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

1,856 篇 会议
6 册 图书
1 篇 期刊文献

馆藏范围

1,863 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,364 篇 工学
- 1,248 篇 计算机科学与技术...
- 997 篇 软件工程
- 318 篇 生物工程
- 309 篇 信息与通信工程
- 189 篇 生物医学工程（可授...
- 160 篇 控制科学与工程
- 124 篇 电气工程
- 118 篇 光学工程
- 83 篇 机械工程
- 74 篇 化学工程与技术
- 64 篇 安全科学与工程
- 62 篇 网络空间安全
- 53 篇 电子科学与技术（可...
- 48 篇 仪器科学与技术
747 篇 理学
- 390 篇 数学
- 326 篇 生物学
- 166 篇 统计学（可授理学、...
- 150 篇 物理学
- 134 篇 系统科学
- 83 篇 化学
440 篇 管理学
- 250 篇 管理科学与工程(可...
- 224 篇 图书情报与档案管...
- 128 篇 工商管理
174 篇 医学
- 165 篇 临床医学
- 158 篇 基础医学(可授医学...
- 117 篇 药学(可授医学、理...
- 62 篇 公共卫生与预防医...
78 篇 教育学
- 78 篇 教育学
75 篇 法学
- 68 篇 社会学
50 篇 农学
- 49 篇 作物学
45 篇 经济学
4 篇 军事学

主题

326 篇 machine learning
128 篇 deep learning
77 篇 support vector m...
66 篇 machine learning...
55 篇 forecasting
46 篇 feature extracti...
37 篇 decision trees
36 篇 accuracy
35 篇 computational mo...
34 篇 computer vision
31 篇 predictive model...
30 篇 training
28 篇 data mining
28 篇 students
28 篇 convolutional ne...
26 篇 neural networks
22 篇 object detection
22 篇 artificial intel...
21 篇 sentiment analys...
20 篇 internet of thin...

机构

12 篇 chitkara univers...
7 篇 shenyang ligong ...
6 篇 uttaranchal inst...
5 篇 department of co...
5 篇 maharishi school...
5 篇 alibaba cloud bi...
4 篇 school of comput...
4 篇 college of compu...
4 篇 key laboratory o...
4 篇 lovely professio...
4 篇 jilin agricultur...
4 篇 uttaranchal univ...
4 篇 key laboratory o...
4 篇 department of co...
4 篇 master of comput...
4 篇 school of inform...
3 篇 school of comput...
3 篇 vivekananda glob...
3 篇 department of el...
3 篇 college of compu...

作者

4 篇 liu gang
4 篇 kumar rakesh
4 篇 waseemullah
4 篇 liu peng
3 篇 zhang tao
3 篇 kumar ajay
3 篇 rakesh kumar
3 篇 babu tina
3 篇 siddhant
3 篇 sharma arun
3 篇 faisal rehman
3 篇 wang xiaofei
3 篇 sharif hanan
3 篇 singh sunil kuma...
3 篇 rehman faisal
3 篇 tina babu
3 篇 yang wei
3 篇 sharma avinash
3 篇 prajwal
3 篇 vinay kukreja

语言

1,803 篇 英文
58 篇 其他
16 篇 中文

检索条件"任意字段=3rd International Conference on Machine Learning and Computer Application, ICMLCA 2022"

共 1863 条记录，以下是1741-1750 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：

application of machine analysis algorithms to automate implementation of tasks of combating criminal money laundering 3rd

Application of machine analysis algorithms to automate imple...

引用

3rd international conference on Digital Transformation and Global Society, DTGS 2018

作者： Dorofeev, Dmitry Khrestina, Marina Usubaliev, Timur Dobrotvorskiy, Aleksey Filatov, Saveliy Moscow Russia Quality Software Solutions LLC Moscow Russia National Research University Higher School of Economics Moscow Russia

ISBN: (纸本)9783030028428

The progress in IT gave people a bigger space for fraudulent activity. To help the analysis of criminal financial activity special software was invented. The problem is that the machine of money laundering becomes more sophisticated, but present ways of detecting such activities cannot match the level of fraud capabilities. The main objective in this case is finding methods to improve the available systems and designing new algorithms, understanding all principles that are used in money laundering. To accomplish this, all the steps in AML-systems should be revised or developed from the beginning, new tools should be included. This article gives an overview of the current situation with analysis of weaknesses in present AML-system versions and shows the examples of using machine learning. © Springer Nature Switzerland AG 2018.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

3rd international conference on Cognitive Computing and Information Processing, CCIP 2017

3rd International Conference on Cognitive Computing and Info...

引用

3rd international conference on Cognitive Computing and Information Processing, CCIP 2017

ISBN: (纸本)9789811090585

The proceedings contain 43 papers. The special focus in this conference is on Cognitive Computing and Information Processing. The topics include: Influence of health service infrastructure on the infant mortality rate: An econometric analysis of Indian States;Eyes open and eyes close activity recognition using EEG signals;health and nutritional status of children: Survey, challenges and directions;an empirical analysis of machine learning classifiers for clinical decision making in Asthma;Web based blood donation management system (BDMS) and notifications;silent speech recognition;swarm intelligent approaches for solving shortest path problems with multiple objectives;improved directionally driven self-regulating particle swarm optimizer;judgement of learning for metacognitive type-2 fuzzy inference system;inter intensity and color channel co-occurrence histogram for color texture classification;LDA based discriminant features for texture classification using WT and PDE approach;Position error analysis of IRNSS data using big data analytics;analysis of breast thermal images using anisotropic diffusion filter based modified level sets and efficient fractal algorithm;cluster representation and discrimination based on regression line;recognition of traffic sign based on support vector machine and creation of the Indian traffic sign recognition benchmark;neural network based characterization and reliable routing of data in wireless body sensor networks;automata approach to reduce power consumption in smart grid cloud data center;Hybrid optimization in big data: Error detection and data repairing by big data cleaning using CSO-GSA;application of optimization technique for performance and emission characteristics of a CNG-diesel dual fuel engine: A comparison study.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Forecasting Natural Gas Flows in Large Networks 3rd

引用

3rd international conference on machine learning, Optimization, and Data Science (MOD)

作者： Dell'Amico, Mauro Hadjidimitriou, Natalia Selini Koch, Thorsten Petkovic, Milena Univ Modena & Reggio Emilia Via Amendola 2 I-42122 Reggio Emilia Italy Zuse Inst Berlin Takustr 7 D-14195 Berlin Germany

ISBN: (纸本)9783319729268;9783319729251

Natural gas is the cleanest fossil fuel since it emits the lowest amount of other remains after being burned. Over the years, natural gas usage has increased significantly. Accurate forecasting is crucial for maintaining gas supplies, transportation and network stability. This paper presents two methodologies to identify the optimal configuration o parameters of a Neural Network (NN) to forecast the next 24 h of gas flow for each node of a large gas network. In particular the first one applies a Design Of Experiments (DOE) to obtain a quick initial solution. An orthogonal design, consisting of 18 experiments selected among a total of 4.374 combinations of seven parameters (training algorithm, transfer function, regularization, learning rate, lags, and epochs), is used. The best result is selected as initial solution of an extended experiment for which the Simulated Annealing is run to find the optimal design among 89.100 possible combinations of parameters. The second technique is based on the application of Genetic Algorithm for the selection of the optimal parameters of a recurrent neural network for time series forecast. GA was applied with binary representation of potential solutions, where subsets of bits in the bit string represent different values for several parameters of the recurrent neural network. We tested these methods on three municipal nodes, using one year and half of hourly gas flow to train the network and 60 days for testing. Our results clearly show that the presented methodologies bring promising results in terms of optimal configuration of parameters and forecast error.

关键词： machine learning Neural networks Genetic algorithm Simulated annealing Design Of Experiments (DOE) Time series forecast

来源：评论

学校读者我要写书评

暂无评论

Data Classification using Active learning based Data Modification: An application to Churn Prediction 3

Data Classification using Active Learning based Data Modific...

引用

3rd international conference on Current Trends in computer, Electrical, Electronics and Communication, CTCEEC 2017

作者： Khalid, M.A.R. Farquad, M.A.H. Kamakshi Prasad, V. Department of Computer Science JNTUH College of Engineering Hyderabad Telangana State India Faculty of Computer and Information Systems Madinah Islamic University Madinah Saudi Arabia

ISBN: (纸本)9781538632420

Support Vector machine (SVM) is on one of its kind of data mining algorithm, tends to always give away the global optimum solution to any given problem because of its convex optimization problem solving approach. SVM learns from the given training data and generates a linear hyperplane classifying the given instances. The training instances which are near this separating hyperplane are called support vectors, using which predictions are obtained. In other words, SVM considers the support vectors as important instances for prediction purposes and ignores other instances which are much away from hyperplane boundary. In this project the ability of SVM i.e. extraction of support vectors is explored further and active learning based synthetic data generation (nearest to the support vectors) is employed. Synthetic data generation near support vectors would provide the classification algorithm (Naïve Bayes algorithm in this project) with some extra and suitable instances to learn from which in-turn expected to result in improving the prediction accuracy of the classifier used. Results have shown that Naïve Bayes classifier yielded superior accuracy using the modified dataset when compared to the accuracy yielded using original data available. © 2017 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

The cognitive features of programming language and natural language 3rd

The cognitive features of programming language and natural l...

引用

3rd international conference on Intelligence Science, ICIS 2018

作者： Xu, Wen Xu, Fangqu Zou, Xiaohui Xu, Zhenlin Shanghai Shenyue Software Technology Co. Ltd. Room B10 North D. Bld. 8 No. 619 Longchang Rd. Shanghai200090 China Sino-American Searle Research Center Tiantongyuan Paolichuntianpai Building 2 Room 1235 Daxing Beijing102629 China

ISBN: (纸本)9783030013127

The purpose of this paper is to establish the mechanism of mutual transformation between programming language and natural language through the cognitive features of programming language and natural language which enables computers to read natural language and furthermore, to think like a human brain to achieve the purpose of human-computer interaction. The method is: First, establish a data dictionary, a vocabulary table, a sentence table and a bilingual table so that natural language and programming language can establish a one-to-one, one-to-many conversion relationship. Second, according to the data dictionary and bilingual table, establish the thinking tree model, and implement the traversal of natural language (a particular mathematical problem) through programming language. Third, establish a selection mechanism so that, through programming language, the computer knows how to make different choices and responses corresponding to different natural languages. The result is: Through the exploration of the cognitive features of programming language and natural language, establish the mechanism of the mutual transformation between programming language and natural language. The significance is: through the use of two different languages, it can establish the mechanism of human-computer interaction. For the one-to-one situations, it can be automatically converted based on rules. On the other hand, for the one-to-many situation, it can realize machine learning, moreover, deep learning based on statistics. Thus, it lays the foundation for the application of artificial intelligence in the field of education. © IFIP international Federation for Information Processing 2018.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

A research of network applications classification based on deep learning 3rd

A research of network applications classification based on d...

引用

3rd international conference on machine learning and Intelligent Communications, MLICOM 2018

作者： Shao, Hong Tang, Liujun Dong, Ligang Chen, Long Jiang, Xian Wang, Weiming School of Information and Electronic Engineering Zhejiang Gongshang University Hangzhou310018 China

ISBN: (纸本)9783030005566

Nowadays, the huge traffic generated by a growing number of network applications occupies enormous network bandwidth and increases the burden of network management. The ability to identify and categorize network applications accurately is crucial for learning network traffic conditions, finding people’s online behavior and accelerating the development of the Internet. The prior traffic classification methods often have unstable recognition rate and high computational complexity, which affects the network traffic management and application categories monitoring. Therefore, this paper proposes a method of using the deep learning technology to classify network applications. First, we propose a network application classification model based on Deep Belief Network (DBN). Then we construct a DBN-based model suitable for network applications classification with the Tensorflow framework. Finally, the classification performances of this DBN-based model and the BP-based model are compared on the real data sets. The experimental results show that the applications classification model based on DBN has higher classification accuracy for P2P applications. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2018.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Traffic prediction using viterbi algorithm in machine learning approach 3rd

Traffic prediction using viterbi algorithm in machine learni...

引用

3rd international conference on Next Generation Computing Technologies, NGCT 2017

作者： Suvitha, D. Vijayalakshmi, M. Mohideen Sameer, P.M. Department of Information Science and Technology Anna University CEG Campus ChennaiTamil Nadu India

ISBN: (纸本)9789811086564

Road traffic snarl-up is a major issue in metropolitan area of both developing and developed countries. In order to diminish this imperative, traffic congestion states of road systems are assessed, so that congested path can be avoided and flipside path can be chosen while traveling from one place to another. Information’s are gathered by the GPS gadgets and offers new open doors for traffic and route prediction, particularly in urban city systems. The core purpose of this research work is to build up an Android application which gives a deliberate approach in providing the best route between a source and destination to the drivers so that driver will not be caught in the traffic. Android application uses machine learning algorithms. In this paper, Hidden Markov Model (HMM) is used for predicting traffic states which performs better and more robust than the other models. The best path from source to destination is predicted using Viterbi algorithm taking into the account of road traffic at the time and the driver will be directed to the best path. This application takes Json request as input to interface with the local server through Internet for predicting the traffic state and the best path. The output is returned back from the server as a Json response to the Android application. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

Health Assistant Wearable-Based Data Science System Model: A Pilot Study 3

Health Assistant Wearable-Based Data Science System Model: A...

引用

3rd international conference on Information Management and Technology, ICIMTech 2018

作者： Budiarto, Arif Febriana, Trisna Suparyanto, Teddy Caraka, Rezzy Eko Pardamean, Bens Computer Science Department Bina Nusantara University School of Computer Science Jakarta11480 Indonesia Information Systems Department Bina Nusantara University School of Information Systems Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Indonesia Faculty of Science National University of Malaysia School of Mathematical Science Bangi43000 Malaysia Computer Science Department Bina Nusantara University BINUS Graduate Program-Master of Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

The rapid development of Information and Communication Technology (ICT) has an impact on the innovation of new technology that gives benefits for health. One of its latest development is wearable device technology. Nowadays, the growth of this technology market is very positive. But unfortunately the growth of this technology is not followed by the availability of supporting applications that provide maximum benefits for users by utilizing personal health and activity data. This paper is intended to provide a report of our initial research in developing a health assistant solution that utilizes wearable device generated data. The whole research process is executed using Design Thinking approach that put the users as the main consideration. This initial research is started by designing a field research that can potentially gathered users' data generated from wearable device. A series of statistical and machine learning techniques are presented to analyze time series data to create a model. Finally, to implement the model, a mobile application prototype is also proposed. The outcomes from this initial research will be used to develop a fully working solution. © 2018 IEEE.

关键词： learning systems

来源：评论

学校读者我要写书评

暂无评论

application and Analysis of Fuzzy ARTMAP Network in computer Servo System

Application and Analysis of Fuzzy ARTMAP Network in Computer...

引用

international conference on Mechanical, Control and computer Engineering (ICMCCE)

作者： Rui Yang

From the perspective of operational logic, machine learning essentially uses the way of function, transforms the problem of machine learning into a function problem, and then implements machine learning by solving the objective function. The most important tool in solving the objective function is the optimization algorithm. In order to speed up the training process, it is necessary to design a parallel and distributed optimization algorithm in the context of big data. In recent years, many researchers have carried out extensive research on this issue, and some research results have been widely applied to the practice of machine learning.

关键词： Handheld computers Neural networks conferences Adaptive systems Cameras

来源：评论

学校读者我要写书评

暂无评论

application of NLP algorithms: Automatic text classifier tool 3rd

Application of NLP algorithms: Automatic text classifier too...

引用

3rd international conference on Digital Transformation and Global Society, DTGS 2018

作者： Romanov, Aleksandr Kozlova, Ekaterina Lomotin, Konstantin National Research University Higher School of Economics Myasnitskaya Ulitsa Moscow101000 Russia

ISBN: (纸本)9783030028459

This research is dedicated to the design of a decision support system for categorization of scientific literature. The purpose of this work is to research possible ways to apply the machine learning algorithms to the automation of manual text categorization. The following stages are considered: preprocessing of raw data, word embedding, model selection, classification model, and software design. At the first stage, in collaboration with VINITI RAS, the training set of 200,000 Russian texts was formed. At the second stage, the word embedding model was justified as Word2 Vec vector representation from text matrix by "sum" convolution with dimensionality 1500. At the third stage, the quality of the classifiers was estimated, and the logistic regression algorithm with the highest F1 score (0.94) was selected. And at the final stage, the ATC (Automatic Text Classifier) application, which embeds the results obtained on the previous stages, was developed. The overall application structure was described. It consists of compact program modules that can be replaced or adapted to the incoming text and gain the most classification score. © Springer Nature Switzerland AG 2018.

关键词： Support vector machines

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187页 << < 171 172 173 174 175 176 177 178 179 180 > >>

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：