Proceedings of the 2019 International Conference on Data Mining and Machine Learning最新文献_第3页

Proceedings of the 2019 International Conference on Data Mining and Machine Learning Pub Date : 2019-04-28 DOI: 10.1145/3335656.3335679

Anton Voronov, Yao Shen, Pritom Kumar Mondal

引用次数: 5

Hypothesis and Application of Complex Truncated Stochastic Investment-Revenue Model 复截尾随机投资收益模型的假设及应用

Proceedings of the 2019 International Conference on Data Mining and Machine Learning Pub Date : 2019-04-28 DOI: 10.1145/3335656.3335687

Li Ye, Chen Yiyan

引用次数: 0

An improved FCM clustering algorithm based on cosine similarity 基于余弦相似度的改进FCM聚类算法

Proceedings of the 2019 International Conference on Data Mining and Machine Learning Pub Date : 2019-04-28 DOI: 10.1145/3335656.3335693

Minxuan Li

引用次数: 8

Application of Mathematical Model in Pension: System Reform for Retired Employee in Enterprise 数学模型在企业退休人员养老金制度改革中的应用

Proceedings of the 2019 International Conference on Data Mining and Machine Learning Pub Date : 2019-04-28 DOI: 10.1145/3335656.3335681

Haihui Wu

{"title":"Application of Mathematical Model in Pension: System Reform for Retired Employee in Enterprise","authors":"Haihui Wu","doi":"10.1145/3335656.3335681","DOIUrl":"https://doi.org/10.1145/3335656.3335681","url":null,"abstract":"In this paper, we describe the formatting guidelines for ACM SIG Proceedings. In this paper, the reform of the pensions system for retired workers in Chinese enterprises is studied by means of mathematical modeling. Firstly, the paper analyzes the average wage of workers in Shandong Province since 1978, which is rising as the time goes by using the statistical data and the Matlab software, combined with relevant knowledge of economics. The Malthus and Logistic models were successively adopted as empirical formulas for regression analysis, so as to obtain a more accurate prediction model. And the annual average wage of workers from 2019 to 2040 is predicted by using this model. Then, taking a certain enterprise as an example, a mathematical model is set up to calculate the pension substitution rate and the gap of the pension fund of the enterprise staff in all kinds of situations, and to give the age when the payment of the pension is in balance with the earnings. Finally, some effective measures for the government are given by using the model in order to achieve the target of 58.5% of the basic old-age insurance in the future and maintain the balance of income and expenditure of the pension insurance fund.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"442 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127605295","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

Application of PCA in the Porosity Evaluation of a Coal Reservoir 主成分分析法在煤储层孔隙度评价中的应用

Proceedings of the 2019 International Conference on Data Mining and Machine Learning Pub Date : 2019-04-28 DOI: 10.1145/3335656.3335695

Jingang Wu, Guang Zhang

{"title":"Application of PCA in the Porosity Evaluation of a Coal Reservoir","authors":"Jingang Wu, Guang Zhang","doi":"10.1145/3335656.3335695","DOIUrl":"https://doi.org/10.1145/3335656.3335695","url":null,"abstract":"In this paper, we study the feasibility of applying the principal component analysis (PCA) for porosity evaluation of a coal Reservoir. The geological characteristics of the No. 3 coal reservoir in Qinshui Basin (Shanxi Province, China) were analyzed at first. On this basis, vitrinite reflectance, coal macrolithotype, ash content, macro-fissure density, micro-fissure density, and coal structure were adopted as the index variables for evaluating the porosity. Three principal components were extracted by reducing dimensions of the six primitive variables. Then, a scoring model of the principal components was constructed to calculate the comprehensive scores for porosity of the coal samples. In addition, Qinshui Basin was partitioned into four regions: a (Yangquan), b (Jingfang-Wangzhuang), c (Changcun), and d (Jincheng), which were listed in a descending order as a, c, b, and d with reducing porosities. Explanation of the principal components and geological theoretical analysis revealed that the geotectonic movements and evolutions, and sedimentary environment are main controlling factors for studying the porosity based zoning of the research region. The results prove that it is feasible to apply PCA to evaluate the porosity of coal reservoirs.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134431850","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

Detecting Domain Generation Algorithms Based on Cascade Foresets 基于级联森林集的检测域生成算法

Proceedings of the 2019 International Conference on Data Mining and Machine Learning Pub Date : 2019-04-28 DOI: 10.1145/3335656.3335690

Xianrong Song, Haoliang Sun, Hong Zhang, Meng Zhang

引用次数: 0

Enhanced Automatic Image Parameter setting and Segmentation Method 增强的自动图像参数设置和分割方法

Proceedings of the 2019 International Conference on Data Mining and Machine Learning Pub Date : 2019-04-28 DOI: 10.1145/3335656.3335697

Kedir Kamu Sirur, Ye Peng, Zhang Qinchuan

引用次数: 0

Hierarchical Relation Extraction Based On Bidirectional Long Short-Term Memory Networks 基于双向长短期记忆网络的层次关系提取

Proceedings of the 2019 International Conference on Data Mining and Machine Learning Pub Date : 2019-04-28 DOI: 10.1145/3335656.3335694

Jia Chen, Liang Liu, Jiali Xu, Bei Hui

引用次数: 0

Research on the Influence of National System along "the Belt and Road Initiative" on Investment Area Selection Based on Mult-Motivation Analysis of Intelligent Modeling and Information Processing 基于智能建模与信息处理多动机分析的“一带一路”沿线国家体系对投资区选择的影响研究

Proceedings of the 2019 International Conference on Data Mining and Machine Learning Pub Date : 2019-04-28 DOI: 10.1145/3335656.3335689

Liu Ying, Zhang Renping, Rizwan Ali

{"title":"Research on the Influence of National System along \"the Belt and Road Initiative\" on Investment Area Selection Based on Mult-Motivation Analysis of Intelligent Modeling and Information Processing","authors":"Liu Ying, Zhang Renping, Rizwan Ali","doi":"10.1145/3335656.3335689","DOIUrl":"https://doi.org/10.1145/3335656.3335689","url":null,"abstract":"Through the multi-task analysis of the intelligent modeling and information processing of the business data of each country over the years, it is possible to distinguish which countries have better business environment. From the perspective of investment motives, this paper studies the influence of national institutional mechanism on the choice of overseas investment regions of Chinese enterprises. In addition, Intelligent Modeling analysis of 65 host countries along \"the Belt and Road\" and 275 observations in the past 5 years have been conducted in the paper. Base on the information processing, we found that, compared with those enterprises seeking market and strategic assets, Chinese resource-oriented companies always tend to ignore institutional factors in site selection. However, due to the limitations of China's market economy in the development process and the internal problems of those companies, domestic market-oriented and strategic asset-oriented enterprises often pay less attention to certain institutional factors.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128663244","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 offline behavior similarity of consumers based on Spatio-temporal data set mining 基于时空数据集挖掘的消费者线下行为相似度研究

Proceedings of the 2019 International Conference on Data Mining and Machine Learning Pub Date : 2019-04-28 DOI: 10.1145/3335656.3335684

Zhang Renping, Liu Ying, Rizwan Ali

{"title":"Research on offline behavior similarity of consumers based on Spatio-temporal data set mining","authors":"Zhang Renping, Liu Ying, Rizwan Ali","doi":"10.1145/3335656.3335684","DOIUrl":"https://doi.org/10.1145/3335656.3335684","url":null,"abstract":"The Spatio-temporal data set can be used in business research, For example, The user's geolocation check-in data (POI) in social media can be used to trace back the user's behavior track, however, the analysis of the similarity of LBSN users is not involved in the user's geographical location track. As a result, a density clustering method based on partition hierarchy and different neighborhood radius by users' geographical location is proposed to help explore similar measurement based on Spatio-temporal data set mining. The method observes the number of times a user visits each cluster region at different spatial location scales, and then calculates the similarity of users at each level by taking advantage of vector space model (VSM). Finally, users' similarity in Spatio-temporal(geospatial) behavior is obtained by superimposing user similarity values at different levels with different weights. The experimental results based on real user data of a large-scale social networking site in China show that the proposed method can effectively identify those users when they visit similar geographical locations.","PeriodicalId":396772,"journal":{"name":"Proceedings of the 2019 International Conference on Data Mining and Machine Learning","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121061014","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