Data Warehouse Algorithm Study with a Novel Mutation Operator

2014 ◽  
Vol 602-605 ◽  
pp. 3388-3391
Author(s):  
Jian Cao ◽  
Gang Li ◽  
Cheng Tao Zhang
Keyword(s):  
Data Mining ◽  
Data Warehouse ◽  
Optimization Problems ◽  
Novel Mutation ◽  
Random Variables ◽  
Current Situation ◽  
Plan Recognition ◽  
Mutation Operator ◽  
Complex Optimization ◽  
Independent Identically Distributed

Focused on the issue of establishing data warehouse in data mining study, the study also considered the current situation of researches into dynamic plan recognition. This paper aims to enhance the performance of PSO in complex optimization problems and proposes an improved PSO variant by incorporating a novel mutation operator. The results obtained extend and improve the corresponding theorem for independent identically distributed random variables sequence.

Identical Distributed Pairwise NQD Random Variables Sequences with a Novel Mutation Operator

2014 ◽  
Vol 989-994 ◽  
pp. 2491-2494
Author(s):  
Jian Cao ◽  
Gang Li ◽  
Cen Rui Ma
Keyword(s):  
Optimization Problems ◽  
Novel Mutation ◽  
Random Variables ◽  
Strong Stability ◽  
Mutation Operator ◽  
Linear Forms ◽  
Grid Portal ◽  
Complex Optimization ◽  
Independent Identically Distributed ◽  
Improved Pso

We study the strong stability of linear forms of pairwise negatively quadrant dependent (NQD) identically distributed random variables sequence under some suitable conditions. To overcome the weakness of collaborative services ability in different grid portal, a new grid portal architecture based on CSGPA (Collaborative Services Grid Portal Architecture), is proposed. This paper aims to enhance the performance of PSO in complex optimization problems and proposes an improved PSO variant by incorporating a novel mutation operator. The results obtained extend and improve the corresponding theorem for independent identically distributed random variables sequence.

A Database Grid Service with a Novel Mutation Operator

2014 ◽  
Vol 989-994 ◽  
pp. 4869-4872
Author(s):  
Jian Cao ◽  
Yan Bin Li ◽  
Cong Yan
Keyword(s):  
Optimization Problems ◽  
Novel Mutation ◽  
Experimental Studies ◽  
Heterogeneous Databases ◽  
Grid Service ◽  
Benchmark Problems ◽  
Mutation Operator ◽  
Grid Portal ◽  
Complex Optimization ◽  
Improved Pso

Database grid service provides users with a unified interface to access to distributed heterogeneous databases resources. To overcome the weakness of collaborative services ability in different grid portal, a new grid portal architecture based on CSGPA (Collaborative Services Grid Portal Architecture), is proposed. This paper aims to enhance the performance of PSO in complex optimization problems and proposes an improved PSO variant by incorporating a novel mutation operator. Experimental studies on some well-known benchmark problems show that our approach achieves promising results.

A Note on the Accuracy of Normal Approximation of Random Quantities

2021 ◽  
Vol 73 (1) ◽  
pp. 62-67
Author(s):  
Ibrahim A. Ahmad ◽  
A. R. Mugdadi
Keyword(s):  
Sample Size ◽  
Order Statistic ◽  
Normal Approximation ◽  
Order Approximation ◽  
Random Variables ◽  
Random Variable ◽  
Limiting Distribution ◽  
Exact Order ◽  
Fixed Sample ◽  
Independent Identically Distributed

For a sequence of independent, identically distributed random variable (iid rv's) [Formula: see text] and a sequence of integer-valued random variables [Formula: see text], define the random quantiles as [Formula: see text], where [Formula: see text] denote the largest integer less than or equal to [Formula: see text], and [Formula: see text] the [Formula: see text]th order statistic in a sample [Formula: see text] and [Formula: see text]. In this note, the limiting distribution and its exact order approximation are obtained for [Formula: see text]. The limiting distribution result we obtain extends the work of several including Wretman[Formula: see text]. The exact order of normal approximation generalizes the fixed sample size results of Reiss[Formula: see text]. AMS 2000 subject classification: 60F12; 60F05; 62G30.

scholarly journals Search Patterns Based on Trajectories Extracted from the Response of Second-Order Systems

2021 ◽  
Vol 11 (8) ◽  
pp. 3430
Author(s):  
Erik Cuevas ◽  
Héctor Becerra ◽  
Héctor Escobar ◽  
Alberto Luque-Chang ◽  
Marco Pérez ◽  
...  
Keyword(s):  
Convergence Rates ◽  
Optimization Problems ◽  
Search Space ◽  
Second Order ◽  
Order System ◽  
Search Patterns ◽  
Multiple Behaviors ◽  
Complex Optimization ◽  
Second Order Systems ◽  
Order Algorithm

Recently, several new metaheuristic schemes have been introduced in the literature. Although all these approaches consider very different phenomena as metaphors, the search patterns used to explore the search space are very similar. On the other hand, second-order systems are models that present different temporal behaviors depending on the value of their parameters. Such temporal behaviors can be conceived as search patterns with multiple behaviors and simple configurations. In this paper, a set of new search patterns are introduced to explore the search space efficiently. They emulate the response of a second-order system. The proposed set of search patterns have been integrated as a complete search strategy, called Second-Order Algorithm (SOA), to obtain the global solution of complex optimization problems. To analyze the performance of the proposed scheme, it has been compared in a set of representative optimization problems, including multimodal, unimodal, and hybrid benchmark formulations. Numerical results demonstrate that the proposed SOA method exhibits remarkable performance in terms of accuracy and high convergence rates.

scholarly journals A counterexample to the existence of a general central limit theorem for pairwise independent identically distributed random variables

2021 ◽  
Vol 499 (1) ◽  
pp. 124982
Author(s):  
Benjamin Avanzi ◽  
Guillaume Boglioni Beaulieu ◽  
Pierre Lafaye de Micheaux ◽  
Frédéric Ouimet ◽  
Bernard Wong
Keyword(s):  
Central Limit Theorem ◽  
Limit Theorem ◽  
Central Limit ◽  
Random Variables ◽  
Independent Identically Distributed

scholarly journals Chunking and cooperation in particle swarm optimization for feature selection

2021 ◽  
Author(s):  
Malek Sarhani ◽  
Stefan Voß
Keyword(s):  
Feature Selection ◽  
Particle Swarm Optimization ◽  
Cooperative Learning ◽  
Optimization Problems ◽  
Practical Importance ◽  
Particle Swarm ◽  
Large Datasets ◽  
Social Phenomena ◽  
Swarm Optimization ◽  
Complex Optimization

AbstractBio-inspired optimization aims at adapting observed natural behavioral patterns and social phenomena towards efficiently solving complex optimization problems, and is nowadays gaining much attention. However, researchers recently highlighted an inconsistency between the need in the field and the actual trend. Indeed, while nowadays it is important to design innovative contributions, an actual trend in bio-inspired optimization is to re-iterate the existing knowledge in a different form. The aim of this paper is to fill this gap. More precisely, we start first by highlighting new examples for this problem by considering and describing the concepts of chunking and cooperative learning. Second, by considering particle swarm optimization (PSO), we present a novel bridge between these two notions adapted to the problem of feature selection. In the experiments, we investigate the practical importance of our approach while exploring both its strength and limitations. The results indicate that the approach is mainly suitable for large datasets, and that further research is needed to improve the computational efficiency of the approach and to ensure the independence of the sub-problems defined using chunking.

Sign in / Sign up

Export Citation Format

Share Document