检索结果-南通市图书馆

Evaluating the Impact of prediction techniques: Software Reliability Perspective

Computers, Materials & Continua 2021年第5期67卷 1471-1488页

作者： Kavita Sahu Fahad A.Alzahrani R.K.Srivastava Rajeev Kumar Department of Computer Science Dr.Shakuntala Misra National Rehabilitation UniversityLucknow226017India Department of Computer Engineering College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Application Shri Ramswaroop Memorial UniversityBarabanki225003India Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025India

Maintaining software reliability is the key idea for conducting quality *** can be done by having less complex *** developers and other experts have made signicant efforts in this context,the level of reliability is not the same as it should ***,further research into the most detailed mechanisms for evaluating and increasing software reliability is essential.A signicant aspect of growing the degree of reliable applications is the quantitative assessment of *** are multiple statistical as well as soft computing methods available in literature for predicting reliability of ***,none of these mechanisms are useful for all kinds of failure datasets and *** nding the most optimal model for reliability prediction is an important *** paper suggests a novel method to substantially pick the best model of reliability *** method is the combination of analytic hierarchy method(AHP),hesitant fuzzy(HF)sets and technique for order of preference by similarity to ideal solution(TOPSIS).In addition,using the different iterations of the process,procedural sensitivity was also performed to validate the *** ndings of the software reliability prediction models prioritization will help the developers to estimate reliability prediction based on the software type.

关键词： Software reliability reliability prediction prediction techniques hesitant-fuzzy-AHP hesitant-fuzzy-TOPSIS

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

A prediction technique for single-event effects on complex integrated circuits

引用

Journal of Semiconductors 2015年第11期36卷 80-84页

作者：赵元富于春青范隆岳素格陈茂鑫杜守刚郑宏超 Beijing Microelectronics Technology Institute Beijing University of Aeronautics & Astronautics

The sensitivity of complex integrated circuits to single-event effects is investigated. Sensitivity depends not only on the cross section of physical modules but also on the behavior of data patterns running on the system.A method dividing the main functional modules is proposed. The intrinsic cross section and the duty cycles of different sensitive modules are obtained during the execution of data patterns. A method for extracting the duty cycle is presented and a set of test patterns with different duty cycles are implemented experimentally. By combining the intrinsic cross section and the duty cycle of different sensitive modules, a universal method to predict SEE sensitivities of different test patterns is proposed, which is verified by experiments based on the target circuit of a microprocessor. Experimental results show that the deviation between prediction and experiment is less than 20%.

关键词： complex ICs duty cycle prediction of cross section prediction techniques

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Improving Churn prediction in Telecommunications using Complementary Fusion of Multilayer Features based on Factorization and Construction

Improving Churn Prediction in Telecommunications using Compl...

引用

第26届中国控制与决策会议

作者： Qiuhua Shen Hong Li Qin Liao Wei Zhang KONE KALILOU School of Information Science and Engineering Central South University School Of Architecture Hunan University

ISBN: (纸本)9781479937097

High dimensional and unbalanced datasets are the main problems which prevent from achieving ideally churn prediction performance. Features selection is necessary to be adopted to enhance the model performance. A new predicting framework is proposed in this paper which uses complementary fusion of the multilayer features. Several subsets and new features were acquired according to feature factorization and feature construction respectively. The effective features were selected by multilayer complementary fusion which according to the contribution of feature subsets and new features. In this way, the imbalance defects of class distributions can be fixed, prediction accuracy can be improved and system stability can be reinforced. Five data mining models were applied in customer churn. Experimental results demonstrated that the method we proposed could preferably overcome the inelasticity of traditional feature selection algorithms, and more effective than those existing methods in telecommunications industry. Furthermore, we found optimal fusion with prediction model for customer churn prediction in telecommunications industry through exploring the advantages and limitations of each feature subset and prediction techniques.

关键词： Customer Churn prediction prediction techniques Feature Selection Complementary Fusion Feature Factorization Feature Construction

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

Application of Support Vector Machine in Ecological Economy Forecasting

Application of Support Vector Machine in Ecological Economy ...

引用

2010 3rd IEEE International Conference on Computer Science and Information Technology—ICCSIT 2010

作者： Liu Hui 61081 troopses Chinese People’s Liberation Army Beijing 100094 China Kong Ling-fang Biological Practical Vocational Institute of Shanxi Taiyuan 030031 China

In the paper,ecological economy forecasting based on support vector machine is *** ecological economy forecasting is the forecasting of the three energy indices:self-sufficient rate of energy,environment load rate and production rate of pure energy,so the three energy indices are predicted *** experimental data of the three energy indices:self-sufficient rate of energy,environment load rate and production rate of pure energy are collected,and support vector machine is employed to predict three energy *** testing results show that the ecological economy forecasting by support vector machine is feasible.

关键词： support vector machine regional economies forecasting prediction techniques

来源： cnki会议评论

在线全文

cnki会议

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

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

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：