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Quantitatively characterizing sandy soil structure altered by MICP using multi-level thresholding segmentation algorithm 被引量:1
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作者 Jianjun Zi Tao Liu +3 位作者 Wei Zhang Xiaohua Pan Hu Ji Honghu Zhu 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第10期4285-4299,共15页
The influences of biological,chemical,and flow processes on soil structure through microbially induced carbonate precipitation(MICP)are not yet fully understood.In this study,we use a multi-level thresholding segmenta... The influences of biological,chemical,and flow processes on soil structure through microbially induced carbonate precipitation(MICP)are not yet fully understood.In this study,we use a multi-level thresholding segmentation algorithm,genetic algorithm(GA)enhanced Kapur entropy(KE)(GAE-KE),to accomplish quantitative characterization of sandy soil structure altered by MICP cementation.A sandy soil sample was treated using MICP method and scanned by the synchrotron radiation(SR)micro-CT with a resolution of 6.5 mm.After validation,tri-level thresholding segmentation using GAE-KE successfully separated the precipitated calcium carbonate crystals from sand particles and pores.The spatial distributions of porosity,pore structure parameters,and flow characteristics were calculated for quantitative characterization.The results offer pore-scale insights into the MICP treatment effect,and the quantitative understanding confirms the feasibility of the GAE-KE multi-level thresholding segmentation algorithm. 展开更多
关键词 Soil structure MICRO-CT Multi-level thresholding MICP Genetic algorithm(GA)
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Multi-Level Image Segmentation Combining Chaotic Initialized Chimp Optimization Algorithm and Cauchy Mutation
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作者 Shujing Li Zhangfei Li +2 位作者 Wenhui Cheng Chenyang Qi Linguo Li 《Computers, Materials & Continua》 SCIE EI 2024年第8期2049-2063,共15页
To enhance the diversity and distribution uniformity of initial population,as well as to avoid local extrema in the Chimp Optimization Algorithm(CHOA),this paper improves the CHOA based on chaos initialization and Cau... To enhance the diversity and distribution uniformity of initial population,as well as to avoid local extrema in the Chimp Optimization Algorithm(CHOA),this paper improves the CHOA based on chaos initialization and Cauchy mutation.First,Sin chaos is introduced to improve the random population initialization scheme of the CHOA,which not only guarantees the diversity of the population,but also enhances the distribution uniformity of the initial population.Next,Cauchy mutation is added to optimize the global search ability of the CHOA in the process of position(threshold)updating to avoid the CHOA falling into local optima.Finally,an improved CHOA was formed through the combination of chaos initialization and Cauchy mutation(CICMCHOA),then taking fuzzy Kapur as the objective function,this paper applied CICMCHOA to natural and medical image segmentation,and compared it with four algorithms,including the improved Satin Bowerbird optimizer(ISBO),Cuckoo Search(ICS),etc.The experimental results deriving from visual and specific indicators demonstrate that CICMCHOA delivers superior segmentation effects in image segmentation. 展开更多
关键词 Image segmentation image thresholding chimp optimization algorithm chaos initialization Cauchy mutation
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AMicroseismic Signal Denoising Algorithm Combining VMD and Wavelet Threshold Denoising Optimized by BWOA
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作者 Dijun Rao Min Huang +2 位作者 Xiuzhi Shi Zhi Yu Zhengxiang He 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第10期187-217,共31页
The denoising of microseismic signals is a prerequisite for subsequent analysis and research.In this research,a new microseismic signal denoising algorithm called the Black Widow Optimization Algorithm(BWOA)optimized ... The denoising of microseismic signals is a prerequisite for subsequent analysis and research.In this research,a new microseismic signal denoising algorithm called the Black Widow Optimization Algorithm(BWOA)optimized VariationalMode Decomposition(VMD)jointWavelet Threshold Denoising(WTD)algorithm(BVW)is proposed.The BVW algorithm integrates VMD and WTD,both of which are optimized by BWOA.Specifically,this algorithm utilizes VMD to decompose the microseismic signal to be denoised into several Band-Limited IntrinsicMode Functions(BLIMFs).Subsequently,these BLIMFs whose correlation coefficients with the microseismic signal to be denoised are higher than a threshold are selected as the effective mode functions,and the effective mode functions are denoised using WTD to filter out the residual low-and intermediate-frequency noise.Finally,the denoised microseismic signal is obtained through reconstruction.The ideal values of VMD parameters and WTD parameters are acquired by searching with BWOA to achieve the best VMD decomposition performance and solve the problem of relying on experience and requiring a large workload in the application of the WTD algorithm.The outcomes of simulated experiments indicate that this algorithm is capable of achieving good denoising performance under noise of different intensities,and the denoising performance is significantly better than the commonly used VMD and Empirical Mode Decomposition(EMD)algorithms.The BVW algorithm is more efficient in filtering noise,the waveform after denoising is smoother,the amplitude of the waveform is the closest to the original signal,and the signal-to-noise ratio(SNR)and the root mean square error after denoising are more satisfying.The case based on Fankou Lead-Zinc Mine shows that for microseismic signals with different intensities of noise monitored on-site,compared with VMD and EMD,the BVW algorithm ismore efficient in filtering noise,and the SNR after denoising is higher. 展开更多
关键词 Variational mode decomposition microseismic signal DENOISING wavelet threshold denoising black widow optimization algorithm
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Defect image segmentation using multilevel thresholding based on firefly algorithm with opposition-learning 被引量:3
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作者 陈恺 戴敏 +2 位作者 张志胜 陈平 史金飞 《Journal of Southeast University(English Edition)》 EI CAS 2014年第4期434-438,共5页
To segment defects from the quad flat non-lead QFN package surface a multilevel Otsu thresholding method based on the firefly algorithm with opposition-learning is proposed. First the Otsu thresholding algorithm is ex... To segment defects from the quad flat non-lead QFN package surface a multilevel Otsu thresholding method based on the firefly algorithm with opposition-learning is proposed. First the Otsu thresholding algorithm is expanded to a multilevel Otsu thresholding algorithm. Secondly a firefly algorithm with opposition-learning OFA is proposed.In the OFA opposite fireflies are generated to increase the diversity of the fireflies and improve the global search ability. Thirdly the OFA is applied to searching multilevel thresholds for image segmentation. Finally the proposed method is implemented to segment the QFN images with defects and the results are compared with three methods i.e. the exhaustive search method the multilevel Otsu thresholding method based on particle swarm optimization and the multilevel Otsu thresholding method based on the firefly algorithm. Experimental results show that the proposed method can segment QFN surface defects images more efficiently and at a greater speed than that of the other three methods. 展开更多
关键词 quad flat non-lead QFN surface defects opposition-learning firefly algorithm multilevel Otsu thresholding algorithm
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基于改进FISTA的高分辨率声源定位方法
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作者 邓如朝 杨祥国 +4 位作者 李昌伟 张梦如 陈宁芳 杨萍 李昕 《声学技术》 CSCD 北大核心 2024年第3期440-450,共11页
为提高快速迭代收缩阈值算法(Fast Iterative Shrinkage-Thresholding Algorithm,FISTA)在反卷积波束形成中的空间分辨率以及计算速度,采用基于快速傅里叶变换的声学模型,引入过松弛方法和“贪婪”重启策略,提出两种改进的快速迭代收缩... 为提高快速迭代收缩阈值算法(Fast Iterative Shrinkage-Thresholding Algorithm,FISTA)在反卷积波束形成中的空间分辨率以及计算速度,采用基于快速傅里叶变换的声学模型,引入过松弛方法和“贪婪”重启策略,提出两种改进的快速迭代收缩阈值算法,即基于快速傅里叶变换的过松弛单调快速迭代收缩阈值算法(Over-relaxed Monotone Fast Iterative Shrinkage-Thresholding Algorithm based on Fast Fourier Transform,FFT-OMFISTA)和基于快速傅里叶变换的“贪婪”快速迭代收缩阈值算法("Greedy"Fast Iterative Shrinkage-Thresholding Algorithm based on Fast Fourier Transform,FFT-GFISTA),并应用于反卷积波束形成的求解过程中。设计了单声源和双声源的仿真与实验,验证了所提算法的有效性与优越性。结果表明,两种所提算法都具有良好的性能,都能在声源定位中实现更高的空间分辨率以及更快的计算速度。 展开更多
关键词 声源定位 反卷积 波束形成 快速迭代收缩阈值算法(FISta) 麦克风阵列
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FISTA框架下基于构造导向空变中值滤波的含异常噪声地震数据重建
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作者 张元鹏 周辉 +1 位作者 张强 方金伟 《地球物理学报》 SCIE EI CAS CSCD 北大核心 2024年第7期2785-2801,共17页
受实际环境、采集成本等因素的制约,野外观测的地震数据经常出现不规则缺失的现象.为了给后续地震资料处理和成像提供完整的数据,势必要对缺失地震道进行插值重建.基于稀疏变换的插值方法被广泛用于地震数据重建,但传统的基于稀疏变换... 受实际环境、采集成本等因素的制约,野外观测的地震数据经常出现不规则缺失的现象.为了给后续地震资料处理和成像提供完整的数据,势必要对缺失地震道进行插值重建.基于稀疏变换的插值方法被广泛用于地震数据重建,但传统的基于稀疏变换的插值方法对异常噪声非常敏感,当采集数据中存在异常噪声时会严重影响该方法的重建精度.为了克服这一问题,本文在快速迭代阈值收缩算法(FISTA)框架中引入构造导向中值滤波技术,提出了一种能同时压制异常噪声并对缺失地震道进行高精度重建的插值方法.该方法在FISTA的每次迭代中都对地震信号沿其局部倾角方向进行中值滤波以衰减异常噪声并最大限度地保护有效信号不被损害.得益于此,新方法可对含异常噪声的欠采样地震数据进行高精度重建.模型和实际数据测试均表明,当采集数据存在异常噪声时,新方法在插值精度和稳定性方面均优于传统稀疏促进插值方法. 展开更多
关键词 地震数据重建 稀疏促进 快速迭代阈值收缩 构造导向中值滤波 异常噪声
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Research on Defect Detection of Wind Turbine Blades Based on Morphology and Improved Otsu Algorithm Using Infrared Images
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作者 Shuang Kang Yinchao He +1 位作者 Wenwen Li Sen Liu 《Computers, Materials & Continua》 SCIE EI 2024年第10期933-949,共17页
To address the issues of low accuracy and high false positive rate in traditional Otsu algorithm for defect detection on infrared images of wind turbine blades(WTB),this paper proposes a technique that combines morpho... To address the issues of low accuracy and high false positive rate in traditional Otsu algorithm for defect detection on infrared images of wind turbine blades(WTB),this paper proposes a technique that combines morphological image enhancement with an improved Otsu algorithm.First,mathematical morphology’s differential multi-scale white and black top-hat operations are applied to enhance the image.The algorithm employs entropy as the objective function to guide the iteration process of image enhancement,selecting appropriate structural element scales to execute differential multi-scale white and black top-hat transformations,effectively enhancing the detail features of defect regions and improving the contrast between defects and background.Afterwards,grayscale inversion is performed on the enhanced infrared defect image to better adapt to the improved Otsu algorithm.Finally,by introducing a parameter K to adjust the calculation of inter-class variance in the Otsu method,the weight of the target pixels is increased.Combined with the adaptive iterative threshold algorithm,the threshold selection process is further fine-tuned.Experimental results show that compared to traditional Otsu algorithms and other improvements,the proposed method has significant advantages in terms of defect detection accuracy and reducing false positive rates.The average defect detection rate approaches 1,and the average Hausdorff distance decreases to 0.825,indicating strong robustness and accuracy of the method. 展开更多
关键词 Morphological enhancement improved Otsu algorithm infrared image grayscale inversion adaptive iterative thresholding
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Study and Implementation of Web Mining Classification Algorithm Based on Building Tree of Detection Class Threshold
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作者 陈俊杰 宋瀚涛 陆玉昌 《Journal of Beijing Institute of Technology》 EI CAS 2005年第2期126-129,共4页
A new classification algorithm for web mining is proposed on the basis of general classification algorithm for data mining in order to implement personalized information services. The building tree method of detecting... A new classification algorithm for web mining is proposed on the basis of general classification algorithm for data mining in order to implement personalized information services. The building tree method of detecting class threshold is used for construction of decision tree according to the concept of user expectation so as to find classification rules in different layers. Compared with the traditional C4.5 algorithm, the disadvantage of excessive adaptation in C4.5 has been improved so that classification results not only have much higher accuracy but also statistic meaning. 展开更多
关键词 data mining classification algorithm class threshold induced concept
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Implementation of Adaptive Wavelet Thresholding Denoising Algorithm Based on DSP
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作者 张雪峰 康春霞 +1 位作者 裴峰 张志杰 《Journal of Measurement Science and Instrumentation》 CAS 2011年第3期272-275,共4页
By utilizing the capability of high-speed computing,powerful real-time processing of TMS320F2812 DSP,wavelet thresholding denoising algorithm is realized based on Digital Signal Processors.Based on the multi-resolutio... By utilizing the capability of high-speed computing,powerful real-time processing of TMS320F2812 DSP,wavelet thresholding denoising algorithm is realized based on Digital Signal Processors.Based on the multi-resolution analysis of wavelet transformation,this paper proposes a new thresholding function,to some extent,to overcome the shortcomings of discontinuity in hard-thresholding function and bias in soft-thresholding function.The threshold value can be abtained adaptively according to the characteristics of wavelet coefficients of each layer by adopting adaptive threshold algorithm and then the noise is removed.The simulation results show that the improved thresholding function and the adaptive threshold algorithm have a good effect on denoising and meet the criteria of smoothness and similarity between the original signal and denoising signal. 展开更多
关键词 Mallat algorithm wavelet denoising thresholding function adaptive threshold Digital Signal Processors
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Dynamic threshold for SPWVD parameter estimation based on Otsu algorithm 被引量:10
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作者 Ning Ma Jianxin Wang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2013年第6期919-924,共6页
Time-frequency-based methods are proven to be effective for parameter estimation of linear frequency modulation (LFM) signals. The smoothed pseudo Winger-Ville distribution (SPWVD) is used for the parameter estima... Time-frequency-based methods are proven to be effective for parameter estimation of linear frequency modulation (LFM) signals. The smoothed pseudo Winger-Ville distribution (SPWVD) is used for the parameter estimation of multi-LFM signals, and a method of the SPWVD binarization by a dynamic threshold based on the Otsu algorithm is proposed. The proposed method is effective in the demand for the estimation of different parameters and the unknown signal-to-noise ratio (SNR) circumstance. The performance of this method is confirmed by numerical simulation. 展开更多
关键词 parameter estimation smoothed pseudo Winger-Ville distribution (SPWVD) dynamic threshold Otsu algorithm
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A Context Sensitive Multilevel Thresholding Using Swarm Based Algorithms 被引量:6
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作者 Shreya Pare Anil Kumar +1 位作者 Varun Bajaj Girish Kumar Singh 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2019年第6期1471-1486,共16页
In this paper, a comprehensive energy function is used to formulate the three most popular objective functions:Kapur's, Otsu and Tsalli's functions for performing effective multilevel color image thresholding.... In this paper, a comprehensive energy function is used to formulate the three most popular objective functions:Kapur's, Otsu and Tsalli's functions for performing effective multilevel color image thresholding. These new energy based objective criterions are further combined with the proficient search capability of swarm based algorithms to improve the efficiency and robustness. The proposed multilevel thresholding approach accurately determines the optimal threshold values by using generated energy curve, and acutely distinguishes different objects within the multi-channel complex images. The performance evaluation indices and experiments on different test images illustrate that Kapur's entropy aided with differential evolution and bacterial foraging optimization algorithm generates the most accurate and visually pleasing segmented images. 展开更多
关键词 COLOR image segmentation Kapur's ENTROPY MULTILEVEL thresholdING OTSU method SWARM based optimization algorithms Tsalli's ENTROPY
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An Improved Artificial Immune Algorithm with a Dynamic Threshold 被引量:5
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作者 Zhang Qiao Xu Xu Liang Yan-chun 《Journal of Bionic Engineering》 SCIE EI CSCD 2006年第2期93-97,共5页
An improved artificial immune algorithm with a dynamic threshold is presented. The calculation for the affinity function in the real-valued coding artificial immune algorithm is modified through considering the antib... An improved artificial immune algorithm with a dynamic threshold is presented. The calculation for the affinity function in the real-valued coding artificial immune algorithm is modified through considering the antibody's fitness and setting the dynamic threshold value. Numerical experiments show that compared with the genetic algorithm and the originally real-valued coding artificial immune algorithm, the improved algorithm possesses high speed of convergence and good performance for preventing premature convergence. 展开更多
关键词 dynamic threshold artificial immune algorithm genetic algorithm ANTIBODY
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Solving algorithm for TA optimization model based on ACO-SA 被引量:4
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作者 Jun Wang Xiaoguang Gao Yongwen Zhu 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2011年第4期628-639,共12页
An ant colony optimization (ACO)-simulated annealing (SA)-based algorithm is developed for the target assignment problem (TAP) in the air defense (AD) command and control (C2) system of surface to air missi... An ant colony optimization (ACO)-simulated annealing (SA)-based algorithm is developed for the target assignment problem (TAP) in the air defense (AD) command and control (C2) system of surface to air missile (SAM) tactical unit. The accomplishment process of target assignment (TA) task is analyzed. A firing advantage degree (FAD) concept of fire unit (FU) intercepting targets is put forward and its evaluation model is established by using a linear weighted synthetic method. A TA optimization model is presented and its solving algorithms are designed respectively based on ACO and SA. A hybrid optimization strategy is presented and developed synthesizing the merits of ACO and SA. The simulation examples show that the model and algorithms can meet the solving requirement of TAP in AD combat. 展开更多
关键词 target assignment (ta OPTIMIZATION ant colony optimization (ACO) algorithm simulated annealing (SA) algorithm hybrid optimization strategy.
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Fast recursive algorithm for two-dimensional Tsallis entropy thresholding method 被引量:2
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作者 Tang Yinggan Di Qiuyan Guan Xinping 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2009年第3期619-624,共6页
Recently, a two-dimensional (2-D) Tsallis entropy thresholding method has been proposed as a new method for image segmentation. But the computation complexity of 2-D Tsallis entropy is very large and becomes an obst... Recently, a two-dimensional (2-D) Tsallis entropy thresholding method has been proposed as a new method for image segmentation. But the computation complexity of 2-D Tsallis entropy is very large and becomes an obstacle to real time image processing systems. A fast recursive algorithm for 2-D Tsallis entropy thresholding is proposed. The key variables involved in calculating 2-D Tsallis entropy are written in recursive form. Thus, many repeating calculations are avoided and the computation complexity reduces to O(L2) from O(L4). The effectiveness of the proposed algorithm is illustrated by experimental results. 展开更多
关键词 image segmentation thresholdING Tsallis entropy fast recursive algorithm
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Image Segmentation of Brain MR Images Using Otsu’s Based Hybrid WCMFO Algorithm 被引量:6
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作者 A.Renugambal K.Selva Bhuvaneswari 《Computers, Materials & Continua》 SCIE EI 2020年第8期681-700,共20页
In this study,a novel hybrid Water Cycle Moth-Flame Optimization(WCMFO)algorithm is proposed for multilevel thresholding brain image segmentation in Magnetic Resonance(MR)image slices.WCMFO constitutes a hybrid betwee... In this study,a novel hybrid Water Cycle Moth-Flame Optimization(WCMFO)algorithm is proposed for multilevel thresholding brain image segmentation in Magnetic Resonance(MR)image slices.WCMFO constitutes a hybrid between the two techniques,comprising the water cycle and moth-flame optimization algorithms.The optimal thresholds are obtained by maximizing the between class variance(Otsu’s function)of the image.To test the performance of threshold searching process,the proposed algorithm has been evaluated on standard benchmark of ten axial T2-weighted brain MR images for image segmentation.The experimental outcomes infer that it produces better optimal threshold values at a greater and quicker convergence rate.In contrast to other state-of-the-art methods,namely Adaptive Wind Driven Optimization(AWDO),Adaptive Bacterial Foraging(ABF)and Particle Swarm Optimization(PSO),the proposed algorithm has been found to be better at producing the best objective function,Peak Signal-to-Noise Ratio(PSNR),Standard Deviation(STD)and lower computational time values.Further,it was observed thatthe segmented image gives greater detail when the threshold level increases.Moreover,the statistical test result confirms that the best and mean values are almost zero and the average difference between best and mean value 1.86 is obtained through the 30 executions of the proposed algorithm.Thus,these images will lead to better segments of gray,white and cerebrospinal fluid that enable better clinical choices and diagnoses using a proposed algorithm. 展开更多
关键词 Hybrid WCMFO algorithm Otsu’s function multilevel thresholding image segmentation brain MR image
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Sustainable Investment Forecasting of Power Grids Based on theDeep Restricted Boltzmann Machine Optimized by the Lion Algorithm 被引量:3
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作者 Qian Wang Xiaolong Yang +1 位作者 Di Pu Yingying Fan 《Computer Modeling in Engineering & Sciences》 SCIE EI 2022年第1期269-286,共18页
This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine(DRBM)optimized by the Lion algorithm(LA).Firstly,two factors including transmission and distribution pric... This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine(DRBM)optimized by the Lion algorithm(LA).Firstly,two factors including transmission and distribution price reform(TDPR)and 5G station construction were comprehensively incorporated into the consideration of influencing factors,and the fuzzy threshold method was used to screen out critical influencing factors.Then,the LA was used to optimize the parameters of the DRBM model to improve the model’s prediction accuracy,and the model was trained with the selected influencing factors and investment.Finally,the LA-DRBM model was used to predict the investment of a power grid enterprise,and the final prediction result was obtained by modifying the initial result with the modifying factors.The LA-DRBMmodel compensates for the deficiency of the singlemodel,and greatly improves the investment prediction accuracy of the power grid.In this study,a power grid enterprise was taken as an example to carry out an empirical analysis to prove the validity of the model,and a comparison with the RBM,support vector machine(SVM),back propagation neural network(BPNN),and regression model was conducted to verify the superiority of the model.The conclusion indicates that the proposed model has a strong generalization ability and good robustness,is able to abstract the combination of low-level features into high-level features,and can improve the efficiency of the model’s calculations for investment prediction of power grid enterprises. 展开更多
关键词 Lion algorithm deep restricted boltzmann machine fuzzy threshold method power grid investment forecasting
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A novel adjustable multiple cross-hexagonal search algorithm for fast block motion estimation 被引量:2
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作者 XIE Chun-lai CHEUNG Chun-ho LIU Wei-zhong 《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 SCIE EI CAS CSCD 2007年第8期1304-1310,共7页
In this paper,we propose a novel adjustable multiple cross-hexagonal search(AMCHS) algorithm for fast block motion estimation. It employs adjustable multiple cross search patterns(AMCSP) in the first step and then use... In this paper,we propose a novel adjustable multiple cross-hexagonal search(AMCHS) algorithm for fast block motion estimation. It employs adjustable multiple cross search patterns(AMCSP) in the first step and then uses half-way-skip and half-way-stop technique to determine whether to employ two hexagonal search patterns(HSPs) subsequently. The AMCSP can be used to find small motion vectors efficiently while the HSPs can be used to find large ones accurately to ensure prediction quality. Simulation results showed that our proposed AMCHS achieves faster search speed,and provides better distortion performance than other popular fast search algorithms,such as CDS and CDHS. 展开更多
关键词 Motion estimation Fast search algorithm Adjustable search patterns threshold strategy Hexagonal search pattern
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2-D mini mumfuzzy entropy method of image thresholding based on genetic algorithm 被引量:1
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作者 张兴会 刘玲 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2005年第3期557-560,共4页
A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the chara... A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the characteristic relationship between the gray level of each pixel and the average value of its neighborhood. When the threshold is not located at the obvious and deep valley of the histgram, genetic algorithm is devoted to the problem of selecting the appropriate threshold value. The experimental results indicate that the proposed method has good performance. 展开更多
关键词 image thresholding 2-D fuzzy entropy genetic algorithm.
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‘Outbreak Gold Standard’Selection to Provide Optimized Threshold for Infectious Diseases Early-alert Based on China Infectious Disease Automated-alert and Response System 被引量:5
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作者 王瑞平 姜永根 +2 位作者 赵根明 郭晓芹 Engelgau Michael 《Journal of Huazhong University of Science and Technology(Medical Sciences)》 SCIE CAS 2017年第6期833-841,共9页
The China Infectious Disease Automated-alert and Response System(CIDARS) was successfully implemented and became operational nationwide in 2008. The CIDARS plays an important role in and has been integrated into the... The China Infectious Disease Automated-alert and Response System(CIDARS) was successfully implemented and became operational nationwide in 2008. The CIDARS plays an important role in and has been integrated into the routine outbreak monitoring efforts of the Center for Disease Control(CDC) at all levels in China. In the CIDARS, thresholds are determined using the ?Mean+2SD? in the early stage which have limitations. This study compared the performance of optimized thresholds defined using the ?Mean +2SD? method to the performance of 5 novel algorithms to select optimal ?Outbreak Gold Standard(OGS)? and corresponding thresholds for outbreak detection. Data for infectious disease were organized by calendar week and year. The ?Mean+2 SD?, C1, C2, moving average(MA), seasonal model(SM), and cumulative sum(CUSUM) algorithms were applied. Outbreak signals for the predicted value(Px) were calculated using a percentile-based moving window. When the outbreak signals generated by an algorithm were in line with a Px generated outbreak signal for each week, this Px was then defined as the optimized threshold for that algorithm. In this study, six infectious diseases were selected and classified into TYPE A(chickenpox and mumps), TYPE B(influenza and rubella) and TYPE C [hand foot and mouth disease(HFMD) and scarlet fever]. Optimized thresholds for chickenpox(P_(55)), mumps(P_(50)), influenza(P_(40), P_(55), and P_(75)), rubella(P_(45) and P_(75)), HFMD(P_(65) and P_(70)), and scarlet fever(P_(75) and P_(80)) were identified. The C1, C2, CUSUM, SM, and MA algorithms were appropriate for TYPE A. All 6 algorithms were appropriate for TYPE B. C1 and CUSUM algorithms were appropriate for TYPE C. It is critical to incorporate more flexible algorithms as OGS into the CIDRAS and to identify the proper OGS and corresponding recommended optimized threshold by different infectious disease types. 展开更多
关键词 outbreak gold standard optimized threshold algorithms early-alert signal China Infectious Disease Automated-alert and Response System
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Dynamic Threshold-Based Approach to Detect Low-Rate DDoS Attacks on Software-Defined Networking Controller 被引量:1
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作者 Mohammad Adnan Aladaileh Mohammed Anbar +2 位作者 Iznan H.Hasbullah Abdullah Ahmed Bahashwan Shadi Al-Sarawn 《Computers, Materials & Continua》 SCIE EI 2022年第10期1403-1416,共14页
The emergence of a new network architecture,known as Software Defined Networking(SDN),in the last two decades has overcome some drawbacks of traditional networks in terms of performance,scalability,reliability,securit... The emergence of a new network architecture,known as Software Defined Networking(SDN),in the last two decades has overcome some drawbacks of traditional networks in terms of performance,scalability,reliability,security,and network management.However,the SDN is vulnerable to security threats that target its controller,such as low-rate Distributed Denial of Service(DDoS)attacks,The low-rate DDoS attack is one of the most prevalent attacks that poses a severe threat to SDN network security because the controller is a vital architecture component.Therefore,there is an urgent need to propose a detection approach for this type of attack with a high detection rate and low false-positive rates.Thus,this paper proposes an approach to detect low-rate DDoS attacks on the SDN controller by adapting a dynamic threshold.The proposed approach has been evaluated using four simulation scenarios covering a combination of low-rate DDoS attacks against the SDN controller involving(i)a single host attack targeting a single victim;(ii)a single host attack targeting multiple victims;(iii)multiple hosts attack targeting a single victim;and(iv)multiple hosts attack targeting multiple victims.The proposed approach’s average detection rates are 96.65%,91.83%,96.17%,and 95.33%for the above scenarios,respectively;and its average false-positive rates are 3.33%,8.17%,3.83%,and 4.67%for similar scenarios,respectively.The comparison between the proposed approach and two existing approaches showed that it outperformed them in both categories. 展开更多
关键词 Attack detection CONTROLLER dynamic threshold entropy algorithm distributed denial of service software defined networking static threshold
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