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Full-Text Articles in Computer Engineering
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 …