Adv. Artif. Intell.最新文献_第2页

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":"27 1","pages":"679847:1-679847:12"},"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

Genetic Algorithm Based PID Controller Tuning Approach for Continuous Stirred Tank Reactor 基于遗传算法的连续搅拌槽式反应器PID控制器整定方法

Adv. Artif. Intell. Pub Date : 2014-01-01 DOI: 10.1155/2014/791230

A. Jayachitra, R. Vinodha

引用次数: 124

Physical Violence Detection for Preventing School Bullying 防范校园欺凌的肢体暴力检测

Adv. Artif. Intell. Pub Date : 2014-01-01 DOI: 10.1155/2014/740358

Liang Ye, H. Ferdinando, T. Seppänen, E. Alasaarela

引用次数: 31

An Emotion Detection System Based on Multi Least Squares Twin Support Vector Machine 基于多最小二乘双支持向量机的情感检测系统

Adv. Artif. Intell. Pub Date : 2014-01-01 DOI: 10.1155/2014/282659

Divya Tomar, Divya Ojha, Sonali Agarwal

{"title":"An Emotion Detection System Based on Multi Least Squares Twin Support Vector Machine","authors":"Divya Tomar, Divya Ojha, Sonali Agarwal","doi":"10.1155/2014/282659","DOIUrl":"https://doi.org/10.1155/2014/282659","url":null,"abstract":"Posttraumatic stress disorder (PTSD), bipolar manic disorder (BMD), obsessive compulsive disorder (OCD), depression, and suicide are some major problems existing in civilian and military life. The change in emotion is responsible for such type of diseases. So, it is essential to develop a robust and reliable emotion detection system which is suitable for real world applications. Apart from healthcare, importance of automatically recognizing emotions from human speech has grown with the increasing role of spoken language interfaces in human-computer interaction applications. Detection of emotion in speech can be applied in a variety of situations to allocate limited human resources to clients with the highest levels of distress or need, such as in automated call centers or in a nursing home. In this paper, we used a novelmulti least squares twin support vector machine classifier in order to detect seven different emotions such as anger, happiness, sadness, anxiety, disgust, panic, and neutral emotions. The experimental result indicates better performance of the proposed technique over other existing approaches. The result suggests that the proposed emotion detection system may be used for screening of mental status.","PeriodicalId":7253,"journal":{"name":"Adv. Artif. Intell.","volume":"390 1","pages":"282659:1-282659:11"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80443262","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: 13

Intelligent Control for USV Based on Improved Elman Neural Network with TSK Fuzzy 基于改进Elman神经网络TSK模糊的无人潜航器智能控制

Adv. Artif. Intell. Pub Date : 2014-01-01 DOI: 10.1155/2014/739517

Shang-Jen Chuang, Chiung-Hsing Chen, Chih-Ming Hong, Guan-Yu Chen

{"title":"Intelligent Control for USV Based on Improved Elman Neural Network with TSK Fuzzy","authors":"Shang-Jen Chuang, Chiung-Hsing Chen, Chih-Ming Hong, Guan-Yu Chen","doi":"10.1155/2014/739517","DOIUrl":"https://doi.org/10.1155/2014/739517","url":null,"abstract":"In recent years, based on the rising of global personal safety demand and human resource cost considerations, development of unmanned vehicles to replace manpower requirement to perform high-risk operations is increasing. In order to acquire useful resources under the marine environment, a large boat as an unmanned surface vehicle (USV) was implemented. The USV is equipped with automatic navigation features and a complete substitute artificial manipulation. This USV system for exploring the marine environment has more carrying capacity and that measurement system can also be self-designed through a modular approach in accordance with the needs for various types of environmental conditions. The investigation work becomes more flexible. A catamaran hull is adopted as automatic navigation test with CompactRIO embedded system. Through GPS and direction sensor we not only can know the current location of the boat, but also can calculate the distance with a predetermined position and the angle difference immediately. In this paper, the design of automatic navigation is calculated in accordance with improved Elman neural network (ENN) algorithms. Takagi-Sugeno-Kang (TSK) fuzzy and improved ENN control are applied to adjust required power and steering, which allows the hull to move straight forward to a predetermined target position. The route will be free from outside influence and realize automatic navigation purpose.","PeriodicalId":7253,"journal":{"name":"Adv. Artif. Intell.","volume":"76 1","pages":"739517:1-739517:9"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83665518","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

Hybrid Wavelet-Postfix-GP Model for Rainfall Prediction of Anand Region of India 混合小波-后置- gp模式在印度阿南德地区降雨预报中的应用

Adv. Artif. Intell. Pub Date : 2014-01-01 DOI: 10.1155/2014/717803

V. Dabhi, S. Chaudhary

引用次数: 29

Artificial Neural Network-Based Fault Distance Locator for Double-Circuit Transmission Lines 基于人工神经网络的双回输电线路故障距离定位

Adv. Artif. Intell. Pub Date : 2013-02-07 DOI: 10.1155/2013/271865

Anamika Jain

{"title":"Artificial Neural Network-Based Fault Distance Locator for Double-Circuit Transmission Lines","authors":"Anamika Jain","doi":"10.1155/2013/271865","DOIUrl":"https://doi.org/10.1155/2013/271865","url":null,"abstract":"This paper analyses two different approaches of fault distance location in a double circuit transmission lines, using artificial neural networks. The single and modular artificial neural networks were developed for determining the fault distance location under varying types of faults in both the circuits. The proposed method uses the voltages and currents signals available at only the local end of the line. The model of the example power system is developed using Matlab/Simulink software. Effects of variations in power system parameters, for example, fault inception angle, CT saturation, source strength, its X/R ratios, fault resistance, fault type and distance to fault have been investigated extensively on the performance of the neural network based protection scheme (for all ten faults in both the circuits). Additionally, the effects of network changes: namely, double circuit operation and single circuit operation, have also been considered. Thus, the present work considers the entire range of possible operating conditions, which has not been reported earlier. The comparative results of single and modular neural network indicate that the modular approach gives correct fault location with better accuracy. It is adaptive to variation in power system parameters, network changes and works successfully under a variety of operating conditions.","PeriodicalId":7253,"journal":{"name":"Adv. Artif. Intell.","volume":"18 1","pages":"271865:1-271865:12"},"PeriodicalIF":0.0,"publicationDate":"2013-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86551861","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: 20

Efficacious End User Measures - Part 1: Relative Class Size and End User Problem Domains 有效的最终用户度量-第1部分:相对类大小和最终用户问题域

Adv. Artif. Intell. Pub Date : 2013-01-01 DOI: 10.1155/2013/427958

E. Eiland, L. Liebrock

{"title":"Efficacious End User Measures - Part 1: Relative Class Size and End User Problem Domains","authors":"E. Eiland, L. Liebrock","doi":"10.1155/2013/427958","DOIUrl":"https://doi.org/10.1155/2013/427958","url":null,"abstract":"Biological and medical endeavors are beginning to realize the benefits of artificial intelligence and machine learning. However, classification, prediction, and diagnostic (CPD) errors can cause significant losses, even loss of life. Hence, end users are best served when they have performance information relevant to their needs, this paper's focus. Relative class size (rCS) is commonly recognized as a confounding factor in CPD evaluation. Unfortunately, rCS-invariant measures are not easily mapped to end user conditions. We determine a cause of rCS invariance, joint probability table (JPT) normalization. JPT normalization means that more end user efficacious measures can be used without sacrificing invariance. An important revelation is that without data normalization, the Matthews correlation coefficient (MCC) and information coefficient (IC) are not relative class size invariants; this is a potential source of confusion, as we found not all reports using MCC or IC normalize their data. We derive MCC rCS-invariant expression. JPT normalization can be extended to allow JPT rCS to be set to any desired value (JPT tuning). This makes sensitivity analysis feasible, a benefit to both applied researchers and practitioners (end users). We apply our findings to two published CPD studies to illustrate how end users benefit.","PeriodicalId":7253,"journal":{"name":"Adv. Artif. Intell.","volume":"76 1","pages":"427958:1-427958:22"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83836223","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: 4

A Novel Method for Training an Echo State Network with Feedback-Error Learning 一种基于反馈误差学习的回声状态网络训练新方法

Adv. Artif. Intell. Pub Date : 2013-01-01 DOI: 10.1155/2013/891501

R. A. Løvlid

引用次数: 3