A group of statistical algorithms are proposed for the inversion of the three major components of CaseII waters inthe coastal area of the Huanghai Sea and the East China Sea. The algorithms are based on the in situ da...A group of statistical algorithms are proposed for the inversion of the three major components of CaseII waters inthe coastal area of the Huanghai Sea and the East China Sea. The algorithms are based on the in situ data collected inthe spring of 2003 with strict quality assurance according to NASA ocean bio-optic protocols. These algorithms arethe first ones with quantitative confidence that can be applied for the area. The average relative error of the inversedand in situ measured components' concentrations are: Chl-a about 37%, total suspended matter (TSM) about 25%,respectively. This preliminary result is quite satisfactory for CaseII waters, although some aspects in the modelneed further study. The sensitivity of the input error of 5% to remote sensing reflectance (Rrs) is also analyzed andit shows the algorithms are quite stable. The algorithms show a large difference with Tassans local SeaWiFSalgorithms for different waters, except for the Chl-a algorithm.展开更多
This paper suggests a group of statistical algorithms for calculating the total absorption coefficients based on in situ data of apparent optical property and inherent optical property collected with strict quality as...This paper suggests a group of statistical algorithms for calculating the total absorption coefficients based on in situ data of apparent optical property and inherent optical property collected with strict quality assurance according to NASA ocean bio-optic protocols in the Yellow Sea and the East China Sea in spring 2003. The band-ratios ofRrs412/Rrs555, Rrs49o/Rrs555 are used in the algorithms to derive the total absorption coefficients （at） at 412, 440, 488, 510, 532 and 555nm bands, respectively. The average relative errors between inversed and measured values are less than 25.8%, with the correlative coefficients （R2） being 0.75-0.85. Error sensitivity analysis shows that the maximum retrieval error is less than 24.0% at ＋5% error in Rrs＇s. So the statistical algorithms of this paper are practicable. In this paper, the relations between the total absorption coefficients at 412, 488, 510, 532, 555 nm and that of 440nm are also studied. The results show that the relations between the total absorption coefficients of 400-600 nm and that of 440 nm are correlated well and all of their correlative coefficients R2 are greater than 0.99. Furthermore, a regression analysis is also done for the slope of the linear relations and wavelengths, and the R2 is also 0.99. Thus it is possible to retrieve other bands＇ total absorption coefficients with only one band absorption value, which significantly reduce the number of unknown parameters in studying other ocean color related problems.展开更多
Integrated use of statistical process control (SPC) and engineering process control (EPC) has better performance than that by solely using SPC or EPC. But integrated scheme has resulted in the problem of “Window of O...Integrated use of statistical process control (SPC) and engineering process control (EPC) has better performance than that by solely using SPC or EPC. But integrated scheme has resulted in the problem of “Window of Opportunity” and autocorrelation. In this paper, advanced T2 statistics model and neural networks scheme are combined to solve the above problems: use T2 statistics technique to solve the problem of autocorrelation;adopt neural networks technique to solve the problem of “Window of Opportunity” and identification of disturbance causes. At the same time, regarding the shortcoming of neural network technique that its algorithm has a low speed of convergence and it is usually plunged into local optimum easily. Genetic algorithm was proposed to train samples in this paper. Results of the simulation ex-periments show that this method can detect the process disturbance quickly and accurately as well as identify the dis-turbance type.展开更多
Objective To evaluate the feasibility of using a low concentration of contrast medium （Visipaque 270 mgl/mL）, low tube voltage, and an advanced image reconstruction algorithm in head and neck computed tomography ang...Objective To evaluate the feasibility of using a low concentration of contrast medium （Visipaque 270 mgl/mL）, low tube voltage, and an advanced image reconstruction algorithm in head and neck computed tomography angiography （CTA）. Methods Forty patients （22 men and 18 women; average age 48.7 ± 14.25 years; average body mass index 23.9 ± 3.7 kg/m^2） undergoing CTA for suspected vascular diseases were randomly assigned into two groups. Group A （n = 20） was administered 370 mgl/mL contrast medium, and group B （n = 20） was administered 270 mgl/mL contrast medium. Both groups were administered at a rate of 4.8 mL/s and an injection volume of 0.8 mL/kg. Images of group A were obtained with 120 kVp and filtered back projection （FBP） reconstruction, whereas images of group B were obtained with 80 kVp and 80% adaptive iterative statistical reconstruction algorithm （ASiR）. The CT values and standard deviations of intracranial arteries and image noise on the corona radiata were measured to calculate the contrast-to-noise ratio （CNR） and signal-to-noise ratio （SNR）. The beam-hardening artifacts （BHAs） around the skull base were calculated. Two readers evaluated the image quality with volume rendered images using scores from 1 to 5. The values between the two groups were statistically compared. Results The mean CT value of the intracranial arteries in group B was significantly higher than that in group A （P 〈 0.001）. The CNR and SNR values in group B were also statistically higher than those in group A （P 〈 0.001）. Image noise and BHAs were not significantly different between the two groups. The image quality score of VR images of in group B was significantly higher than that in group A （P = 0.001）. However, the quality scores of axial enhancement images in group B became significantly smaller than those in group A （P〈 0.001）. The CT dose index volume and dose-length product were decreased by 63.8% and 64%, respectively, in group B （P 〈 0.001 for both）. Conclusion Visipaque combined with 80 kVp and 80% ASiR provided similar image quality in intracranial CTA with 64% radiation dose reduction compared with the use of lopamidol, 120 kVp, and FBP reconstruc-tion.展开更多
To improve the location accuracy, a hybrid location algorithm based on cuckoo and statistical manifold method is proposed. It combines the cuckoo algorithm's strong global optimization ability and the statistical ...To improve the location accuracy, a hybrid location algorithm based on cuckoo and statistical manifold method is proposed. It combines the cuckoo algorithm's strong global optimization ability and the statistical manifold<span>’</span><span>s accurate positioning ability fully. The simulation results show that the hybrid location algorithm has higher accuracy and reduces the influence of initial value selection on location accuracy.</span>展开更多
The fundamental problem of similarity studies, in the frame of data-mining, is to examine and detect similar items in articles, papers, and books with huge sizes. In this paper, we are interested in the probabilistic,...The fundamental problem of similarity studies, in the frame of data-mining, is to examine and detect similar items in articles, papers, and books with huge sizes. In this paper, we are interested in the probabilistic, and the statistical and the algorithmic aspects in studies of texts. We will be using the approach of k-shinglings, a k-shingling being defined as a sequence of k consecutive characters that are extracted from a text (k ≥ 1). The main stake in this field is to find accurate and quick algorithms to compute the similarity in short times. This will be achieved in using approximation methods. The first approximation method is statistical and, is based on the theorem of Glivenko-Cantelli. The second is the banding technique. And the third concerns a modification of the algorithm proposed by Rajaraman et al. ([1]), denoted here as (RUM). The Jaccard index is the one being used in this paper. We finally illustrate these results of the paper on the four Gospels. The results are very conclusive.展开更多
Identification of modal parameters of a linear structure with output-only measurements has received much attention over the past decades. In the paper, the Natural Excitation Technique (NExT) is used for acquisition o...Identification of modal parameters of a linear structure with output-only measurements has received much attention over the past decades. In the paper, the Natural Excitation Technique (NExT) is used for acquisition of the impulse signals from the structural responses. Then Eigensystem Realization Algorithm (ERA) is utilized for modal identification. For disregarding the fictitious ‘computational modes', a procedure, Statistically Averaging Modal Frequency Method (SAMFM), is developed to distinguish the true modes from noise modes, and to improve the precision of the identified modal frequencies of the structure. An offshore platform is modeled with the finite element method. The theoretical modal parameters are obtained for a comparison with the identified values. The dynamic responses of the platform under random wave loading are computed for providing the output signals used for identification with ERA. Results of simulation demonstrate that the proposed method can determine the system modal frequency with high precision.展开更多
In this paper,a reconfigurable intelligent surface(RIS)-assisted MIMO wireless secure communication system is considered,in which a base station(BS)equipped with multiple antennas exploits statistical channel state in...In this paper,a reconfigurable intelligent surface(RIS)-assisted MIMO wireless secure communication system is considered,in which a base station(BS)equipped with multiple antennas exploits statistical channel state information to communicate with a legitimate multi-antenna user,in the presence of an eavesdropper,also equipped with multiple antennas.We firstly obtain an analytical expression of the ergodic secrecy rate based on the results of largedimensional random matrix theory.Then,a jointly alternating optimization algorithm with the method of Taylor series expansion and the projected gradient ascent method is proposed to design the transmit covariance matrix at the BS,as well as the diagonal phaseshifting matrix to maximize the ergodic secrecy rate.Simulations are conducted to demonstrate the accuracy of the derived analytical expressions,as well as the superior performance of our proposed algorithm.展开更多
In this article, we consider a lifetime distribution, the Weibull-Logarithmic distri- bution introduced by [6]. We investigate some new statistical characterizations and properties. We develop the maximum likelihood i...In this article, we consider a lifetime distribution, the Weibull-Logarithmic distri- bution introduced by [6]. We investigate some new statistical characterizations and properties. We develop the maximum likelihood inference using EM algorithm. Asymptotic properties of the MLEs are obtained and extensive simulations are conducted to assess the performance of parameter estimation. A numerical example is used to illustrate the application.展开更多
A multiple model tracking algorithm based on neural network and multiple-process noise soft-switching for maneuvering targets is presented.In this algorithm, the＂current＂statistical model and neural network are runn...A multiple model tracking algorithm based on neural network and multiple-process noise soft-switching for maneuvering targets is presented.In this algorithm, the＂current＂statistical model and neural network are running in parallel.The neural network algorithm is used to modify the adaptive noise filtering algorithm based on the mean value and variance of the＂current＂statistical model for maneuvering targets, and then the multiple model tracking algorithm of the multiple processing switch is used to improve the precision of tracking maneuvering targets.The modified algorithm is proved to be effective by simulation.展开更多
A new dynamical evolutionary algorithm (DEA) based on the theory of statistical mechanics is presented. This algorithm is very different from the traditional evolutionary algorithm and the two novel features are the u...A new dynamical evolutionary algorithm (DEA) based on the theory of statistical mechanics is presented. This algorithm is very different from the traditional evolutionary algorithm and the two novel features are the unique of selecting strategy and the determination of individuals that are selected to crossover and mutate. We use DEA to solve a lot of global optimization problems that are nonlinear, multimodal and multidimensional and obtain satisfactory results.展开更多
Finding a suitable solution to an optimization problem designed in science is a major challenge.Therefore,these must be addressed utilizing proper approaches.Based on a random search space,optimization algorithms can ...Finding a suitable solution to an optimization problem designed in science is a major challenge.Therefore,these must be addressed utilizing proper approaches.Based on a random search space,optimization algorithms can find acceptable solutions to problems.Archery Algorithm(AA)is a new stochastic approach for addressing optimization problems that is discussed in this study.The fundamental idea of developing the suggested AA is to imitate the archer’s shooting behavior toward the target panel.The proposed algorithm updates the location of each member of the population in each dimension of the search space by a member randomly marked by the archer.The AA is mathematically described,and its capacity to solve optimization problems is evaluated on twenty-three distinct types of objective functions.Furthermore,the proposed algorithm’s performance is compared vs.eight approaches,including teaching-learning based optimization,marine predators algorithm,genetic algorithm,grey wolf optimization,particle swarm optimization,whale optimization algorithm,gravitational search algorithm,and tunicate swarm algorithm.According to the simulation findings,the AA has a good capacity to tackle optimization issues in both unimodal and multimodal scenarios,and it can give adequate quasi-optimal solutions to these problems.The analysis and comparison of competing algorithms’performance with the proposed algorithm demonstrates the superiority and competitiveness of the AA.展开更多
Wind turbine blades are generally manufactured using fiber type material because of their cost effectiveness and light weight property however,blade get damaged due to wind gusts,bad weather conditions,unpredictable a...Wind turbine blades are generally manufactured using fiber type material because of their cost effectiveness and light weight property however,blade get damaged due to wind gusts,bad weather conditions,unpredictable aerodynamic forces,lightning strikes and gravitational loads which causes crack on the surface of wind turbine blade.It is very much essential to identify the damage on blade before it crashes catastrophically which might possibly destroy the complete wind turbine.In this paper,a fifteen tree classification based machine learning algorithms were modelled for identifying and detecting the crack on wind turbine blades.The models are built based on computing the vibration response of the blade when it is excited using piezoelectric accelerometer.The statistical,histogram and ARMA methods for each algorithm were compared essentially to suggest a better model for the identification and localization of crack on wind turbine blade.展开更多
Polynomial-time randomized algorithms were constructed to approximately solve optimal robust performance controller design problems in probabilistic sense and the rigorous mathematical justification of the approach wa...Polynomial-time randomized algorithms were constructed to approximately solve optimal robust performance controller design problems in probabilistic sense and the rigorous mathematical justification of the approach was given. The randomized algorithms here were based on a property from statistical learning theory known as (uniform) convergence of empirical means (UCEM). It is argued that in order to assess the performance of a controller as the plant varies over a pre-specified family, it is better to use the average performance of the controller as the objective function to be optimized, rather than its worst-case performance. The approach is illustrated to be efficient through an example.展开更多
Distributed Denial-of-Service (DDoS) attacks against public web servers are increasingly common. Countering DDoS attacks are becoming ever more challenging with the vast resources and techniques increasingly available...Distributed Denial-of-Service (DDoS) attacks against public web servers are increasingly common. Countering DDoS attacks are becoming ever more challenging with the vast resources and techniques increasingly available to attackers. It is impossible for the victim servers to work on the individual level of on-going traffic flows. In this paper, we establish IP Flow which is used to select proper features for DDoS detection. The IP flow statistics is used to allocate the weights for traffic routing by routers. Our system protects servers from DDoS attacks without strong client authentication or allowing an attacker with partial connectivity information to repeatedly disrupt communications. The new algorithm is thus proposed to get efficiently maximum throughput by the traffic filtering, and its feasibility and validity have been verified in a real network circumstance. The experiment shows that it is with high average detection and with low false alarm and miss alarm. Moreover, it can optimize the network traffic simultaneously with defending against DDoS attacks, thus eliminating efficiently the global burst of traffic arising from normal traffic.展开更多
Due to the advances of intelligent transportation system(ITSs),traffic forecasting has gained significant interest as robust traffic prediction acts as an important part in different ITSs namely traffic signal control...Due to the advances of intelligent transportation system(ITSs),traffic forecasting has gained significant interest as robust traffic prediction acts as an important part in different ITSs namely traffic signal control,navigation,route mapping,etc.The traffic prediction model aims to predict the traffic conditions based on the past traffic data.For more accurate traffic prediction,this study proposes an optimal deep learning-enabled statistical analysis model.This study offers the design of optimal convolutional neural network with attention long short term memory(OCNN-ALSTM)model for traffic prediction.The proposed OCNN-ALSTM technique primarily preprocesses the traffic data by the use of min-max normalization technique.Besides,OCNN-ALSTM technique was executed for classifying and predicting the traffic data in real time cases.For enhancing the predictive outcomes of the OCNN-ALSTM technique,the bird swarm algorithm(BSA)is employed to it and thereby overall efficacy of the network gets improved.The design of BSA for optimal hyperparameter tuning of the CNN-ALSTM model shows the novelty of the work.The experimental validation of the OCNNALSTM technique is performed using benchmark datasets and the results are examined under several aspects.The simulation results reported the enhanced outcomes of the OCNN-ALSTM model over the recent methods under several dimensions.展开更多
Based on the genetic algorithm(GA),a new genetic probability decoding(GPD) scheme for forward error correction(FEC) codes in optical transmission systems is proposed.The GPD scheme can further offset the quantificatio...Based on the genetic algorithm(GA),a new genetic probability decoding(GPD) scheme for forward error correction(FEC) codes in optical transmission systems is proposed.The GPD scheme can further offset the quantification error of the hard decision by making use of the channel interference probability and statistics information to restore the maximal likelihood transmission code word.The theoretical performance analysis and the simulation result show that the proposed GPD scheme has the advantages of lower decoding complexity,faster decoding speed and better decoding correction-error performance.Therefore,the proposed GPD algorithm is a better practical decoding algorithm.展开更多
基金The work was supported by the Subsystem of Calibration and ValidationHY-I Ground Application System+1 种基金National Satellite Ocean Application Service(NSOAS)China High-Tech“863"Project under contract Nos 2001AA636010 and 2001AA637010/7030.
文摘A group of statistical algorithms are proposed for the inversion of the three major components of CaseII waters inthe coastal area of the Huanghai Sea and the East China Sea. The algorithms are based on the in situ data collected inthe spring of 2003 with strict quality assurance according to NASA ocean bio-optic protocols. These algorithms arethe first ones with quantitative confidence that can be applied for the area. The average relative error of the inversedand in situ measured components' concentrations are: Chl-a about 37%, total suspended matter (TSM) about 25%,respectively. This preliminary result is quite satisfactory for CaseII waters, although some aspects in the modelneed further study. The sensitivity of the input error of 5% to remote sensing reflectance (Rrs) is also analyzed andit shows the algorithms are quite stable. The algorithms show a large difference with Tassans local SeaWiFSalgorithms for different waters, except for the Chl-a algorithm.
基金Supported by the Subsystem of Calibration and Validation, HY-1 Ground Application System, National Satellite Ocean Application Ser-vice (NSOAS). China High-Tech "863" Project (Nos. 2001AA636010, 2002AA639160 and 2002AA639200). The Ocean Science Fund Sponsor Project for the Youth, State Oceanic Administration (No. 2005415). The Director’s Science and Technology Fund Sponsor Project for the Youth, NSOAS.
文摘This paper suggests a group of statistical algorithms for calculating the total absorption coefficients based on in situ data of apparent optical property and inherent optical property collected with strict quality assurance according to NASA ocean bio-optic protocols in the Yellow Sea and the East China Sea in spring 2003. The band-ratios ofRrs412/Rrs555, Rrs49o/Rrs555 are used in the algorithms to derive the total absorption coefficients （at） at 412, 440, 488, 510, 532 and 555nm bands, respectively. The average relative errors between inversed and measured values are less than 25.8%, with the correlative coefficients （R2） being 0.75-0.85. Error sensitivity analysis shows that the maximum retrieval error is less than 24.0% at ＋5% error in Rrs＇s. So the statistical algorithms of this paper are practicable. In this paper, the relations between the total absorption coefficients at 412, 488, 510, 532, 555 nm and that of 440nm are also studied. The results show that the relations between the total absorption coefficients of 400-600 nm and that of 440 nm are correlated well and all of their correlative coefficients R2 are greater than 0.99. Furthermore, a regression analysis is also done for the slope of the linear relations and wavelengths, and the R2 is also 0.99. Thus it is possible to retrieve other bands＇ total absorption coefficients with only one band absorption value, which significantly reduce the number of unknown parameters in studying other ocean color related problems.
文摘Integrated use of statistical process control (SPC) and engineering process control (EPC) has better performance than that by solely using SPC or EPC. But integrated scheme has resulted in the problem of “Window of Opportunity” and autocorrelation. In this paper, advanced T2 statistics model and neural networks scheme are combined to solve the above problems: use T2 statistics technique to solve the problem of autocorrelation;adopt neural networks technique to solve the problem of “Window of Opportunity” and identification of disturbance causes. At the same time, regarding the shortcoming of neural network technique that its algorithm has a low speed of convergence and it is usually plunged into local optimum easily. Genetic algorithm was proposed to train samples in this paper. Results of the simulation ex-periments show that this method can detect the process disturbance quickly and accurately as well as identify the dis-turbance type.
文摘Objective To evaluate the feasibility of using a low concentration of contrast medium （Visipaque 270 mgl/mL）, low tube voltage, and an advanced image reconstruction algorithm in head and neck computed tomography angiography （CTA）. Methods Forty patients （22 men and 18 women; average age 48.7 ± 14.25 years; average body mass index 23.9 ± 3.7 kg/m^2） undergoing CTA for suspected vascular diseases were randomly assigned into two groups. Group A （n = 20） was administered 370 mgl/mL contrast medium, and group B （n = 20） was administered 270 mgl/mL contrast medium. Both groups were administered at a rate of 4.8 mL/s and an injection volume of 0.8 mL/kg. Images of group A were obtained with 120 kVp and filtered back projection （FBP） reconstruction, whereas images of group B were obtained with 80 kVp and 80% adaptive iterative statistical reconstruction algorithm （ASiR）. The CT values and standard deviations of intracranial arteries and image noise on the corona radiata were measured to calculate the contrast-to-noise ratio （CNR） and signal-to-noise ratio （SNR）. The beam-hardening artifacts （BHAs） around the skull base were calculated. Two readers evaluated the image quality with volume rendered images using scores from 1 to 5. The values between the two groups were statistically compared. Results The mean CT value of the intracranial arteries in group B was significantly higher than that in group A （P 〈 0.001）. The CNR and SNR values in group B were also statistically higher than those in group A （P 〈 0.001）. Image noise and BHAs were not significantly different between the two groups. The image quality score of VR images of in group B was significantly higher than that in group A （P = 0.001）. However, the quality scores of axial enhancement images in group B became significantly smaller than those in group A （P〈 0.001）. The CT dose index volume and dose-length product were decreased by 63.8% and 64%, respectively, in group B （P 〈 0.001 for both）. Conclusion Visipaque combined with 80 kVp and 80% ASiR provided similar image quality in intracranial CTA with 64% radiation dose reduction compared with the use of lopamidol, 120 kVp, and FBP reconstruc-tion.
文摘To improve the location accuracy, a hybrid location algorithm based on cuckoo and statistical manifold method is proposed. It combines the cuckoo algorithm's strong global optimization ability and the statistical manifold<span>’</span><span>s accurate positioning ability fully. The simulation results show that the hybrid location algorithm has higher accuracy and reduces the influence of initial value selection on location accuracy.</span>
文摘The fundamental problem of similarity studies, in the frame of data-mining, is to examine and detect similar items in articles, papers, and books with huge sizes. In this paper, we are interested in the probabilistic, and the statistical and the algorithmic aspects in studies of texts. We will be using the approach of k-shinglings, a k-shingling being defined as a sequence of k consecutive characters that are extracted from a text (k ≥ 1). The main stake in this field is to find accurate and quick algorithms to compute the similarity in short times. This will be achieved in using approximation methods. The first approximation method is statistical and, is based on the theorem of Glivenko-Cantelli. The second is the banding technique. And the third concerns a modification of the algorithm proposed by Rajaraman et al. ([1]), denoted here as (RUM). The Jaccard index is the one being used in this paper. We finally illustrate these results of the paper on the four Gospels. The results are very conclusive.
文摘Identification of modal parameters of a linear structure with output-only measurements has received much attention over the past decades. In the paper, the Natural Excitation Technique (NExT) is used for acquisition of the impulse signals from the structural responses. Then Eigensystem Realization Algorithm (ERA) is utilized for modal identification. For disregarding the fictitious ‘computational modes', a procedure, Statistically Averaging Modal Frequency Method (SAMFM), is developed to distinguish the true modes from noise modes, and to improve the precision of the identified modal frequencies of the structure. An offshore platform is modeled with the finite element method. The theoretical modal parameters are obtained for a comparison with the identified values. The dynamic responses of the platform under random wave loading are computed for providing the output signals used for identification with ERA. Results of simulation demonstrate that the proposed method can determine the system modal frequency with high precision.
基金supported in part by the National Natural Science Foundation of China under Grant U1805262,62071247,61801244,61771264in part by the Natural Science Foundation of Jiangsu Province under Grant BK20180754+1 种基金in part by the Guangdong Provincial Special Fund For Modern Agriculture Industry Technology Innovation Teams under Grant 2020KJ122in part by the Initial Scientic Research Foundation of NJUPT under Grant NY218103.
文摘In this paper,a reconfigurable intelligent surface(RIS)-assisted MIMO wireless secure communication system is considered,in which a base station(BS)equipped with multiple antennas exploits statistical channel state information to communicate with a legitimate multi-antenna user,in the presence of an eavesdropper,also equipped with multiple antennas.We firstly obtain an analytical expression of the ergodic secrecy rate based on the results of largedimensional random matrix theory.Then,a jointly alternating optimization algorithm with the method of Taylor series expansion and the projected gradient ascent method is proposed to design the transmit covariance matrix at the BS,as well as the diagonal phaseshifting matrix to maximize the ergodic secrecy rate.Simulations are conducted to demonstrate the accuracy of the derived analytical expressions,as well as the superior performance of our proposed algorithm.
基金supported by National Natural Science Foundation of China(611750 68,61472168,61163004)Natural Science Foundation of Yunnan Province(2013FA130)Talent Promotion Project of Ministry of Science and Technology(2014HE001)
基金Supported by the program for the Fundamental Research Funds for the Central Universities(2014RC042,2015JBM109)
文摘In this article, we consider a lifetime distribution, the Weibull-Logarithmic distri- bution introduced by [6]. We investigate some new statistical characterizations and properties. We develop the maximum likelihood inference using EM algorithm. Asymptotic properties of the MLEs are obtained and extensive simulations are conducted to assess the performance of parameter estimation. A numerical example is used to illustrate the application.
文摘A multiple model tracking algorithm based on neural network and multiple-process noise soft-switching for maneuvering targets is presented.In this algorithm, the＂current＂statistical model and neural network are running in parallel.The neural network algorithm is used to modify the adaptive noise filtering algorithm based on the mean value and variance of the＂current＂statistical model for maneuvering targets, and then the multiple model tracking algorithm of the multiple processing switch is used to improve the precision of tracking maneuvering targets.The modified algorithm is proved to be effective by simulation.
文摘A new dynamical evolutionary algorithm (DEA) based on the theory of statistical mechanics is presented. This algorithm is very different from the traditional evolutionary algorithm and the two novel features are the unique of selecting strategy and the determination of individuals that are selected to crossover and mutate. We use DEA to solve a lot of global optimization problems that are nonlinear, multimodal and multidimensional and obtain satisfactory results.
基金The research was supported by the Excellence Project PrF UHK No.2208/2021-2022,University of Hradec Kralove,Czech Republic.
文摘Finding a suitable solution to an optimization problem designed in science is a major challenge.Therefore,these must be addressed utilizing proper approaches.Based on a random search space,optimization algorithms can find acceptable solutions to problems.Archery Algorithm(AA)is a new stochastic approach for addressing optimization problems that is discussed in this study.The fundamental idea of developing the suggested AA is to imitate the archer’s shooting behavior toward the target panel.The proposed algorithm updates the location of each member of the population in each dimension of the search space by a member randomly marked by the archer.The AA is mathematically described,and its capacity to solve optimization problems is evaluated on twenty-three distinct types of objective functions.Furthermore,the proposed algorithm’s performance is compared vs.eight approaches,including teaching-learning based optimization,marine predators algorithm,genetic algorithm,grey wolf optimization,particle swarm optimization,whale optimization algorithm,gravitational search algorithm,and tunicate swarm algorithm.According to the simulation findings,the AA has a good capacity to tackle optimization issues in both unimodal and multimodal scenarios,and it can give adequate quasi-optimal solutions to these problems.The analysis and comparison of competing algorithms’performance with the proposed algorithm demonstrates the superiority and competitiveness of the AA.
文摘Wind turbine blades are generally manufactured using fiber type material because of their cost effectiveness and light weight property however,blade get damaged due to wind gusts,bad weather conditions,unpredictable aerodynamic forces,lightning strikes and gravitational loads which causes crack on the surface of wind turbine blade.It is very much essential to identify the damage on blade before it crashes catastrophically which might possibly destroy the complete wind turbine.In this paper,a fifteen tree classification based machine learning algorithms were modelled for identifying and detecting the crack on wind turbine blades.The models are built based on computing the vibration response of the blade when it is excited using piezoelectric accelerometer.The statistical,histogram and ARMA methods for each algorithm were compared essentially to suggest a better model for the identification and localization of crack on wind turbine blade.
文摘Polynomial-time randomized algorithms were constructed to approximately solve optimal robust performance controller design problems in probabilistic sense and the rigorous mathematical justification of the approach was given. The randomized algorithms here were based on a property from statistical learning theory known as (uniform) convergence of empirical means (UCEM). It is argued that in order to assess the performance of a controller as the plant varies over a pre-specified family, it is better to use the average performance of the controller as the objective function to be optimized, rather than its worst-case performance. The approach is illustrated to be efficient through an example.
文摘Distributed Denial-of-Service (DDoS) attacks against public web servers are increasingly common. Countering DDoS attacks are becoming ever more challenging with the vast resources and techniques increasingly available to attackers. It is impossible for the victim servers to work on the individual level of on-going traffic flows. In this paper, we establish IP Flow which is used to select proper features for DDoS detection. The IP flow statistics is used to allocate the weights for traffic routing by routers. Our system protects servers from DDoS attacks without strong client authentication or allowing an attacker with partial connectivity information to repeatedly disrupt communications. The new algorithm is thus proposed to get efficiently maximum throughput by the traffic filtering, and its feasibility and validity have been verified in a real network circumstance. The experiment shows that it is with high average detection and with low false alarm and miss alarm. Moreover, it can optimize the network traffic simultaneously with defending against DDoS attacks, thus eliminating efficiently the global burst of traffic arising from normal traffic.
基金This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF-2021R1A6A1A03039493).
文摘Due to the advances of intelligent transportation system(ITSs),traffic forecasting has gained significant interest as robust traffic prediction acts as an important part in different ITSs namely traffic signal control,navigation,route mapping,etc.The traffic prediction model aims to predict the traffic conditions based on the past traffic data.For more accurate traffic prediction,this study proposes an optimal deep learning-enabled statistical analysis model.This study offers the design of optimal convolutional neural network with attention long short term memory(OCNN-ALSTM)model for traffic prediction.The proposed OCNN-ALSTM technique primarily preprocesses the traffic data by the use of min-max normalization technique.Besides,OCNN-ALSTM technique was executed for classifying and predicting the traffic data in real time cases.For enhancing the predictive outcomes of the OCNN-ALSTM technique,the bird swarm algorithm(BSA)is employed to it and thereby overall efficacy of the network gets improved.The design of BSA for optimal hyperparameter tuning of the CNN-ALSTM model shows the novelty of the work.The experimental validation of the OCNNALSTM technique is performed using benchmark datasets and the results are examined under several aspects.The simulation results reported the enhanced outcomes of the OCNN-ALSTM model over the recent methods under several dimensions.
基金supported by the National Natural Science Foundation of China (Nos.61071117 and 61003256)the Natural Science Foundation of Chongqing CSTC (No.2010BB2409)the Science and Technology Foundation of Chongqing Municipal Education Commission (No.KJ110519)
文摘Based on the genetic algorithm(GA),a new genetic probability decoding(GPD) scheme for forward error correction(FEC) codes in optical transmission systems is proposed.The GPD scheme can further offset the quantification error of the hard decision by making use of the channel interference probability and statistics information to restore the maximal likelihood transmission code word.The theoretical performance analysis and the simulation result show that the proposed GPD scheme has the advantages of lower decoding complexity,faster decoding speed and better decoding correction-error performance.Therefore,the proposed GPD algorithm is a better practical decoding algorithm.
