Adv. Artif. Intell.最新文献_第2页

Design and Implementation of Fuzzy Approximation PI Controller for Automatic Cruise Control System 自动巡航控制系统模糊逼近PI控制器的设计与实现

Adv. Artif. Intell. Pub Date : 2015-01-01 DOI: 10.1155/2015/624638

P. Maji, S. K. Patra, K. Mahapatra

引用次数: 1

Pop-Out: A New Cognitive Model of Visual Attention That Uses Light Level Analysis to Better Mimic the Free-Viewing Task of Static Images 弹出:一种新的视觉注意认知模型，使用光照水平分析来更好地模仿静态图像的自由观看任务

Adv. Artif. Intell. Pub Date : 2015-01-01 DOI: 10.1155/2015/471483

Makiese Mibulumukini

引用次数: 2

A Dirichlet Process Mixture Based Name Origin Clustering and Alignment Model for Transliteration 基于Dirichlet过程混合的人名起源聚类与音译对齐模型

Adv. Artif. Intell. Pub Date : 2015-01-01 DOI: 10.1155/2015/927063

Chunyue Zhang, T. Zhao, Tingting Li

{"title":"A Dirichlet Process Mixture Based Name Origin Clustering and Alignment Model for Transliteration","authors":"Chunyue Zhang, T. Zhao, Tingting Li","doi":"10.1155/2015/927063","DOIUrl":"https://doi.org/10.1155/2015/927063","url":null,"abstract":"In machine transliteration, it is common that the transliterated names in the target language come from multiple language origins. A conventional maximum likelihood based single model can not deal with this issue very well and often suffers from overfitting. In this paper, we exploit a coupled Dirichlet process mixture model (cDPMM) to address overfitting and names multiorigin cluster issues simultaneously in the transliteration sequence alignment step over the name pairs. After the alignment step, the cDPMM clusters name pairs into many groups according to their origin information automatically. In the decoding step, in order to use the learned origin information sufficiently, we use a cluster combination method (CCM) to build clustering-specific transliteration models by combining small clusters into large ones based on the perplexities of name language and transliteration model, which makes sure each origin cluster has enough data for training a transliteration model. On the three different Western-Chinese multiorigin names corpora, the cDPMM outperforms two state-of-the-art baseline models in terms of both the top-1 accuracy and mean F-score, and furthermore the CCM significantly improves the cDPMM.","PeriodicalId":7253,"journal":{"name":"Adv. Artif. Intell.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90825113","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

Adv. Artif. Intell. Pub Date : 2015-01-01 DOI: 10.1155/2015/325703

D. Sengupta, G. Saha

{"title":"Study on Similarity among Indian Languages Using Language Verification Framework","authors":"D. Sengupta, G. Saha","doi":"10.1155/2015/325703","DOIUrl":"https://doi.org/10.1155/2015/325703","url":null,"abstract":"Majority of Indian languages have originated from two language families, namely, Indo-European and Dravidian. Therefore, certain kind of similarity among languages of a particular family can be expected to exist. Also, languages spoken in neighboring regions show certain similarity since there happens to be a lot of intermingling between population of neighboring regions. This paper develops a technique to measure similarity among Indian languages in a novel way, using language verification framework. Four verification systems are designed for each language. Acceptance of one language as another, which relates to false acceptance in language verification framework, is used as a measure of similarity. If language A shows false acceptance more than a predefined threshold with language B, in at least three out of the four systems, then languages A and B are considered to be similar in this work. It is expected that the languages belonging to the same family should manifest their similarity in experimental results. Also, similarity between neighboring languages should be detected through experiments. Any deviation from such fact should be due to specific linguistic or historical reasons. This work analyzes any such scenario.","PeriodicalId":7253,"journal":{"name":"Adv. Artif. Intell.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82170324","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: 22

Wavelet Network: Online Sequential Extreme Learning Machine for Nonlinear Dynamic Systems Identification 小波网络:非线性动态系统辨识的在线顺序极限学习机

Adv. Artif. Intell. Pub Date : 2015-01-01 DOI: 10.1155/2015/184318

D. Salih, S. Noor, M. Marhaban, R. Kamil

引用次数: 6

Two Artificial Neural Networks for Modeling Discrete Survival Time of Censored Data 两种基于人工神经网络的截尾数据离散生存时间建模

Adv. Artif. Intell. Pub Date : 2015-01-01 DOI: 10.1155/2015/270165

Taysseer Sharaf, C. Tsokos

引用次数: 10

Reinforcement Learning in an Environment Synthetically Augmented with Digital Pheromones 数字信息素综合增强环境中的强化学习

Adv. Artif. Intell. Pub Date : 2014-03-13 DOI: 10.1155/2014/932485

Salvador E. Barbosa, Mikel D. Petty

{"title":"Reinforcement Learning in an Environment Synthetically Augmented with Digital Pheromones","authors":"Salvador E. Barbosa, Mikel D. Petty","doi":"10.1155/2014/932485","DOIUrl":"https://doi.org/10.1155/2014/932485","url":null,"abstract":"Reinforcement learning requires information about states, actions, and outcomes as the basis for learning. For many applications, it can be difficult to construct a representative model of the environment, either due to lack of required information or because of that the model's state space may become too large to allow a solution in a reasonable amount of time, using the experience of prior actions. An environment consisting solely of the occurrence or nonoccurrence of specific events attributable to a human actor may appear to lack the necessary structure for the positioning of responding agents in time and space using reinforcement learning. Digital pheromones can be used to synthetically augment such an environment with event sequence information to create a more persistent and measurable imprint on the environment that supports reinforcement learning. We implemented this method and combined it with the ability of agents to learn from actions not taken, a concept known as fictive learning. This approach was tested against the historical sequence of Somali maritime pirate attacks from 2005 to mid-2012, enabling a set of autonomous agents representing naval vessels to successfully respond to an average of 333 of the 899 pirate attacks, outperforming the historical record of 139 successes.","PeriodicalId":7253,"journal":{"name":"Adv. Artif. Intell.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86496280","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: 8

Design of a T Factor Based RBFNC for a Flight Control System 基于T因子的RBFNC飞控系统设计

Adv. Artif. Intell. Pub Date : 2014-01-01 DOI: 10.1155/2014/897691

C. Mohanty, P. S. Khuntia, D. Mitra

引用次数: 5

Estimation of Missing Rainfall Data Using GEP: Case Study of Raja River, Alor Setar, Kedah 利用GEP估算缺失降雨数据:以吉打州Alor Setar Raja河为例

Adv. Artif. Intell. Pub Date : 2014-01-01 DOI: 10.1155/2014/716398

N. Ghani, Z. A. Hasan, T. L. Lau

引用次数: 5

A New Evolutionary-Incremental Framework for Feature Selection 一种新的进化-增量特征选择框架

Adv. Artif. Intell. Pub Date : 2014-01-01 DOI: 10.1155/2014/679847

M. Sigari, Muhammad Reza Pourshahabi, H. Pourreza

{"title":"A New Evolutionary-Incremental Framework for Feature Selection","authors":"M. Sigari, Muhammad Reza Pourshahabi, H. Pourreza","doi":"10.1155/2014/679847","DOIUrl":"https://doi.org/10.1155/2014/679847","url":null,"abstract":"Feature selection is an NP-hard problem from the viewpoint of algorithm design and it is one of the main open problems in pattern recognition. In this paper, we propose a new evolutionary-incremental framework for feature selection.The proposed framework can be applied on an ordinary evolutionary algorithm (EA) such as genetic algorithm (GA) or invasive weed optimization (IWO). This framework proposes some generic modifications on ordinary EAs to be compatible with the variable length of solutions. In this framework, the solutions related to the primary generations have short length.Then, the length of solutions may be increased through generations gradually. In addition, our evolutionary-incremental framework deploys two new operators called addition and deletion operators which change the length of solutions randomly. For evaluation of the proposed framework, we use that for feature selection in the application of face recognition. In this regard, we applied our feature selection method on a robust face recognition algorithm which is based on the extraction of Gabor coefficients. Experimental results show that our proposed evolutionary-incremental framework can select a few number of features from existing thousands features efficiently. Comparison result of the proposed methods with the previous methods shows that our framework is comprehensive, robust, and well-defined to apply on many EAs for feature selection.","PeriodicalId":7253,"journal":{"name":"Adv. Artif. Intell.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80958322","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: 3