检索结果-南通市图书馆

Approach of hybrid soft computing for agricultural data classification

International Journal of agricultural and Biological Engineering 2015年第6期8卷 54-61页

作者： Shi Lei Duan Qiguo Si Haiping Qiao Hongbo Zhang Juanjuan Ma Xinming College of Information and Management Science Henan Agricultural UniversityZhengzhou 450002China Collaborative Innovation Center of Henan Grain Crops Zhengzhou 450002China Zhengzhou Commodity Exchange Zhengzhou 450008China

Soft computing is an important computational paradigm,and it provides the capability of flexible information processing to solve real world *** data classification is one of the important applications of computing technologies in agriculture,and it has become a hot topic because of the enormous growth of agricultural data *** vector machine is a powerful soft computing technique and it realizes the idea of structural risk minimization principle to find a partition hyperplane that can satisfy the class *** set theory is another famous soft computing technique to deal with vague and uncertain *** learning is an effective method to learn multiple learners and combine their decisions for achieving much higher prediction *** this study,the support vector machine,rough set and ensemble learning were incorporated to construct a hybrid soft computing approach to classify the agricultural *** experimental evaluation of different methods was conducted on public agricultural *** experimental results indicated that the proposed algorithm improves the performance of classification effectively.

关键词： agricultural data soft computing rough set support vector machine ensemble learning classification

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Thematic harvesting of agricultural resources from generic repositories

引用

Information Processing in Agriculture 2015年第2期2卷 93-100页

作者： Devika P.Madalli Documentation Research and Training Center(DRTC)Indian Statistical Institute(ISI) 560059India

Metadata aggregators and service providers harvest entire collections or they restrict harvesting by date or *** most often user approach to collections is not by dates or set names but by domain based *** by domains is an issue when service providers attempt to collect data from multiple *** main problem is that harvesters,at present,do not have the facility to distinguish themes such as *** the present work,an attempt has been through Tharvest,a thematic harvester model using the proposed methodology harvesting agricultural resources from generic *** encompasses a process where technical terms of the domain of agriculture are taken from AGROVOC,a multilingual,structured controlled vocabulary designed to cover concepts and terminologies in the agriculture *** is deployed to provide the basis for selective *** system components and workflows are presented and *** aggregators provide end-users a single platform discovery facility to resources collected from various data *** is observed that aggregators such as INDUS[***/***/indus]dealing with agriculture and related domains facilitate aggregating metadata from not only repositories but also other sources such as journals and enable a centralized access to full text and *** harvesting can be fairly simple and straight forward,it is not without its *** paper intends to highlight some of the issues in harvesting metadata in agricultural *** particular focus is to identify agriculture related metadata from generic sets.

关键词： Thematic harvesting agricultural data Issues in harvesting

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Yield performance estimation of corn hybrids using machine learning algorithms

引用

Artificial Intelligence in Agriculture 2021年第1期5卷 82-89页

作者： Farnaz Babaie Sarijaloo Michele Porta Bijan Taslimi Panos M.Pardalos Department of Industrial and Systems Engineering University of FloridaGainesvilleFLUSA Department of Computer Engineering University of ParmaParmaItaly

Estimation of yield performance for crop products is a topic of interest in *** breeding programs,we cannot test all possible hybrids created by crossing two parents(inbred and tester)since it would be too time consuming and *** this paper,we exploit different machine learning algorithms including decision tree,gradient boosting machine,random forest,adaptive boosting,XGBoost and neural network to predict the yield of corn hybrids using data provided in the 2020 Syngenta Crop *** participants were asked to predict the yield of missing hybrids which were not tested *** results show that the prediction obtained by XGBoost is more accurate than other models with a root mean square error equal to ***,we use XGBoost model to estimate the yield performance for untested combinations of inbreds and *** this approach,we identify hybrids with high predicted yield that can be bred to increase corn production.

关键词： Yield prediction data analysis Corn hybrids Machine learning agricultural data

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：