智能学习系统与应用(英文)最新文献_第10页

Automatic Classification of Unstructured Blog Text 非结构化博客文本的自动分类

智能学习系统与应用(英文) Pub Date : 2013-05-20 DOI: 10.4236/JILSA.2013.52012

M. K. Dalal, M. Zaveri

引用次数: 13

A Novel Stochastic Framework for the Optimal Placement and Sizing of Distribution Static Compensator 分布静态补偿器最优布局和尺寸的一种新的随机框架

智能学习系统与应用(英文) Pub Date : 2013-05-20 DOI: 10.4236/JILSA.2013.52010

Reza Khorram-Nia, Aliasghar Baziar, A. Kavousi-fard

引用次数: 16

Attention-Guided Organized Perception and Learning of Object Categories Based on Probabilistic Latent Variable Models 基于概率潜变量模型的注意引导有组织的对象类别感知和学习

智能学习系统与应用(英文) Pub Date : 2013-05-20 DOI: 10.4236/JILSA.2013.52014

M. Atsumi

{"title":"Attention-Guided Organized Perception and Learning of Object Categories Based on Probabilistic Latent Variable Models","authors":"M. Atsumi","doi":"10.4236/JILSA.2013.52014","DOIUrl":"https://doi.org/10.4236/JILSA.2013.52014","url":null,"abstract":"This paper proposes a probabilistic model of object category learning in conjunction with attention-guided organized perception. This model consists of a model of attention-guided organized perception of object segments on Markov random fields and a model of learning object categories based on a probabilistic latent component analysis. In attention guided organized perception, concurrent figure-ground segmentation is performed on dynamically-formed Markov random fields around salient preattentive points and co-occurring segments are grouped in the neighborhood of selective attended segments. In object category learning, a set of classes of each object category is obtained based on the probabilistic latent component analysis with the variable number of classes from bags of features of segments extracted from images which contain the categorical objects in context and an object category is represented by a composite of object classes. Through experiments using two image data sets, it is shown that the model learns a probabilistic structure of intra-categorical composition and inter-categorical difference of object categories and achieves high performance in object category recognition.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70329680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

The Role of Rare Terms in Enhancing the Performance of Polynomial Networks Based Text Categorization 稀有项在提高基于多项式网络的文本分类性能中的作用

智能学习系统与应用(英文) Pub Date : 2013-05-20 DOI: 10.4236/JILSA.2013.52009

Mayy M. Al-Tahrawi

引用次数: 7

Hybrid Methodology for Structural Health Monitoring Based on Immune Algorithms and Symbolic Time Series Analysis 基于免疫算法和符号时间序列分析的结构健康监测混合方法

智能学习系统与应用(英文) Pub Date : 2013-02-22 DOI: 10.4236/JILSA.2013.51006

Rongshuai Li, A. Mita, Jin Zhou

引用次数: 8

Hybrid Intelligent Modeling for Optimizing Welding Process Parameters for Reduced Activation Ferritic-Martensitic (RAFM) Steel 低活化铁素体-马氏体(RAFM)钢焊接工艺参数优化的混合智能建模

智能学习系统与应用(英文) Pub Date : 2013-02-22 DOI: 10.4236/JILSA.2013.51005

C. Neelamegam, Vishnuvardhan Sapineni, V. Muthukumaran, Jayakumar Tamanna

{"title":"Hybrid Intelligent Modeling for Optimizing Welding Process Parameters for Reduced Activation Ferritic-Martensitic (RAFM) Steel","authors":"C. Neelamegam, Vishnuvardhan Sapineni, V. Muthukumaran, Jayakumar Tamanna","doi":"10.4236/JILSA.2013.51005","DOIUrl":"https://doi.org/10.4236/JILSA.2013.51005","url":null,"abstract":"Reduced-activated ferritic-martensitic steels are being considered for use in fusion energy reactor and subsequent fusion power reactor applications. Typically, those reduced activated steels can loose their radioactivity in approximately 100 years, compared to thousands of years for the non-reduced-activated steels. The commonly used welding process for fabricating this steel are electron-beam welding, and tungsten inert gas (TIG) welding. Therefore, Activated-flux tungsten inert gas (A-TIG) welding, a variant of TIG welding has been developed in-house to increase the depth of penetration in single pass welding. In structural materials produced by A-TIG welding process, weld bead width, depth of penetration and heat affected zone (HAZ) width play an important role in determining in mechanical properties and also the performance of the weld joints during service. To obtain the desired weld bead geometry, HAZ width and make a good weld joint, it becomes important to set up the welding process parameters. The current work attempts to develop independent models correlating the welding process parameters like current, voltage and torch speed with weld bead shape will bead shape parameters like depth of penetration, bead width, HAZ width using ANFIS. These models will be used to evaluate the objective function in the genetic algorithm. Then genetic algorithm is employed to determine the optimum A-TIG welding process parameters to obtain the desired weld bead shape parameters and HAZ width.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70329919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

A Novel Self Adaptive Modification Approach Based on Bat Algorithm for Optimal Management of Renewable MG 一种基于Bat算法的自适应修正可再生电网优化管理方法

智能学习系统与应用(英文) Pub Date : 2013-02-22 DOI: 10.4236/JILSA.2013.51002

Aliasghar Baziar, Abdollah Kavoosi-Fard, J. Zare

{"title":"A Novel Self Adaptive Modification Approach Based on Bat Algorithm for Optimal Management of Renewable MG","authors":"Aliasghar Baziar, Abdollah Kavoosi-Fard, J. Zare","doi":"10.4236/JILSA.2013.51002","DOIUrl":"https://doi.org/10.4236/JILSA.2013.51002","url":null,"abstract":"In the new competitive electricity market, the accurate operation management of Micro-Grid (MG) with various types of renewable power sources (RES) can be an effective approach to supply the electrical consumers more reliably and economically. In this regard, this paper proposes a novel solution methodology based on bat algorithm to solve the op- timal energy management of MG including several RESs with the back-up of Fuel Cell (FC), Wind Turbine (WT), Photovoltaics (PV), Micro Turbine (MT) as well as storage devices to meet the energy mismatch. The problem is formulated as a nonlinear constraint optimization problem to minimize the total cost of the grid and RESs, simultaneously. In addition, the problem considers the interactive effects of MG and utility in a 24 hour time interval which would in- crease the complexity of the problem from the optimization point of view more severely. The proposed optimization technique is consisted of a self adaptive modification method compromised of two modification methods based on bat algorithm to explore the total search space globally. The superiority of the proposed method over the other well-known algorithms is demonstrated through a typical renewable MG as the test system.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4236/JILSA.2013.51002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70329714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 50

Genetic Optimization of Artificial Neural Networks to Forecast Virioplankton Abundance from Cytometric Data 利用细胞数据预测浮游生物丰度的人工神经网络遗传优化

智能学习系统与应用(英文) Pub Date : 2013-02-22 DOI: 10.4236/JILSA.2013.51007

G. C. Pereira, Marilia Mitidieri F. Oliveira, N. Ebecken

{"title":"Genetic Optimization of Artificial Neural Networks to Forecast Virioplankton Abundance from Cytometric Data","authors":"G. C. Pereira, Marilia Mitidieri F. Oliveira, N. Ebecken","doi":"10.4236/JILSA.2013.51007","DOIUrl":"https://doi.org/10.4236/JILSA.2013.51007","url":null,"abstract":"Since viruses are able to influence the trophic status and community structure they should be accessed and accounted in ecosystem functioning and management models. So, this work met a set of biological, chemical and physical time series in order to explore the correlations with marine virioplankton community across different trophic gradients. The case studied is the Arraial do Cabo upwelling system, northeast of Rio de Janeiro State in Southeast coast of Brazil. The main goal is to evolve three type of artificial neural network (ANN) by genetic algorithm (GA) optimization to predict virioplankton abundance and dynamic. The input variables range from the abundance of phytoplankton, bacterioplankton and its ratios acquired by one in situ and another ex situ flow cytometers. These data were collected with weekly frequency from August 2006 to June 2007. Our results show viruses being highly correlated to their host, and that GA provided an efficient method of optimizing ANN architectures to predict the virioplankton abundance. The RBF-NN model presented the best performance to an accuracy of 97% for any period in the year. A discussion and ecological interpretations about the system behavior is also provided.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70329976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Training with Input Selection and Testing (TWIST) Algorithm: A Significant Advance in Pattern Recognition Performance of Machine Learning 训练与输入选择和测试(TWIST)算法:机器学习模式识别性能的重大进展

智能学习系统与应用(英文) Pub Date : 2013-02-22 DOI: 10.4236/JILSA.2013.51004

M. Buscema, Marco Breda, W. Lodwick

{"title":"Training with Input Selection and Testing (TWIST) Algorithm: A Significant Advance in Pattern Recognition Performance of Machine Learning","authors":"M. Buscema, Marco Breda, W. Lodwick","doi":"10.4236/JILSA.2013.51004","DOIUrl":"https://doi.org/10.4236/JILSA.2013.51004","url":null,"abstract":"This article shows the efficacy of TWIST, a methodology for the design of training and testing data subsets extracted from given dataset associated with a problem to be solved via ANNs. The methodology we present is embedded in algorithms and actualized in computer software. Our methodology as implemented in software is compared to the current standard methods of random cross validation: 10-Fold CV, random split into two subsets and the more advanced T&T. For each strategy, 13 learning machines, representing different families of the main algorithms, have been trained and tested. All algorithms were implemented using the well-known WEKA software package. On one hand a falsification test with randomly distributed dependent variable has been used to show how T&T and TWIST behaves as the other two strategies: when there is no information available on the datasets they are equivalent. On the other hand, using the real Statlog (Heart) dataset, a strong difference in accuracy is experimentally proved. Our results show that TWIST is superior to current methods. Pairs of subsets with similar probability density functions are generated, without coding noise, according to an optimal strategy that extracts the most useful information for pattern classification.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70329853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 40

LP-SVR Model Selection Using an Inexact Globalized Quasi-Newton Strategy 基于非精确全局拟牛顿策略的LP-SVR模型选择

智能学习系统与应用(英文) Pub Date : 2013-02-22 DOI: 10.4236/JILSA.2013.51003

P. Rivas-Perea, Juan Cota-Ruiz, J. Venzor, D. G. Chaparro, J. Rosiles

引用次数: 6