To serve as a reference for future foreign tourism study,relevant tourist sectors have done in-depth investigations on foreign tourism both domestically and internationally.A study of outbound tourism activities from ...To serve as a reference for future foreign tourism study,relevant tourist sectors have done in-depth investigations on foreign tourism both domestically and internationally.A study of outbound tourism activities from the viewpoint of tourists can examine its development law and create successful marketing tactics based on the rise in the number of foreign tourists.Based on this,this study suggests a data mining technique to examine the variations in travel needs and marketing tactics among various consumer groups.The combined example analysis demonstrates how logical and useful our data mining analysis is.Our data tests demonstrate that the tourism strategy outlined in this paper can enhance the number of tourists by piquing their interest based on the rise in the number of international travellers travelling overseas.展开更多
This paper proposes an intelligent management system (IMS) to help managers in their delicate and tedious task of exploiting the plethora of data (indicators) contained in management dashboards. This system is based o...This paper proposes an intelligent management system (IMS) to help managers in their delicate and tedious task of exploiting the plethora of data (indicators) contained in management dashboards. This system is based on intelligent agents, ontologies and data mining. It is implemented by PASSI (Process for Agent Societies Specification and Implementation) methods for agent design and implementation, the Methodology for Knowledge Modeling and Hot-Winters for data prediction. Intelligent agents not only track indicators but also store the knowledge of managers within the company. Ontologies are used to manage the representation and presentation aspects of knowledge. Data mining makes it possible to: make the most of all available data;model the industrial process of data selection, exploration and modeling;and transform behaviors into predictive indicators. An instance of the IMS named SYGISS, currently in operation within a large brewery organization, allows us to observe very interesting results: the extraction of indicators is done in less than 5 minutes whereas manual extraction used to take 14 days;the generation of dashboards is instantaneous whereas it used to take 12 hours;the interpretation of indicators is instantaneous whereas it used to take a day;forecasts are possible and are done in less than 5 minutes whereas they did not exist with the old management. These important contributions help to optimize the management of this organization.展开更多
Coal is an essential fossil fuel in China; however, coal mining and its utilization are being under the increasing pressure from ecological and environmental protection. Therefore, the consulting project "Technic...Coal is an essential fossil fuel in China; however, coal mining and its utilization are being under the increasing pressure from ecological and environmental protection. Therefore, the consulting project "Technical Revolution in Ecological and Efficient Coal Mining and Utilization & Intelligence and Diverse Coordination of Coal-based Energy System," initiated by Chinese Academy of Engineering, puts forward three stages(3.0, 4.0 and 5.0) of China's coal industry development strategy. Aimed at "reduced staff,ultra-low ecological damage, and emission level near to natural gas," breakthroughs should be achieved in the following three key technologies during the China Coal Industry 3.0 stage(2016–2025): including intelligent coal mining, ecological mining, ultra-low emission and environmental protection. This paper focuses on the development trends of the China Coal Industry 3.0 and its support for China Coal Industry 4.0 and 5.0 is analyzed and prospected as well, which may offer technical assistance and strategy orientation for realizing the transformation from traditional coal energy to clean energy.展开更多
The traditional library can’t provide the service of personalized recommendation for users. This paper used Clementine to solve this problem. Firstly, model of K-means clustering analyze the initial data to delete th...The traditional library can’t provide the service of personalized recommendation for users. This paper used Clementine to solve this problem. Firstly, model of K-means clustering analyze the initial data to delete the redundant data. It can avoid scanning the database repeatedly and producing a large number of false rules. Secondly, the paper used clustering results to perform association rule mining. It can obtain valuable information and achieve the service of intelligent recommendation.展开更多
Data mining is a procedure of separating covered up,obscure,however possibly valuable data from gigantic data.Huge Data impactsly affects logical disclosures and worth creation.Data mining(DM)with Big Data has been br...Data mining is a procedure of separating covered up,obscure,however possibly valuable data from gigantic data.Huge Data impactsly affects logical disclosures and worth creation.Data mining(DM)with Big Data has been broadly utilized in the lifecycle of electronic items that range from the structure and generation stages to the administration organize.A far reaching examination of DM with Big Data and a survey of its application in the phases of its lifecycle won't just profit scientists to create solid research.As of late huge data have turned into a trendy expression,which constrained the analysts to extend the current data mining methods to adapt to the advanced idea of data and to grow new scientific procedures.In this paper,we build up an exact assessment technique dependent on the standard of Design of Experiment.We apply this technique to assess data mining instruments and AI calculations towards structure huge data examination for media transmission checking data.Two contextual investigations are directed to give bits of knowledge of relations between the necessities of data examination and the decision of an instrument or calculation with regards to data investigation work processes.展开更多
Influence maximization,whose aim is to maximise the expected number of influenced nodes by selecting a seed set of k influential nodes from a social network,has many applications such as goods advertising and rumour s...Influence maximization,whose aim is to maximise the expected number of influenced nodes by selecting a seed set of k influential nodes from a social network,has many applications such as goods advertising and rumour suppression.Among the existing influence maximization methods,the community‐based ones can achieve a good balance between effectiveness and efficiency.However,this kind of algorithm usually utilise the network community structures by viewing each node as a non‐overlapping node.In fact,many nodes in social networks are overlapping ones,which play more important role in influence spreading.To this end,an overlapping community‐based particle swarm opti-mization algorithm named OCPSO for influence maximization in social networks,which can make full use of overlapping nodes,non‐overlapping nodes,and their interactive information is proposed.Specifically,an overlapping community detection algorithm is used to obtain the information of overlapping community structures,based on which three novel evolutionary strategies,such as initialisation,mutation,and local search are designed in OCPSO for better finding influential nodes.Experimental results in terms of influence spread and running time on nine real‐world social networks demonstrate that the proposed OCPSO is competitive and promising comparing to several state‐of‐the‐arts(e.g.CGA,CMA‐IM,CIM,CDH‐SHRINK,CNCG,and CFIN).展开更多
针对矿井安全生产检测数据传输效率低下和共享性差的特点,综合考虑开发成本与工作环境要求,基于CAN(Controller Area Network)和REST(Representational State Transfer)物联网技术提出了智能矿山安全检测方法,设计了矿山安全检测判别程...针对矿井安全生产检测数据传输效率低下和共享性差的特点,综合考虑开发成本与工作环境要求,基于CAN(Controller Area Network)和REST(Representational State Transfer)物联网技术提出了智能矿山安全检测方法,设计了矿山安全检测判别程序,采用最大熵模型算法开发了数据信息预警程序。结合CAN总线技术,将多传感器信息进行有机融合并进行安全数据检测,将井下传感器设备相关信息经过判断分析后传输至总机。将所提安全检测方法进行了系统开发,并在淮北某矿进行了应用。结果表明:基于CAN和REST物联网技术的安全检测方法能够实现多点测量,并可随机增减检测设备,可实现数据实时传输和共享,有助于实现矿山安全实时检测。展开更多
基金2021 Youth Innovation Talents Project of Universities in Guangdong Province“Cause Analysis and Countermeasure Research on the Difference of Tourism Resources Development and Marketing Weakening in Underdeveloped Regions of Western Guangdong”(Project No.2021WQNCX241).
文摘To serve as a reference for future foreign tourism study,relevant tourist sectors have done in-depth investigations on foreign tourism both domestically and internationally.A study of outbound tourism activities from the viewpoint of tourists can examine its development law and create successful marketing tactics based on the rise in the number of foreign tourists.Based on this,this study suggests a data mining technique to examine the variations in travel needs and marketing tactics among various consumer groups.The combined example analysis demonstrates how logical and useful our data mining analysis is.Our data tests demonstrate that the tourism strategy outlined in this paper can enhance the number of tourists by piquing their interest based on the rise in the number of international travellers travelling overseas.
文摘This paper proposes an intelligent management system (IMS) to help managers in their delicate and tedious task of exploiting the plethora of data (indicators) contained in management dashboards. This system is based on intelligent agents, ontologies and data mining. It is implemented by PASSI (Process for Agent Societies Specification and Implementation) methods for agent design and implementation, the Methodology for Knowledge Modeling and Hot-Winters for data prediction. Intelligent agents not only track indicators but also store the knowledge of managers within the company. Ontologies are used to manage the representation and presentation aspects of knowledge. Data mining makes it possible to: make the most of all available data;model the industrial process of data selection, exploration and modeling;and transform behaviors into predictive indicators. An instance of the IMS named SYGISS, currently in operation within a large brewery organization, allows us to observe very interesting results: the extraction of indicators is done in less than 5 minutes whereas manual extraction used to take 14 days;the generation of dashboards is instantaneous whereas it used to take 12 hours;the interpretation of indicators is instantaneous whereas it used to take a day;forecasts are possible and are done in less than 5 minutes whereas they did not exist with the old management. These important contributions help to optimize the management of this organization.
基金supported by the Major State Basic Research Development Program of China (No. 2014CB046302)
文摘Coal is an essential fossil fuel in China; however, coal mining and its utilization are being under the increasing pressure from ecological and environmental protection. Therefore, the consulting project "Technical Revolution in Ecological and Efficient Coal Mining and Utilization & Intelligence and Diverse Coordination of Coal-based Energy System," initiated by Chinese Academy of Engineering, puts forward three stages(3.0, 4.0 and 5.0) of China's coal industry development strategy. Aimed at "reduced staff,ultra-low ecological damage, and emission level near to natural gas," breakthroughs should be achieved in the following three key technologies during the China Coal Industry 3.0 stage(2016–2025): including intelligent coal mining, ecological mining, ultra-low emission and environmental protection. This paper focuses on the development trends of the China Coal Industry 3.0 and its support for China Coal Industry 4.0 and 5.0 is analyzed and prospected as well, which may offer technical assistance and strategy orientation for realizing the transformation from traditional coal energy to clean energy.
基金Supported by the National Natural Science Foundation of China （50375026, 50375028） the National High-tech R＆D Program of China （863 Program） （2012AA06A407）
文摘The traditional library can’t provide the service of personalized recommendation for users. This paper used Clementine to solve this problem. Firstly, model of K-means clustering analyze the initial data to delete the redundant data. It can avoid scanning the database repeatedly and producing a large number of false rules. Secondly, the paper used clustering results to perform association rule mining. It can obtain valuable information and achieve the service of intelligent recommendation.
文摘Data mining is a procedure of separating covered up,obscure,however possibly valuable data from gigantic data.Huge Data impactsly affects logical disclosures and worth creation.Data mining(DM)with Big Data has been broadly utilized in the lifecycle of electronic items that range from the structure and generation stages to the administration organize.A far reaching examination of DM with Big Data and a survey of its application in the phases of its lifecycle won't just profit scientists to create solid research.As of late huge data have turned into a trendy expression,which constrained the analysts to extend the current data mining methods to adapt to the advanced idea of data and to grow new scientific procedures.In this paper,we build up an exact assessment technique dependent on the standard of Design of Experiment.We apply this technique to assess data mining instruments and AI calculations towards structure huge data examination for media transmission checking data.Two contextual investigations are directed to give bits of knowledge of relations between the necessities of data examination and the decision of an instrument or calculation with regards to data investigation work processes.
基金supported in part by the National Natural Science Foundation of China(61976001,62076001,61876184)the Key Projects of University Excellent Talents Support Plan of Anhui Provincial Department of Education(gxyqZD2021089)+1 种基金the University Synergy Innovation Program of Anhui Province(GXXT‐2020‐050)the Natural Science Foundation of Anhui Province(2008085QF309).
文摘Influence maximization,whose aim is to maximise the expected number of influenced nodes by selecting a seed set of k influential nodes from a social network,has many applications such as goods advertising and rumour suppression.Among the existing influence maximization methods,the community‐based ones can achieve a good balance between effectiveness and efficiency.However,this kind of algorithm usually utilise the network community structures by viewing each node as a non‐overlapping node.In fact,many nodes in social networks are overlapping ones,which play more important role in influence spreading.To this end,an overlapping community‐based particle swarm opti-mization algorithm named OCPSO for influence maximization in social networks,which can make full use of overlapping nodes,non‐overlapping nodes,and their interactive information is proposed.Specifically,an overlapping community detection algorithm is used to obtain the information of overlapping community structures,based on which three novel evolutionary strategies,such as initialisation,mutation,and local search are designed in OCPSO for better finding influential nodes.Experimental results in terms of influence spread and running time on nine real‐world social networks demonstrate that the proposed OCPSO is competitive and promising comparing to several state‐of‐the‐arts(e.g.CGA,CMA‐IM,CIM,CDH‐SHRINK,CNCG,and CFIN).
文摘针对矿井安全生产检测数据传输效率低下和共享性差的特点,综合考虑开发成本与工作环境要求,基于CAN(Controller Area Network)和REST(Representational State Transfer)物联网技术提出了智能矿山安全检测方法,设计了矿山安全检测判别程序,采用最大熵模型算法开发了数据信息预警程序。结合CAN总线技术,将多传感器信息进行有机融合并进行安全数据检测,将井下传感器设备相关信息经过判断分析后传输至总机。将所提安全检测方法进行了系统开发,并在淮北某矿进行了应用。结果表明:基于CAN和REST物联网技术的安全检测方法能够实现多点测量,并可随机增减检测设备,可实现数据实时传输和共享,有助于实现矿山安全实时检测。
