Disassembly sequence planning （DSP） plays a significant role in maintenance planning of the aircraft. It is used during the design stage for the analysis of maintainability of the aircraft. To solve product disassem...Disassembly sequence planning （DSP） plays a significant role in maintenance planning of the aircraft. It is used during the design stage for the analysis of maintainability of the aircraft. To solve product disassembly sequence planning problems efficiently, a product disassembly hybrid graph model, which describes the connection, non-connection and precedence relationships between the product parts, is established based on the characteristic of disassembly. Farther, the optimization model is provided to optimize disassembly sequence. And the solution methodology based on the genetic/simulated annealing algorithm with binaxy-tree algorithm is given. Finally, an example is analyzed in detail, and the result shows that the model is correct and efficient.展开更多
In machine learning,randomness is a crucial factor in the success of ensemble learning,and it can be injected into tree-based ensembles by rotating the feature space.However,it is a common practice to rotate the featu...In machine learning,randomness is a crucial factor in the success of ensemble learning,and it can be injected into tree-based ensembles by rotating the feature space.However,it is a common practice to rotate the feature space randomly.Thus,a large number of trees are required to ensure the performance of the ensemble model.This random rotation method is theoretically feasible,but it requires massive computing resources,potentially restricting its applications.A multimodal genetic algorithm based rotation forest(MGARF)algorithm is proposed in this paper to solve this problem.It is a tree-based ensemble learning algorithm for classification,taking advantage of the characteristic of trees to inject randomness by feature rotation.However,this algorithm attempts to select a subset of more diverse and accurate base learners using the multimodal optimization method.The classification accuracy of the proposed MGARF algorithm was evaluated by comparing it with the original random forest and random rotation ensemble methods on 23 UCI classification datasets.Experimental results show that the MGARF method outperforms the other methods,and the number of base learners in MGARF models is much fewer.展开更多
在RFID网络通信中,当多个标签同时回应阅读器的查询时,如果没有相应的防冲突机制,会导致标签到阅读器的通信冲突,使得从标签返回的数据难以被阅读器正确识别.防冲突算法是阅读器快速、正确获取标签数据的关键.一种被称为基于栈的ID-二...在RFID网络通信中,当多个标签同时回应阅读器的查询时,如果没有相应的防冲突机制,会导致标签到阅读器的通信冲突,使得从标签返回的数据难以被阅读器正确识别.防冲突算法是阅读器快速、正确获取标签数据的关键.一种被称为基于栈的ID-二进制树防冲突算法(Stack-based ID-binary tree anti-collision algorithm,SIBT)被提出,SIBT算法的新颖性在于它将n个标签的ID号映射为一棵唯一对应的ID-二进制树,标签识别过程转化为在阅读器中创建ID-二进制树的过程.为了提高多标签识别效率,阅读器使用栈保存已经获取的ID-二进制树创建线索,用计数器保存标签在该栈中的深度.理论分析和仿真结果表明SIBT算法的性能优于其他基于树的防冲突算法.展开更多
以年综合费用最小为目标函数,以多种主动管理约束、分布式电源(distributed generation,DG)投资限制和电气限制为约束条件,建立了主动配电网(active distribution network,ADN)中考虑需求侧管理和网络重构的DG规划模型。根据分解协调的...以年综合费用最小为目标函数,以多种主动管理约束、分布式电源(distributed generation,DG)投资限制和电气限制为约束条件,建立了主动配电网(active distribution network,ADN)中考虑需求侧管理和网络重构的DG规划模型。根据分解协调的思想,将模型转化为三层规划模型。针对模型的特点,提出了差分进化算法、树形结构编码的单亲遗传算法和原对偶内点法相结合的混合策略对模型进行求解。在61节点ADN上对规划模型和求解方法进行了仿真和验证,研究了需求侧管理和网络重构对规划结果的影响。展开更多
基金supported by the National High Technology Research and Development Program of China(2006AA04Z427).
文摘Disassembly sequence planning （DSP） plays a significant role in maintenance planning of the aircraft. It is used during the design stage for the analysis of maintainability of the aircraft. To solve product disassembly sequence planning problems efficiently, a product disassembly hybrid graph model, which describes the connection, non-connection and precedence relationships between the product parts, is established based on the characteristic of disassembly. Farther, the optimization model is provided to optimize disassembly sequence. And the solution methodology based on the genetic/simulated annealing algorithm with binaxy-tree algorithm is given. Finally, an example is analyzed in detail, and the result shows that the model is correct and efficient.
基金Project(61603274)supported by the National Natural Science Foundation of ChinaProject(2017KJ249)supported by the Research Project of Tianjin Municipal Education Commission,China。
文摘In machine learning,randomness is a crucial factor in the success of ensemble learning,and it can be injected into tree-based ensembles by rotating the feature space.However,it is a common practice to rotate the feature space randomly.Thus,a large number of trees are required to ensure the performance of the ensemble model.This random rotation method is theoretically feasible,but it requires massive computing resources,potentially restricting its applications.A multimodal genetic algorithm based rotation forest(MGARF)algorithm is proposed in this paper to solve this problem.It is a tree-based ensemble learning algorithm for classification,taking advantage of the characteristic of trees to inject randomness by feature rotation.However,this algorithm attempts to select a subset of more diverse and accurate base learners using the multimodal optimization method.The classification accuracy of the proposed MGARF algorithm was evaluated by comparing it with the original random forest and random rotation ensemble methods on 23 UCI classification datasets.Experimental results show that the MGARF method outperforms the other methods,and the number of base learners in MGARF models is much fewer.
文摘在RFID网络通信中,当多个标签同时回应阅读器的查询时,如果没有相应的防冲突机制,会导致标签到阅读器的通信冲突,使得从标签返回的数据难以被阅读器正确识别.防冲突算法是阅读器快速、正确获取标签数据的关键.一种被称为基于栈的ID-二进制树防冲突算法(Stack-based ID-binary tree anti-collision algorithm,SIBT)被提出,SIBT算法的新颖性在于它将n个标签的ID号映射为一棵唯一对应的ID-二进制树,标签识别过程转化为在阅读器中创建ID-二进制树的过程.为了提高多标签识别效率,阅读器使用栈保存已经获取的ID-二进制树创建线索,用计数器保存标签在该栈中的深度.理论分析和仿真结果表明SIBT算法的性能优于其他基于树的防冲突算法.
文摘以年综合费用最小为目标函数,以多种主动管理约束、分布式电源(distributed generation,DG)投资限制和电气限制为约束条件,建立了主动配电网(active distribution network,ADN)中考虑需求侧管理和网络重构的DG规划模型。根据分解协调的思想,将模型转化为三层规划模型。针对模型的特点,提出了差分进化算法、树形结构编码的单亲遗传算法和原对偶内点法相结合的混合策略对模型进行求解。在61节点ADN上对规划模型和求解方法进行了仿真和验证,研究了需求侧管理和网络重构对规划结果的影响。
