the given real-world trajectory data of an insect swarm, we compute the discrete PDFs of the seven time-varying metrics using that data. Meanwhile, we use the parameterized dynamics model to simulate the insects and compute the discrete PDFs of the seven time-varying metrics with the simulation data. Next, we evaluate the function given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155698#pone.0155698.e021" target="_blank">Eq (6)</a> and use that as an objective function for the genetic algorithm to compute the optimal parameters.</p>

Cited by 0Open access

An Efficiency apriori Algorithm: P_Matrix Algorithm

Bai Si-xue, Xinxi Dai · 2007

Apriori algorithm is the most classical algorithm in association rule mining, but it has two fatal deficiencies: more scans for the databases and generates a great deal of candidate itemsets. To solve these two deficiencies of Apriori algorithm, an efficient and fast algorithm based on Pattern Matrix (named P_Matrix algorithm) is proposed, which solves these two problems: scanning for the databases is cut down to one time and not generating the candidate itemsets but generating the frequent itemsets directly. It greatly reduces the temporal complexity and spatial complexity of the algorithm and highly promotes the efficiency of Aprior algorithm. Key words: data mining; association rule; Apriori algorithm; P_Matrix algorithm

Cited by 7