Binary Decision Diagrams (BDDs) can be graphically manipulated to reduce the number of nodes and hence the area. In this context, ordering of BDDs play a major role. Most of the algorithms for input variable ordering ...Binary Decision Diagrams (BDDs) can be graphically manipulated to reduce the number of nodes and hence the area. In this context, ordering of BDDs play a major role. Most of the algorithms for input variable ordering of OBDD focus primarily on area minimization. However, suitable input variable ordering helps in minimizing the power consumption also. In this particular work, we have proposed two algorithms namely, a genetic algorithm based technique and a branch and bound algorithm to find an optimal input variable order. Of course, the node reordering is taken care of by the standard BDD package buddy-2.4. Moreover, we have evaluated the performances of the proposed algorithms by running an exhaustive search program. Experi-mental results show a substantial saving in area and power. We have also compared our techniques with other state-of-art techniques of variable ordering for OBDDs and found to give superior results.展开更多
Based on the principle of “pre-disaster prevention outweighs rescue during disasters”, this study targets areas threatened by natural disasters, and develops an automatic algorithm based on the Prim algorithm to ser...Based on the principle of “pre-disaster prevention outweighs rescue during disasters”, this study targets areas threatened by natural disasters, and develops an automatic algorithm based on the Prim algorithm to serve as an automatic identification system. In the face of natural disasters that disable key facilities in the region and prevent settlements from contacting the outside world or outsiders from sending rescuers to the settlements, the proposed system helps to identify whether these regions will become isolated areas and conduct disaster mitigation and relief resource allocation before any natural disaster in order to reduce potential disaster losses. An automatic identification system, based on the threshold of channel blocking due to broken roads and bridges, determines through the decision tree model and relevant patterns whether such regions will become isolated areas by identifying areas based on the results of model analysis. The proposed system’s identification results are verified by actual case histories and comparisons;the results can be used to correctly identify isolated areas. Finally, Microsoft Visual Studio C # and Google Map are employed to apply the results and to produce an information mode for the determination and decision support of isolated areas affected by natural disasters.展开更多
巷道断面成形是煤矿掘进过程中的重要工序,但目前的巷道断面成形作业多为人工控制掘进机进行往复式截割,制约了煤矿掘进工作面的智能化发展。为此,针对断面成形轨迹规划未考虑煤岩特征、优化目标单一的问题,提出了一种基于改进灰狼优化(...巷道断面成形是煤矿掘进过程中的重要工序,但目前的巷道断面成形作业多为人工控制掘进机进行往复式截割,制约了煤矿掘进工作面的智能化发展。为此,针对断面成形轨迹规划未考虑煤岩特征、优化目标单一的问题,提出了一种基于改进灰狼优化(grey wolf optimizer, GWO)算法的掘进机断面成形轨迹规划方法。首先,根据夹矸位置将待截割断面环境分为4种情况,对相应断面进行栅格化处理并建立栅格地图,同时采用二值膨胀法对不规则夹矸进行膨胀化处理。然后,对GWO算法进行了改进,以提升其寻优性能和收敛速度。接着,开展了仿真实验,利用改进GWO算法实现了4种环境下掘进机断面成形轨迹的规划。最后,利用掘进机样机开展了断面截割实验。仿真结果表明:相较于传统的GWO算法,改进GWO算法的收敛速度更快且收敛精度更高;在4种断面环境下,基于改进GWO算法规划的断面成形轨迹长度最短,欠挖面积最小,转向次数最少,更容易实现高精度、高效率的轨迹跟踪控制,保证了巷道断面的成形质量。实验结果表明,基于改进GWO算法规划的断面成形轨迹既能提高掘进机的截割效率,又能满足巷道断面成形的质量要求。研究结果可为煤矿井下智能掘进技术的发展提供新的思路和方法。展开更多
Air route network(ARN)planning is an efficient way to alleviate civil aviation flight delays caused by increasing development and pressure for safe operation.Here,the ARN shortest path was taken as the objective funct...Air route network(ARN)planning is an efficient way to alleviate civil aviation flight delays caused by increasing development and pressure for safe operation.Here,the ARN shortest path was taken as the objective function,and an air route network node(ARNN)optimization model was developed to circumvent the restrictions imposed by″three areas″,also known as prohibited areas,restricted areas,and dangerous areas(PRDs),by creating agrid environment.And finally the objective function was solved by means of an adaptive ant colony algorithm(AACA).The A593,A470,B221,and G204 air routes in the busy ZSHA flight information region,where the airspace includes areas with different levels of PRDs,were taken as an example.Based on current flight patterns,a layout optimization of the ARNN was computed using this model and algorithm and successfully avoided PRDs.The optimized result reduced the total length of routes by 2.14% and the total cost by 9.875%.展开更多
针对快速扩展随机树(Rapidly-exploring Random Tree,RRT)算法及其衍生算法路径规划时间长且规划效率低的问题,提出RRT算法与人工势场法结合的PAAPF-RRT机械臂路径规划算法,旨在最短的时间、最小的迭代次数内,在静态环境中找到连接起始...针对快速扩展随机树(Rapidly-exploring Random Tree,RRT)算法及其衍生算法路径规划时间长且规划效率低的问题,提出RRT算法与人工势场法结合的PAAPF-RRT机械臂路径规划算法,旨在最短的时间、最小的迭代次数内,在静态环境中找到连接起始点与终点的最优路径。首先,引入基于地图障碍物分布评估策略和采样区域优化策略,根据地图的障碍物分布、数量调整算法的步长以及偏向概率。然后,伴随随机树的生长,更新随机点的采样区域,保证随机树向目标点生长。其次,将RRT算法与人工势场法结合,当随机树与障碍物发生碰撞时,使用人工势场法引导随机树节点生长避开障碍物,解决了RRT算法随机树生长到障碍物附近且朝目标点生长的方向被障碍物遮挡时随机树无法生长的问题。最后,利用节点修剪策略,把算法生成的初始路径中的冗余节点进行修剪,得到拐点更少、路径更简洁的优化路径。实验结果表明,PAAPF-RRT算法在路径规划时间上对于RRT算法、GB-RRT算法以及RRT*算法分别减少了93.64%、73.58%、93.28%,在迭代次数方面分别下降了91.40%、79.64%、90.58%,在路径长度方面只占其他3种算法的79.34%、86.21%、95.58%。展开更多
针对RRT(rapidly exploring random tree)路径规划算法搜索范围大、目标导向差、容易陷入局部最小值以及路径曲折等问题,提出了一种限制自适应采样区域的改进RRT路径规划算法。将整个搜索空间划分成均匀的等级,根据新节点所在等级和该...针对RRT(rapidly exploring random tree)路径规划算法搜索范围大、目标导向差、容易陷入局部最小值以及路径曲折等问题,提出了一种限制自适应采样区域的改进RRT路径规划算法。将整个搜索空间划分成均匀的等级,根据新节点所在等级和该等级内采样点数量动态调整采样区域,减小搜索范围;利用新节点改进策略使随机树根据环境信息自适应地向目标点调整,并改变扩展步长生成新节点;利用障碍物躲避策略提高算法的目标导向性和躲避障碍物的性能;利用改进的逆向寻优和插入节点并减小转向角的三次B样条曲线对路径进行优化处理。该算法在不同的路径环境中相较于RRT算法的搜索时间和迭代次数均减少了70%以上,且经过优化的路径更短、更平滑。展开更多
文摘Binary Decision Diagrams (BDDs) can be graphically manipulated to reduce the number of nodes and hence the area. In this context, ordering of BDDs play a major role. Most of the algorithms for input variable ordering of OBDD focus primarily on area minimization. However, suitable input variable ordering helps in minimizing the power consumption also. In this particular work, we have proposed two algorithms namely, a genetic algorithm based technique and a branch and bound algorithm to find an optimal input variable order. Of course, the node reordering is taken care of by the standard BDD package buddy-2.4. Moreover, we have evaluated the performances of the proposed algorithms by running an exhaustive search program. Experi-mental results show a substantial saving in area and power. We have also compared our techniques with other state-of-art techniques of variable ordering for OBDDs and found to give superior results.
文摘Based on the principle of “pre-disaster prevention outweighs rescue during disasters”, this study targets areas threatened by natural disasters, and develops an automatic algorithm based on the Prim algorithm to serve as an automatic identification system. In the face of natural disasters that disable key facilities in the region and prevent settlements from contacting the outside world or outsiders from sending rescuers to the settlements, the proposed system helps to identify whether these regions will become isolated areas and conduct disaster mitigation and relief resource allocation before any natural disaster in order to reduce potential disaster losses. An automatic identification system, based on the threshold of channel blocking due to broken roads and bridges, determines through the decision tree model and relevant patterns whether such regions will become isolated areas by identifying areas based on the results of model analysis. The proposed system’s identification results are verified by actual case histories and comparisons;the results can be used to correctly identify isolated areas. Finally, Microsoft Visual Studio C # and Google Map are employed to apply the results and to produce an information mode for the determination and decision support of isolated areas affected by natural disasters.
文摘巷道断面成形是煤矿掘进过程中的重要工序,但目前的巷道断面成形作业多为人工控制掘进机进行往复式截割,制约了煤矿掘进工作面的智能化发展。为此,针对断面成形轨迹规划未考虑煤岩特征、优化目标单一的问题,提出了一种基于改进灰狼优化(grey wolf optimizer, GWO)算法的掘进机断面成形轨迹规划方法。首先,根据夹矸位置将待截割断面环境分为4种情况,对相应断面进行栅格化处理并建立栅格地图,同时采用二值膨胀法对不规则夹矸进行膨胀化处理。然后,对GWO算法进行了改进,以提升其寻优性能和收敛速度。接着,开展了仿真实验,利用改进GWO算法实现了4种环境下掘进机断面成形轨迹的规划。最后,利用掘进机样机开展了断面截割实验。仿真结果表明:相较于传统的GWO算法,改进GWO算法的收敛速度更快且收敛精度更高;在4种断面环境下,基于改进GWO算法规划的断面成形轨迹长度最短,欠挖面积最小,转向次数最少,更容易实现高精度、高效率的轨迹跟踪控制,保证了巷道断面的成形质量。实验结果表明,基于改进GWO算法规划的断面成形轨迹既能提高掘进机的截割效率,又能满足巷道断面成形的质量要求。研究结果可为煤矿井下智能掘进技术的发展提供新的思路和方法。
基金supported by the the Youth Science and Technology Innovation Fund (Science)(Nos.NS2014070, NS2014070)
文摘Air route network(ARN)planning is an efficient way to alleviate civil aviation flight delays caused by increasing development and pressure for safe operation.Here,the ARN shortest path was taken as the objective function,and an air route network node(ARNN)optimization model was developed to circumvent the restrictions imposed by″three areas″,also known as prohibited areas,restricted areas,and dangerous areas(PRDs),by creating agrid environment.And finally the objective function was solved by means of an adaptive ant colony algorithm(AACA).The A593,A470,B221,and G204 air routes in the busy ZSHA flight information region,where the airspace includes areas with different levels of PRDs,were taken as an example.Based on current flight patterns,a layout optimization of the ARNN was computed using this model and algorithm and successfully avoided PRDs.The optimized result reduced the total length of routes by 2.14% and the total cost by 9.875%.
文摘针对快速扩展随机树(Rapidly-exploring Random Tree,RRT)算法及其衍生算法路径规划时间长且规划效率低的问题,提出RRT算法与人工势场法结合的PAAPF-RRT机械臂路径规划算法,旨在最短的时间、最小的迭代次数内,在静态环境中找到连接起始点与终点的最优路径。首先,引入基于地图障碍物分布评估策略和采样区域优化策略,根据地图的障碍物分布、数量调整算法的步长以及偏向概率。然后,伴随随机树的生长,更新随机点的采样区域,保证随机树向目标点生长。其次,将RRT算法与人工势场法结合,当随机树与障碍物发生碰撞时,使用人工势场法引导随机树节点生长避开障碍物,解决了RRT算法随机树生长到障碍物附近且朝目标点生长的方向被障碍物遮挡时随机树无法生长的问题。最后,利用节点修剪策略,把算法生成的初始路径中的冗余节点进行修剪,得到拐点更少、路径更简洁的优化路径。实验结果表明,PAAPF-RRT算法在路径规划时间上对于RRT算法、GB-RRT算法以及RRT*算法分别减少了93.64%、73.58%、93.28%,在迭代次数方面分别下降了91.40%、79.64%、90.58%,在路径长度方面只占其他3种算法的79.34%、86.21%、95.58%。
文摘针对RRT(rapidly exploring random tree)路径规划算法搜索范围大、目标导向差、容易陷入局部最小值以及路径曲折等问题,提出了一种限制自适应采样区域的改进RRT路径规划算法。将整个搜索空间划分成均匀的等级,根据新节点所在等级和该等级内采样点数量动态调整采样区域,减小搜索范围;利用新节点改进策略使随机树根据环境信息自适应地向目标点调整,并改变扩展步长生成新节点;利用障碍物躲避策略提高算法的目标导向性和躲避障碍物的性能;利用改进的逆向寻优和插入节点并减小转向角的三次B样条曲线对路径进行优化处理。该算法在不同的路径环境中相较于RRT算法的搜索时间和迭代次数均减少了70%以上,且经过优化的路径更短、更平滑。
