International Journal of Advanced Research in Artificial Intelligence最新文献_第5页

Enterprise Architecture Model that Enables to Search for Patterns of Statistical Information 支持搜索统计信息模式的企业架构模型

International Journal of Advanced Research in Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.14569/IJARAI.2013.020601

O. Chertov

引用次数: 2

Discrimination Method between Prolate and Oblate Shapes of Leaves Based on Polarization Characteristics Measured with Polarization Film Attached Cameras 基于偏振膜附加相机偏振特性的叶片长形与扁形判别方法

International Journal of Advanced Research in Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.14569/IJARAI.2013.021203

K. Arai

引用次数: 0

Students’ Weakness Detective in Traditional Class 传统课堂中学生弱点的发现

International Journal of Advanced Research in Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.14569/IJARAI.2016.050604

Fatimah Altuhaifa

引用次数: 1

Scale-Based Local Feature Selection for Scene Text Recognition 基于尺度的场景文本识别局部特征选择

International Journal of Advanced Research in Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.14569/IJARAI.2014.030403

Boyu Zhang, Jia Liu, Xianglong Tang

引用次数: 1

Error Analysis of Line of Sight Estimation using Purkinje Images for Eye-based Human-Computer Interaction: HCI 基于眼睛的人机交互浦肯野图像的视线估计误差分析

International Journal of Advanced Research in Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.14569/IJARAI.2016.051003

K. Arai

引用次数: 2

A Trust-based Mechanism for Avoiding Liars in Referring of Reputation in Multiagent System 基于信任的多智能体信誉规避机制

International Journal of Advanced Research in Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.14569/IJARAI.2015.040205

M. Nguyen, Dinh Que Tran

{"title":"A Trust-based Mechanism for Avoiding Liars in Referring of Reputation in Multiagent System","authors":"M. Nguyen, Dinh Que Tran","doi":"10.14569/IJARAI.2015.040205","DOIUrl":"https://doi.org/10.14569/IJARAI.2015.040205","url":null,"abstract":"Trust is considered as the crucial factor for agents in decision making to choose the most trustworthy partner during their interaction in open distributed multiagent systems. Most current trust models are the combination of experience trust and reference trust, in which the reference trust is estimated from the judgements of agents in the community about a given partner. These models are based on the assumption that all agents are reliable when they share their judgements about a given partner to the others. However, these models are no more longer appropriate to applications of multiagent systems, where several concurrent agents may not be ready to share their private judgement about others or may share the wrong data by lying to their partners.\u0000In this paper, we introduce a combination model of experience trust and experience trust with a mechanism to enable agents take into account the trustworthiness of referees when they refer their judgement about a given partner. We conduct experiments to evaluate the proposed model in the context of the e-commerce environment. Our research results suggest that it is better to take into account the trustworthiness of referees when they share their judgement about partners. The experimental results also indicate that although there are liars in the multiagent systems, combination trust computation is better than the trust computation based only on the experience trust of agents.","PeriodicalId":323606,"journal":{"name":"International Journal of Advanced Research in Artificial Intelligence","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124090717","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

Rough Approximations for Incomplete Information 不完全信息的粗略近似

International Journal of Advanced Research in Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.14569/IJARAI.2014.031202

Jun Luo, K. Qin

引用次数: 1

Estimation of Rice Crop Quality and Harvest Amount from Helicopter Mounted NIR Camera Data and Remote Sensing Satellite Data 利用直升机近红外相机数据和遥感卫星数据估算水稻作物品质和收成

International Journal of Advanced Research in Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.14569/IJARAI.2015.041003

K. Arai, Masanoori Sakashita, Osamu Shigetomi, Yuko Miura

{"title":"Estimation of Rice Crop Quality and Harvest Amount from Helicopter Mounted NIR Camera Data and Remote Sensing Satellite Data","authors":"K. Arai, Masanoori Sakashita, Osamu Shigetomi, Yuko Miura","doi":"10.14569/IJARAI.2015.041003","DOIUrl":"https://doi.org/10.14569/IJARAI.2015.041003","url":null,"abstract":"Estimation of rice crop quality and harvest amount in paddy fields with the different rice stump density derived from helicopter mounted NIR camera and remote sensing satellite data is made. Using the intensive study site of rice paddy fields with managing, estimation of protein content in rice crop and nitrogen content in rice leaves through regression analysis with Normalized Difference Vegetation Index: NDVI derived from camera mounted on a radio-control helicopter is made together with harvest amount of rice crops. Through experiments at rice paddy fields which is situated at Saga Prefectural Agriculture Research Institute SPRIA in Saga city, Japan, it is found that protein content in rice crops is highly correlated with NDVI which is acquired with visible and Near Infrared: NIR camera mounted on radio-control helicopter. It also is found that nitrogen content in rice leaves is correlated to NDVI as well. Protein content in rice crop is negatively proportional to rice taste. Therefore rice crop quality can be evaluated through NDVI observation of rice paddy field.","PeriodicalId":323606,"journal":{"name":"International Journal of Advanced Research in Artificial Intelligence","volume":"206 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128677565","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: 6

CBR in the service of accident cases evaluating 案例推理在事故案例评价中的应用

International Journal of Advanced Research in Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.14569/IJARAI.2013.020101

L. Mejri, Sofian Madi, H. Ghézala

{"title":"CBR in the service of accident cases evaluating","authors":"L. Mejri, Sofian Madi, H. Ghézala","doi":"10.14569/IJARAI.2013.020101","DOIUrl":"https://doi.org/10.14569/IJARAI.2013.020101","url":null,"abstract":"This paper introduces a research aiming at the development of a decision support system concerning the approval of automated railway transportation systems. The objective is to implement a valuation method for the degree of compliance of the automated transportation system in-group of safety standards by the analysis of the scenarios of accident. To reach this target, we envisaged an approach Rex (Return of experience) who draws the lessons of accidents / incidents lived and/or imagined by the experts of the analysis of security in the IFSTAAR. Our approach consists in offering a decision support in the side of the experts of the certification based on a reuse of the scenarios of accidents already validated historically on other approved transportation systems. This approach Rex is very useful since it provides to the experts a class of scenarios of accidents similar to the new case treated and getting closer to the context of new case. The Case-based reasoning is then exploited as a mode of reasoning by analogy allowing to choose and to recollect one under group of historical cases that can help in the resolution of the new case introduced by the experts. Process-Oriented Case-Based Reasoning (PO-CBR) is a growing application area in which CBR is used to address problems involving process data in a variety of specialized domains. PO-CBR systems often use structured cases. Our approach is characterized by a two-phased retrieval strategy. A first phase consists in retrieving a set of cases to be considered (a class of cases most similar to a problem to resolve). In a second phase, a more fine grained strategy is then applied to the pool of candidate cases already selected by the mean of similarity measures. This approach can enhance the process of retrieving cases compared to an exhaustive case-by-case comparison.","PeriodicalId":323606,"journal":{"name":"International Journal of Advanced Research in Artificial Intelligence","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129551036","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: 0

A More Intelligent Literature Search 更智能的文献检索

International Journal of Advanced Research in Artificial Intelligence Pub Date : 1900-01-01 DOI: 10.14569/IJARAI.2014.030701

M. G. King, Alison Van Bree

引用次数: 1