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2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)最新文献

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Basin of Attraction as a measure of robustness of an optimization algorithm 作为优化算法稳健性衡量标准的吸引力盆地
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8686850
Ken K. T. Tsang
{"title":"Basin of Attraction as a measure of robustness of an optimization algorithm","authors":"Ken K. T. Tsang","doi":"10.1109/FSKD.2018.8686850","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8686850","url":null,"abstract":"The concept of Basin of Attraction (BOA)from the theory of dynamical systems can be applied to evaluate the robustness of a deterministic optimization algorithm. For an objective function with many local minima, a large BOA with smooth boundaries associated with the global minimum is an important indicator for the robustness of the optimization algorithm. In this paper, numerical examples of BOA for canned commercial optimizer: fmincon in MATLAB's toolbox (Sequential Quadratic Programming, sqp, and Interior-Point Algorithm)are given as illustrations of how BOA can be used as a tool to compare the robustness of optimization algorithms. We also showed in an example of machine learning application, spurious local minima often appear with more training data are added, and these spurious local minima have nothing to do with the legitimate solution. Finally, three different types of quantitative measure of the robustness of an optimization algorithm based on the basin boundaries are proposed.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129702892","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: 4
An improved user-based collaborative filtering algorithm 改进的基于用户的协同过滤算法
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8687118
Z. Zou, Zhijun Wang, Suming Zhang, Shu-han Cheng
{"title":"An improved user-based collaborative filtering algorithm","authors":"Z. Zou, Zhijun Wang, Suming Zhang, Shu-han Cheng","doi":"10.1109/FSKD.2018.8687118","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8687118","url":null,"abstract":"The collaborative filtering algorithm[1] proposed by Grouplens[2] is one of the most commonly used methods for personalized recommendation in recommendation systems [3] [4] [5] [6], and the core component of User-based collaborative filtering is the similarity measure. The traditional user similarity measurement method does not consider the influence of factors such as frequent user interest transfer and content popularity degree difference on the accuracy of the algorithm, and the existing improvement strategies cannot comprehensively consider these two factors. Based on the traditional similarity algorithm, this paper introduces influential factors such as user interest decline over time and content popularity, so as to improve the existing user similarity algorithm and to compare the actual data to prove the improved algorithm.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126817829","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
Research on Braille Music Recognition Based on Convolutional Neural Network 基于卷积神经网络的盲文音乐识别研究
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8686884
Rongrong Huang, Biao Liu, W. Su, He Lin
{"title":"Research on Braille Music Recognition Based on Convolutional Neural Network","authors":"Rongrong Huang, Biao Liu, W. Su, He Lin","doi":"10.1109/FSKD.2018.8686884","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8686884","url":null,"abstract":"In this era of advanced information technology, it is increasingly essential to acquire important information in time. But there exists a wider communicational gap between visually impaired people and visually normal people. The reason is that the current recognition technology of braille is not very mature, which makes the visually impaired people unable to integrate into the current information age. In this paper, the convolutional neural network model, popular at present, is used to establish the recognition model of braille music. Compared with the previous recognition model, it can be seen as a new attempt. At the same time, we performed some basic preprocessing operations on braille music images. The results of every layer of the recognition model are also shown in detail, which is more prominent in the feature extraction of braille characters. In addition, we developed the training algorithm and test algorithm of braille music. Finally, the experimental results show that the recognition model based on convolutional neural network has good effectiveness and strong generalization ability.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126916789","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: 2
A Quality Metric for K-Means Clustering k -均值聚类的质量度量
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8687210
M. Thulasidas
{"title":"A Quality Metric for K-Means Clustering","authors":"M. Thulasidas","doi":"10.1109/FSKD.2018.8687210","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8687210","url":null,"abstract":"From a teaching perspective, K-Means algorithm for clustering figures in the introductory courses in data analytics because of its conceptual simplicity. However, it suffers from a couple of drawbacks in terms of variable selection and the determination of the optimal number of clusters. In this paper, we present a new, mathematically defensible, quality metric for K-Means clustering based on the standard score of the distribution of the centroids. Furthermore, we demonstrate how this Standard Score Metric (SSM) can be used for automatic variable selection and optimal number of clusters using well-known data sets as well as real data collected locally.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123970773","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
Optimised Structure of Convolutional Neural Networks for Controller Area Network Classification 优化的卷积神经网络结构用于控制器区域网络分类
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8687274
Siti-Farhana Lokman, Abu Talib Bin Othman, M. Abu-Bakar
{"title":"Optimised Structure of Convolutional Neural Networks for Controller Area Network Classification","authors":"Siti-Farhana Lokman, Abu Talib Bin Othman, M. Abu-Bakar","doi":"10.1109/FSKD.2018.8687274","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8687274","url":null,"abstract":"Security researchers have proved that current modern automobiles are vulnerable to attack, particularly in Controller Area Network (CAN) which controls most of the critical parts in cars. The adversaries can gain access to the compromised vehicle's component and flood with modified CAN packet to cause physical effects. Hence, categorising normal CAN packets had become significant to determine the standard behaviour of CAN bus traffic in detecting attacks. A proposed anomaly detection classifier in this paper is inspired by the sequence classification in Natural Language Processing (NLP) problem, where, the combination of word embedding and Convolutional Neural Network (CNN) algorithm are used. This approach aims to construct a baseline classifier of normal CAN DATA fields according to their CAN ID family. The cross-entropy loss is used to measure the proposed classifier's performance index. Besides, the hyperparameter tuning structure of the classifier is designed based on Taguchi method. The analysis suggested that maximising Signal-to- Noise (S/N) ratio by setting Rectified Linear Unit (Relu) for activation function, epochs of 6, vocab size of 356 and ‘Dropout’ of 0.6, hence prediction loss can be significantly reduced. A systematic analysis design using Taguchi method is considered a new methodology to anomaly detection classifier in CAN bus data.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"21 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114028699","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
Lexicography minimum solution of max-min fuzzy relation inequalities 最大-最小模糊关系不等式的词典学最小解
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8687268
Hai-Tao Lin, Xiaopeng Yang
{"title":"Lexicography minimum solution of max-min fuzzy relation inequalities","authors":"Hai-Tao Lin, Xiaopeng Yang","doi":"10.1109/FSKD.2018.8687268","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8687268","url":null,"abstract":"Lexicography minimum solution is defined to describe a system of fuzzy relation inequality(FRI) with max-min composition is introduced in this paper. It can be applied to P2P file sharing system when we consider its priority rank of the terminals of the networking. The concepts and properties of lexicography relation and lexicography minimum solution are studied, and an algorithm for lexicography minimum solution is proposed by constructing $n$ programming problems, which is effective and flexible and illustrated by an application example.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127602358","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
Online Judge System Topic Classification 在线裁判系统主题分类
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8686958
Jianyu Liu, Shaohong Zhang, Zongbao Yang, Zhiqian Zhang, Jing Wang, X. Xing
{"title":"Online Judge System Topic Classification","authors":"Jianyu Liu, Shaohong Zhang, Zongbao Yang, Zhiqian Zhang, Jing Wang, X. Xing","doi":"10.1109/FSKD.2018.8686958","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8686958","url":null,"abstract":"with the development of education, the program design teaching is receiving more and more attention as one of the core computer science courses in recently years, more and more schools are training students in conjunction with Online Judge Systems (OJs). A great number of OJ platforms are developed in domestic and foreign, and there are many suits of exercises and solutions reported in the websites. However, the OJs do not classify neither the knowledge points, nor the difficulty of these topics. Moreover, corresponding problem solving methods have not been organized and used by programming enthusiasts. In this paper, we designed a classification method to solve this problem by predicting the topic categories, conjecting the free topics and the solution resources, and classifying the unknown categories and the difficulty level of new topics. It will benefit students and teachers in related learning with OJs.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126435538","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: 2
Mathematical programming of airline revenue management with passenger choice behavior 考虑乘客选择行为的航空公司收益管理数学规划
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8687121
Jinmin Gao, Meilong Le
{"title":"Mathematical programming of airline revenue management with passenger choice behavior","authors":"Jinmin Gao, Meilong Le","doi":"10.1109/FSKD.2018.8687121","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8687121","url":null,"abstract":"Mathematical programming models of airline seat inventory control tend to protect more seats for the high fare class. In order to further study the properties of booking policy based on mathematical programming models, we propose the deterministic and stochastic models that incorporate passenger choice behavior and develop efficient genetic algorithm(GA) to solve the stochastic programming model. In the experiments, we make an evaluation between the mathematical programming models and the decision rules based on traditional EMSR and EMSRb models in three aspects: the percentage of demand diversion, the number of fare classes and the demand level. The results show that, mathematical programming models' tendency to overprotect high-fare demand can make them perform better when adopted to control seat inventory with passenger demand diversion in some situations.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125735141","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: 1
The Influence Ranking for Software Classes 软件类影响力排名
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8687115
Hui Li, Guofeng Gao, X. Ge, Shikai Guo, Liying Hao
{"title":"The Influence Ranking for Software Classes","authors":"Hui Li, Guofeng Gao, X. Ge, Shikai Guo, Liying Hao","doi":"10.1109/FSKD.2018.8687115","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8687115","url":null,"abstract":"As the growth of software system scale and complexity, the risk of system collapse is rising because of the increasing software defects. Many defect detection and prediction methods are presented to solve this problem, but the effect is still not satisfied so far. Therefore, software network is brought in to analyze the system structure from the overall view of the system, and some methods have achieved satisfying results. In this paper, a weighted software network model is first presented to describe the software systems. Then a method of influence ranking for software classes (IRSC)is proposed to sort the propagation capacity of the underlying defect for all the classes. In the following, software defect implantation experiments are conducted and verified that IRSC method is effective on measuring the influence of the classes for software systems.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121959906","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: 2
The Sorting Methods Based on Dominance of Hierarchical Rough Sets 基于层次粗糙集优势度的排序方法
2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) Pub Date : 2018-07-01 DOI: 10.1109/FSKD.2018.8687283
Zixin Liu, Sen Wang, Xuesheng Liu
{"title":"The Sorting Methods Based on Dominance of Hierarchical Rough Sets","authors":"Zixin Liu, Sen Wang, Xuesheng Liu","doi":"10.1109/FSKD.2018.8687283","DOIUrl":"https://doi.org/10.1109/FSKD.2018.8687283","url":null,"abstract":"This article is aiming at the case that attribute sets are defined as a partial order sets in the information system. Using hierarchical rough sets theory, we established the dominance system of knowledge, and sorted out the object of study. In this article, the main characteristic is combining the hierarchical rough sets with partial order sets for the purpose of information fusion, putting forward a sorting method in multiple attribute decision making. This paper fully shows the flexibility of hierarchical rough sets, and the feasibility of the combining hierarchical rough sets with dominance system of knowledge. We also did an experiment on sorting method, and satisfactory results have been achieved.","PeriodicalId":235481,"journal":{"name":"2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130884770","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
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