Augmentation of abnormal cells in the brain causes brain tumor(BT),and early screening and treatmentwill reduce its harshness in patients.BT’s clinical level screening is usually performed with Magnetic Resonance Ima...Augmentation of abnormal cells in the brain causes brain tumor(BT),and early screening and treatmentwill reduce its harshness in patients.BT’s clinical level screening is usually performed with Magnetic Resonance Imaging(MRI)due to its multi-modality nature.The overall aims of the study is to introduce,test and verify an advanced image processing technique with algorithms to automatically extract tumour sections from brain MRI scans,facilitating improved accuracy.The research intends to devise a reliable framework for detecting the BT region in the twodimensional(2D)MRI slice,and identifying its class with improved accuracy.The methodology for the devised framework comprises the phases of:(i)Collection and resizing of images,(ii)Implementation and Segmentation of Convolutional Neural Network(CNN),(iii)Deep feature extraction,(iv)Handcrafted feature extraction,(v)Moth-Flame-Algorithm(MFA)supported feature reduction,and(vi)Performance evaluation.This study utilized clinical-grade brain MRI of BRATS and TCIA datasets for the investigation.This framework segments detected the glioma(low/high grade)and glioblastoma class BT.This work helped to get a segmentation accuracy of over 98%with VGG-UNet and a classification accuracy of over 98%with the VGG16 scheme.This study has confirmed that the implemented framework is very efficient in detecting the BT in MRI slices with/without the skull section.展开更多
针对新能源渗透率提升带来的电压稳定风险,同时考虑柔性互联装置逐步在电力系统试点应用的背景,提出一种考虑电压稳定的含智能储能软开关(soft open point with energy storage system integration,E-SOP)配电系统分布式电源双层规划模...针对新能源渗透率提升带来的电压稳定风险,同时考虑柔性互联装置逐步在电力系统试点应用的背景,提出一种考虑电压稳定的含智能储能软开关(soft open point with energy storage system integration,E-SOP)配电系统分布式电源双层规划模型。首先,分析电压稳定指标及E-SOP的作用机理。其次,基于拉丁超立方采样和经K-medoids算法融合的改进同步回代缩减法得到典型概率日场景。然后,建立含E-SOP接入的双层规划模型,上层模型以年综合费用最小为目标,对风电、光伏等设备进行选址定容;下层模型以电压稳定性、网络损耗、平均电压偏移等为目标,实施含E-SOP的有功无功协同优化。最后,采用改进飞蛾扑火算法进行模型求解。经IEEE 33节点配电系统算例分析,其结果表明,该模型能有效提高配电系统的经济性和实时运行的电压稳定性,验证了求解算法的优越性。展开更多
针对当前网络入侵检测中的数据量较大、数据维度较高的特点,将飞蛾扑火优化(MFO)算法应用于网络入侵检测的特征选择中。鉴于MFO算法收敛过快、易陷入局部最优的问题,提出一种融合粒子群优化(PSO)的二进制飞蛾扑火优化(BPMFO)算法。该算...针对当前网络入侵检测中的数据量较大、数据维度较高的特点,将飞蛾扑火优化(MFO)算法应用于网络入侵检测的特征选择中。鉴于MFO算法收敛过快、易陷入局部最优的问题,提出一种融合粒子群优化(PSO)的二进制飞蛾扑火优化(BPMFO)算法。该算法引入MFO螺旋飞行公式,具有较强的局部搜索能力;结合了粒子群优化(PSO)算法的速度更新方法,让种群个体随着全局最优解和历史最优解的方向移动,增强算法的全局收敛性,从而避免易陷入局部最优。仿真实验以KDD CUP 99数据集为实验基础,分别采用支持向量机(SVM)、K最近邻(KNN)算法和朴素贝叶斯(NBC)3种分类器,与二进制飞蛾扑火优化(BMFO)算法、二进制粒子群优化(BPSO)算法、二进制遗传算法(BGA)、二进制灰狼优化(BGWO)算法和二进制布谷鸟搜索(BCS)算法进行了实验对比。实验结果表明,BPMFO算法应用于网络入侵检测的特征选择时,在算法精度、运行效率、稳定性、收敛速度以及跳出局部最优的综合性能上具有明显优势。展开更多
文摘Augmentation of abnormal cells in the brain causes brain tumor(BT),and early screening and treatmentwill reduce its harshness in patients.BT’s clinical level screening is usually performed with Magnetic Resonance Imaging(MRI)due to its multi-modality nature.The overall aims of the study is to introduce,test and verify an advanced image processing technique with algorithms to automatically extract tumour sections from brain MRI scans,facilitating improved accuracy.The research intends to devise a reliable framework for detecting the BT region in the twodimensional(2D)MRI slice,and identifying its class with improved accuracy.The methodology for the devised framework comprises the phases of:(i)Collection and resizing of images,(ii)Implementation and Segmentation of Convolutional Neural Network(CNN),(iii)Deep feature extraction,(iv)Handcrafted feature extraction,(v)Moth-Flame-Algorithm(MFA)supported feature reduction,and(vi)Performance evaluation.This study utilized clinical-grade brain MRI of BRATS and TCIA datasets for the investigation.This framework segments detected the glioma(low/high grade)and glioblastoma class BT.This work helped to get a segmentation accuracy of over 98%with VGG-UNet and a classification accuracy of over 98%with the VGG16 scheme.This study has confirmed that the implemented framework is very efficient in detecting the BT in MRI slices with/without the skull section.
文摘针对新能源渗透率提升带来的电压稳定风险,同时考虑柔性互联装置逐步在电力系统试点应用的背景,提出一种考虑电压稳定的含智能储能软开关(soft open point with energy storage system integration,E-SOP)配电系统分布式电源双层规划模型。首先,分析电压稳定指标及E-SOP的作用机理。其次,基于拉丁超立方采样和经K-medoids算法融合的改进同步回代缩减法得到典型概率日场景。然后,建立含E-SOP接入的双层规划模型,上层模型以年综合费用最小为目标,对风电、光伏等设备进行选址定容;下层模型以电压稳定性、网络损耗、平均电压偏移等为目标,实施含E-SOP的有功无功协同优化。最后,采用改进飞蛾扑火算法进行模型求解。经IEEE 33节点配电系统算例分析,其结果表明,该模型能有效提高配电系统的经济性和实时运行的电压稳定性,验证了求解算法的优越性。
文摘针对当前网络入侵检测中的数据量较大、数据维度较高的特点,将飞蛾扑火优化(MFO)算法应用于网络入侵检测的特征选择中。鉴于MFO算法收敛过快、易陷入局部最优的问题,提出一种融合粒子群优化(PSO)的二进制飞蛾扑火优化(BPMFO)算法。该算法引入MFO螺旋飞行公式,具有较强的局部搜索能力;结合了粒子群优化(PSO)算法的速度更新方法,让种群个体随着全局最优解和历史最优解的方向移动,增强算法的全局收敛性,从而避免易陷入局部最优。仿真实验以KDD CUP 99数据集为实验基础,分别采用支持向量机(SVM)、K最近邻(KNN)算法和朴素贝叶斯(NBC)3种分类器,与二进制飞蛾扑火优化(BMFO)算法、二进制粒子群优化(BPSO)算法、二进制遗传算法(BGA)、二进制灰狼优化(BGWO)算法和二进制布谷鸟搜索(BCS)算法进行了实验对比。实验结果表明,BPMFO算法应用于网络入侵检测的特征选择时,在算法精度、运行效率、稳定性、收敛速度以及跳出局部最优的综合性能上具有明显优势。
