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Full-Text Articles in Computer Engineering
Spatio-Temporal Association Rule Mining Of Traffic Congestion In A Large-Scale Road Network Based On Trajectory Data, Qifan Zhou, Haixu Liu, Zhipeng Dong, Yin Xu
Spatio-Temporal Association Rule Mining Of Traffic Congestion In A Large-Scale Road Network Based On Trajectory Data, Qifan Zhou, Haixu Liu, Zhipeng Dong, Yin Xu
Journal of System Simulation
Abstract: A K neighbor-RElim (KNR) algorithm and a sequential KNbr-RElim (SKNR) algorithm are proposed to mine traffic congestion association rules and congestion propagation spatio-temporal association rules by vehicle trajectory data in a large-scale road network. The KNR algorithm extends the spatial topology constraint based on the RElim algorithm. The KNR can be used to mine the road links prone to congestion from the large-scale trajectory dataset in a large-scale road network and quantify the strength of association for congested road links. The SKNR algorithm expands the time dimension in the form of sliding window and can be applied for mining …
Research On Assocoation Information Mining Of Space Reconnaissance Equipment System Index, Han Chi, Xiong Wei
Research On Assocoation Information Mining Of Space Reconnaissance Equipment System Index, Han Chi, Xiong Wei
Journal of System Simulation
Abstract: The system effectiveness and system contribution rate of the Space Reconnaissance Equipment System (SRES) has a large number of mutally associated indicators. How to identify relationships the association, select the key indicators and clarify the assocition between core indicators and system contribution rate are the key of the evaluation of system effectiveness and contribution rate. Through the joint simulation of MATLAB and STK, the underlying index data of SRES is obtained. Based on the Frequent Pattern-Tree (FP-Tree) algorithm, the assocition information is discovered, the redundancy is removed and the type of indicator assocition is determined, and an optimization model …
Analysis And Optimization Of Combustion Characteristics Of Cement Kiln Cooperatively Disposing Domestic Refuse, Jingbing Wu, Hanqing Tang, Xu Jun
Analysis And Optimization Of Combustion Characteristics Of Cement Kiln Cooperatively Disposing Domestic Refuse, Jingbing Wu, Hanqing Tang, Xu Jun
Journal of System Simulation
Abstract: Because the traditional methods can hardly analyze the complex combustion characteristics of cement kiln mixed with domestic refuse, a data mining technology is introduced. A domestic cement plant is selected as the object, and its operating data and relevant parameters are collected. The influence coefficient of each parameter on coal consumption and NOx emission is analyzed by using Stability Selection algorithm. The mathematical model of coal consumption and NOx emission is established with Random Forest algorithm, and the key optimization parameters and their optimal values are obtained by K-means clustering algorithm. The result shows that this method …
Energy Efficiency Data Mining And Scheduling Optimization Of Discrete Workshop, Yugu Lin, Wang Yan
Energy Efficiency Data Mining And Scheduling Optimization Of Discrete Workshop, Yugu Lin, Wang Yan
Journal of System Simulation
Abstract: This paper addresses the optimization of energy consumption in discrete workshops and establishes the energy efficiency optimization model of discrete workshops. The relationship between data mining and knowledge discovery is established. Through scheduling data preprocessing and C4.5 decision tree learning algorithm, the discovery of scheduling knowledge is realized. Energy efficiency optimization calculation is achieved in discrete workshops by the combination of scheduling knowledge and improved differential evolution algorithm (IDE). By comparing with TLBO, GA and PSO, the feasibility of IDE algorithm is verified.
Feature Space Modeling For Accurate And Efficient Learning From Non-Stationary Data, Ayesha Akter
Feature Space Modeling For Accurate And Efficient Learning From Non-Stationary Data, Ayesha Akter
Doctoral Dissertations
A non-stationary dataset is one whose statistical properties such as the mean, variance, correlation, probability distribution, etc. change over a specific interval of time. On the contrary, a stationary dataset is one whose statistical properties remain constant over time. Apart from the volatile statistical properties, non-stationary data poses other challenges such as time and memory management due to the limitation of computational resources mostly caused by the recent advancements in data collection technologies which generate a variety of data at an alarming pace and volume. Additionally, when the collected data is complex, managing data complexity, emerging from its dimensionality and …
Optimization Of Material Release For Printed Circuit Board Template Based On Data Mining, Shengping Lü, Qiangsheng Yue, Liu Tao
Optimization Of Material Release For Printed Circuit Board Template Based On Data Mining, Shengping Lü, Qiangsheng Yue, Liu Tao
Journal of System Simulation
Abstract: Data mining were employed for the optimization of material release of PCB (Printed Circuit Board) template. PCB scrap ratio related parameters were specified and prediction model variables were chosen according to hypothesis test. Multiple linear regression (MLR), Chi-squared automatic interaction detector, artificial neural network and support vector machine approaches for the prediction of scrap ratio were employed. Evaluation indictors called as superfluous ratio, supplement release ratio and weighted sum of the two were presented; the material release simulation was conducted and then the four approaches were compared and MLR was taken as the preferred one. Adjust coefficient …
Mining And Validation Of Attacking Behavior In The Robocup 2d Simulation, Chen Bing, Zhang Heng, Zekai Cheng, Dong Peng, Lin Chao
Mining And Validation Of Attacking Behavior In The Robocup 2d Simulation, Chen Bing, Zhang Heng, Zekai Cheng, Dong Peng, Lin Chao
Journal of System Simulation
Abstract: Robocup is an international academic competition which focuses on artificial intelligence and robotics. The 2D simulation is one of the earliest and most influential projects in Robocup. Attacking is the core behaviour of the simulated football game, as well as the attack recognition is considered as an important part in team-confrontations. This paper selects some active and contribution index of attacking, extracts lots of attacking behaviour data of the key agents, proposes two kinds of attacking patterns of 2D simulation, as ‘separate attack’ and ‘cooperative attack’, according to the human-player actions. The following simulation tests give the accuracy of …
Clustering Method Based On Graph Data Model And Reliability Detection, Yanyun Cheng, Huisong Bian, Changsheng Bian
Clustering Method Based On Graph Data Model And Reliability Detection, Yanyun Cheng, Huisong Bian, Changsheng Bian
Journal of System Simulation
Abstract: For the data in feature space, traditional clustering algorithm can take clustering analysis directly. High-dimensional spatial data cannot achieve intuitive and effective graphical visualization of clustering results in 2D plane. Graph data can clearly reflect the similarity relationship between objects. According to the distance of the data objects, the feature space data are modeled as graph data by iteration. Cluster analysis based on modularity is carried out on the modeling graph data. The two-dimensional visualization of non-spherical-shape distribution data cluster and result is achieved. The concept of credibility of the clustering result is proposed, and a method is proposed, …