检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

237 篇 会议
14 册 图书
6 篇 期刊文献

馆藏范围

257 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

76 篇 工学
- 69 篇 计算机科学与技术...
- 22 篇 电气工程
- 20 篇 软件工程
- 7 篇 控制科学与工程
- 6 篇 信息与通信工程
- 4 篇 化学工程与技术
- 2 篇 机械工程
- 2 篇 生物工程
- 2 篇 网络空间安全
- 1 篇 光学工程
- 1 篇 仪器科学与技术
- 1 篇 材料科学与工程（可...
- 1 篇 建筑学
- 1 篇 土木工程
- 1 篇 交通运输工程
- 1 篇 生物医学工程（可授...
- 1 篇 安全科学与工程
15 篇 理学
- 6 篇 数学
- 4 篇 化学
- 3 篇 系统科学
- 2 篇 物理学
- 2 篇 生物学
- 2 篇 统计学（可授理学、...
9 篇 管理学
- 7 篇 图书情报与档案管...
- 2 篇 管理科学与工程(可...
- 1 篇 工商管理
1 篇 法学
- 1 篇 社会学
1 篇 医学
- 1 篇 基础医学(可授医学...
- 1 篇 临床医学
1 篇 艺术学
- 1 篇 设计学（可授艺术学...

主题

160 篇 pattern recognit...
33 篇 testing
29 篇 data mining
26 篇 constraint optim...
26 篇 feature extracti...
25 篇 printing
25 篇 design optimizat...
25 篇 containers
25 篇 integer linear p...
23 篇 computer applica...
18 篇 image segmentati...
18 篇 laboratories
18 篇 shape
14 篇 clustering algor...
13 篇 computer science
13 篇 information scie...
13 篇 training
12 篇 computational mo...
11 篇 particle swarm o...
11 篇 iterative algori...

机构

4 篇 thapar institute...
3 篇 school of artifi...
2 篇 department of co...
2 篇 faculty of compu...
2 篇 univ cincinnati ...
2 篇 division of grad...
2 篇 center for soft ...
2 篇 soft computing r...
2 篇 toyama univ fac ...
2 篇 inst signals sys...
2 篇 universiti tekni...
2 篇 department of da...
2 篇 computer science...
2 篇 univ teknol mala...
2 篇 school of engine...
2 篇 institut de rech...
2 篇 university of ji...
2 篇 department of in...
2 篇 inria rennes
2 篇 univ w florida d...

作者

16 篇 ajith abraham
9 篇 shamsuddin siti ...
7 篇 siti mariyam sha...
4 篇 azlinah mohamed
4 篇 niketa gandhi
4 篇 anu bajaj
3 篇 jun zhang
3 篇 teh ying wah
3 篇 václav snášel
3 篇 muda azah kamila...
3 篇 azah kamilah mud...
3 篇 henri prade
3 篇 ralescu anca
3 篇 abraham ajith
2 篇 yoichi motomura
2 篇 anne laurent
2 篇 asif asifuzzaman
2 篇 juan m. corchado
2 篇 sledge isaac j.
2 篇 muzaffar muhamma...

语言

244 篇 英文
10 篇 其他
3 篇 中文

检索条件"任意字段=International Conference on Soft Computing and Pattern Recognition, SoCPaR 2009"

共 257 条记录，以下是21-30 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Proceedings of the eighth international conference on soft computing and pattern recognition (socpar 2016)

引用

丛书名： Advances in intelligent systems and computing 614

2017年

作者： Abraham Ajith Cherukuri Aswani Kumar Madureira Ana Maria Muda Azah Kamilah

ISBN: (纸本)9783319606187;3319606182;9783319606170

This volume presents 70 carefully selected papers from a major joint event: the 8th international conference on soft computing and pattern recognition (socpar 2016) and the 8th international conference on Computational Aspects of Social Networks (CASoN 2016). socparCASoN 2016, which was organized by the Machine Intelligence Research Labs (MIR Labs), USA and Vellore Institute of Technology (VIT), India and held at the VIT on December 1921, 2016. It brings together researchers and practitioners from academia and industry to share their experiences and exchange new ideas on all interdisciplinary areas of soft computing and pattern recognition, as well as intelligent methods applied to social networks. This book is a valuable resource for practicing engineers/scientists and researchers working in the field of soft computing, pattern recognition and social networks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Student Performance Prediction Analysis Using Neural Networks 15th

Student Performance Prediction Analysis Using Neural Network...

引用

15th international conference on soft computing and pattern recognition, socpar 2023 and 14th World Congress on Nature and Biologically Inspired computing, NaBIC 2023

作者： Prashanth, Mallellu Sai Uma Maheswari, V. Aluvalu, Rajinikanth Prasad Kantipudi, M.V.V. Symbiosis Institute of Technology Hyderabad Campus Symbiosis International University Pune India Department of Computer Science and Engineering Chaitanya Bharathi Institute of Technology Hyderabad India Symbiosis Institute of Technology Pune Campus Symbiosis International University Pune India

ISBN: (纸本)9783031810824

This research paper presents a comprehensive analysis of student performance based on a merged dataset from two subjects: Mathematics and Portuguese. The dataset encompasses a wide range of student attributes and behaviours, allowing us to explore various factors influencing academic success. The study employs exploratory data analysis, data visualization, statistical tests, and machine learning techniques to uncover patterns and relationships within the data. The analysis begins with data preprocessing, including column renaming, categorical variable creation, and merging of datasets. Visualizations such as count plots, heatmaps, and distribution plots are utilized to understand the distribution of final grades and correlations between attributes. Furthermore, the study investigates the impact of romantic status, weekend alcohol consumption, parental education, social activities, desire for higher education, and urban/rural living areas on student performance. Chi-square tests for association are conducted to assess the significance of relationships between categorical variables and final grades. Machine learning models, including Decision Trees, Random Forests, Support Vector Machines, Logistic Regression, AdaBoost, and Stochastic Gradient Descent, are employed to predict student performance. Feature selection techniques are also employed to determine the optimal number of features for achieving high prediction accuracy. Through this comprehensive analysis, we gain insights into the complex interplay of various factors affecting student performance. The findings contribute to a deeper understanding of academic success and highlight potential areas for intervention and improvement. This research serves as a valuable resource for educators, policymakers, and researchers seeking to enhance educational outcomes and facilitate targeted interventions for students. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Face Identification with Feature Learning Using Quasilinear Partial Differential Equation

Face Identification with Feature Learning Using Quasilinear ...

引用

15th international conference on soft computing and pattern recognition, socpar 2023 and 14th World Congress on Nature and Biologically Inspired computing, NaBIC 2023

作者： Muthukumaran, V. Satheesh Kumar, S. Radhika, E.K. Arpana, G.K. Nalini, R. Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Chennai India Department of Computer Science School of Applied Sciences REVA University Bangalore India Department of Computer Science Sindhi College Bangalore India Department of ECE East West College of Engineering Bangalore India

ISBN: (纸本)9783031810855

This study suggests a novel soft computing approach for enhancing face recognition performance using the feature learning methodology. The suggested system of Quasi-linear Partial Differential Equations (QPDE) based face recognition model is used to increase the accuracy of facial identification. The webcam first catches the user's image and saves it to the user's computer. The inference model receives the captured image. The input image is pre-processed to enhance the image, and then the image is split into numerous integral images at the inference model. Using speed-up robust features, an intriguing point is constructed for each integral image. The computed interest point is converted into a QPDE based weight matrix by representing the strength of features at all the regions of the face. With the generated weighted matrix of features extracted from the facial image, the method generates a Fast Artificial intelligence (AI) network with many layers. Each layer of the neural network has many neurons with dedicated functions to compute the similarity and feature weight using QPDE. The proposed approach has produced efficient results compared to earlier methods for the Flickr-Faces-HQ database (FFHQ) datasets. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： soft computing

来源：评论

学校读者我要写书评

暂无评论

Customized hidden layered ann based pattern recognition technique for differential protection of power transformer 11th

Customized hidden layered ann based pattern recognition tech...

引用

11th international conference on soft computing and pattern recognition, socpar 2019, and 11th World Congress on Nature and Biologically Inspired computing, NaBIC 2019

作者： Balaga, Harish Marrapu, Deepthi Vardhaman College of Engineering Hyderabad India

ISBN: (纸本)9783030493448

This article presents the use of Customized Multi-Layer ANN based pattern recognition Technique for the numerical differential protection of a power transformer. An efficient Resilient Back Propagation trained neural network model with customized parallel hidden layers is proposed for the said purpose. The task of the ANN is to discriminate among various operating conditions of the transformer and issue trip signal, only in the case of internal fault. The data base required for the training of algorithm is obtained by using MATLAB/SIMULINK environment. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Power transformers

来源：评论

学校读者我要写书评

暂无评论

A Framework for Recommending Products to Solve Cold Starts Problem Using FP Growth Algorithm

A Framework for Recommending Products to Solve Cold Starts P...

引用

15th international conference on soft computing and pattern recognition, socpar 2023 and 14th World Congress on Nature and Biologically Inspired computing, NaBIC 2023

作者： Dani, Virendra Bhati, Nisha Nagar, Sneha Mandloi, Ayesha Matkar, Mayank Department of Computer Science and Engineering Shri Vaishnav Vidyapeeth Vishwavidyalaya Indore India Department of Computer Science and Engineering Medicaps University Indore India Department of Electronics and Communication Engineering Indore Institute of Science & Technology Indore India Department of Computer Science and Engineering SKITM-Technical Campus Indore India

ISBN: (纸本)9783031889912

Different product characteristics and consumer expectations must be analyzed when making a product or service recommendation based on use. However, if all types of knowledge are inaccessible, this is known as the clod start problem in a recommendation system. To explain and address the issue of cold start, this paper suggests a structure for user experience-based product recommendation. As a result, this paper introduces a four-phase recommendation scheme. In the first step, site usage data is preprocessed and used to make product recommendations. The frequent pattern-based recommendation is performed in the next step. The decision is made in the third process based on the user's current search (user click streams) and related user habits seen in network access logs. In addition, the final recommendation is based on filtering the results obtained in the third step, as well as the product or service's cost, brand, and social review. The results show that the prediction is accurate and precise. Furthermore, compared result of proposed system to traditional system using Apriori Algorithm. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Apriori cold start problem Data Mining frequent pattern k-NN Prediction Recommendation System Web Log

来源：评论

学校读者我要写书评

暂无评论

Detecting Cyber Bullying in the Social Media Using Deep Learning Algorithms

Detecting Cyber Bullying in the Social Media Using Deep Lear...

引用

15th international conference on soft computing and pattern recognition, socpar 2023 and 14th World Congress on Nature and Biologically Inspired computing, NaBIC 2023

作者： Mridul, Aunik Hasan Ahsan, Nowreen Sultana, Zakia Asif, Asifuzzaman Computer Science and Engineering Daffodil International University Dhaka Bangladesh Department of Data Science Clarkson University New York United States Computer Science and Engineering Lovely Professional University Punjab India

ISBN: (纸本)9783031810824

Cyberbullying is a pressing issue in the digital age, especially in non-English-speaking communities. This study focuses on using deep learning techniques to detect cyberbullying in the Bangla language. The research employs a Bangla dataset that includes both cyberbullying and non-cyberbullying text, which undergoes preprocessing, tokenization, and sequence transformation for input into a LSTM recurrent neural network. The LSTM model incorporates word embedding and dropout techniques to enhance its performance. Evaluation metrics like accuracy and AUC-ROC score are employed to assess the model's effectiveness. The study investigates many methods, such as vernacular-specific preparation and data augmenting, that are specifically designed for the identification of cyberbullying in the Bangla language. The findings demonstrate deep learning's capacity to identify cyberbullying in Bangla, which makes a significant contribution to resolving this problem in non-English settings. The research reveals impressive accuracy rates, with LSTM achieving 99.99% accuracy, and a different approach, Convolutional Neural Network (CNN), yielding 99.022%. Ensemble models, including Gradient Boosting, XGBoost, and Random Forest, are also employed and optimized using hyperparameter tuning. Notably, LSTM stands out as the most reliable classifier for cyberbullying detection, as confirmed by the experimental findings and recent research. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Random forests

来源：评论

学校读者我要写书评

暂无评论

Effective Early Hypothyroid Disease Prediction Using Traditional and Ensemble Machine Learning Algorithms 15th

Effective Early Hypothyroid Disease Prediction Using Traditi...

引用

15th international conference on soft computing and pattern recognition, socpar 2023 and 14th World Congress on Nature and Biologically Inspired computing, NaBIC 2023

作者： Mridul, Aunik Hasan Ahsan, Nowreen Saleh, Md. Abu Asif, Asifuzzaman Afrose, Sonia Computer Science and Engineering Daffodil International University Dhaka Bangladesh Department of Data Science Clarkson University New York United States Computer Science and Engineering Lovely Professional University Punjab India Nutrition and Food Engineering Daffodil International University Dhaka Bangladesh

ISBN: (纸本)9783031810794

In recent years, there has been a noticeable rise in the prevalence of physical ailments, most notably hypothyroidism, a condition that has garnered substantial attention due to its substantial impact on a significant portion of the population. To gain a comprehensive understanding of the disease’s severity, distinguishing between standard and affected diagnostic reports is imperative. In this work, we suggest using algorithmic models to facilitate early identification and increase knowledge of possible health hazards linked to hypothyroidism. Our approach is straightforward and well-suited for the prediction of uncomplicated cases of hypothyroid illness in real-world scenarios. Our dataset, sourced from Kaggle, served as the foundation for our research, which involved the utilization of a variety of classifiers, including RF, LR, GB, KN, ABC, DT, GS, and ensemble techniques. The DT classifier proved to be the most accurate, with an astounding accuracy rate of 98.278%. The findings were quite successful. In addition, the accuracy of the Voting Classifier RDGL was 97.218%, while the Stacking Classifier RDAS demonstrated an accuracy of 97.483%. Our optimization efforts, which included hyperparameter tuning, further enhanced the performance of each classifier. Based on extensive experimentation and a review of contemporary research, our findings unequivocally endorse the Decision Tree (DT) boosting classifier as exceptionally proficient, demonstrating a remarkable accuracy rate of 98.278% in the precise prediction of hypothyroid disease. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Bagging Boosting Ensemble Hypothyroidism

来源：评论

学校读者我要写书评

暂无评论

Comparison of global prevalence of sleep disorders in intellectually normal v/s intellectually disabled: A review 11th

Comparison of global prevalence of sleep disorders in intell...

引用

11th international conference on soft computing and pattern recognition, socpar 2019, and 11th World Congress on Nature and Biologically Inspired computing, NaBIC 2019

作者： Irani, Nushafreen Gandhi, Niketa Deshmukh, Sanjay Deshpande, Abhijit Department of Life Sciences University of Mumbai MumbaiMaharashtra400 098 India International Institute of Sleep Sciences ThaneMaharashtra400602 India

ISBN: (纸本)9783030493448

Sleep is not given due importance unless one suffers from any one type of a sleep disorder. The current paper reviews the prevalence of sleep disorders. There is very low awareness about sleep disorders and their disastrous consequences in the Indian population. These consequences include impairment in physical, psychological and lack of neurodevelopment progress. Common methods to assess sleep disorders prevalence in large population groups have been discussed. This review also includes a special mention of sleep disorders in the intellectually disabled population. Our review finds that the prevalence of sleep disorders in this population is significantly high and comparable to the normal population. Sleep issues in intellectually disabled population present dual consequences. Not only sleep issues hamper the growth of persons suffering but unfortunately even the caregivers are also affected by this issue. Sleep disorders in the mentally challenged population are less studied since the person suffering has difficulty in reporting it. Our literature review reveals the fact that sleep issues are prevalent globally and they especially affect the intellectually disabled population. The review also discusses ancient history on sleep & intellectually disabled population. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Sleep research

来源：评论

学校读者我要写书评

暂无评论

soft Feature Based Personal recognition 8th

Soft Feature Based Personal Recognition

引用

8th international conference on soft computing and pattern recognition (socpar) / 8th international conference on Computational Aspects of Social Networks (CASoN)

作者： Kulkarni, Sujata Raut, Ranjana Bhosle, Udhav RSTM Univ Nagpur Yeshwantrao Chavan Coll Engn Nagpur 441110 Maharashtra India SGM Univ Amaravati Elect Dept Amaravati 441110 India Univ Mumbai Rajiv Gandhi Inst Technol Bombay Maharashtra India

ISBN: (纸本)9783319606187;9783319606170

Biometric based personal recognition has become the integral part for administrate and operational aspects for private and government sector. This paper proposed the soft feature based personal recognition by integration of unique and non-unique or soft features to improve the performance of biometrics recognition system. The proposed biometrics recognition system uses unique features of back surface of finger called finger knuckle (FK) and complementary features known as soft features such as age and gender of each individual. Further author presents combination Walsh wavelet Transform based finger knuckle features and soft features at score level using Bayes formula. The algorithm is tested on own FK database and results demonstrated that performance of primary FK recognition system has improved by integrating soft features of same traits. Error Equal Rate (EER) of integrated biometrics is 6.5% which is less as compared to primary.

关键词： Primary biometrics Unique feature soft feature Walsh wavelet transform Bayes formula

来源：评论

学校读者我要写书评

暂无评论

Applicability of soft computing and Optimization Algorithms in software Testing and Metrics - A Brief Review 8th

Applicability of Soft Computing and Optimization Algorithms ...

引用

8th international conference on soft computing and pattern recognition (socpar) / 8th international conference on Computational Aspects of Social Networks (CASoN)

作者： Sharma, Deepak Chandra, Pravin Guru Gobind Singh Indraprastha Univ Univ Sch Informat & Commun Technol Delhi 110078 India

ISBN: (纸本)9783319606187;9783319606170

In spite of many years of work by scientists and specialists on various software qualities, testing stays one of the most broadly honed and concentrated on methodologies for evaluating and improving software quality. Our objective, in this paper, is to present how optimization techniques provide solutions to different and difficult issues in different areas of software engineering. Optimization algorithms are mathematical procedures, which intends to best optimal results for the defect, fault, failure to accomplish tractability, strength, and low arrangement cost. In this paper, a comprehensive overview of software testing and metrics based on soft computing and optimization techniques is presented. In this survey, we try to explain some major problems like defect prediction, software fault prediction and their solutions by soft computing and optimization algorithms. The paper presents an overview of the usage of Mathematical optimization Algorithms and soft computing approaches.

关键词： Optimization algorithms soft computing software testing Metrics software fault prediction

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共26页 << < 1 2 3 4 5 6 7 8 9 10 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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

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：