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Expressway traffic flow prediction using chaos cloud particle swarm algorithm and PPPR model 被引量:2
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作者 赵泽辉 康海贵 李明伟 《Journal of Southeast University(English Edition)》 EI CAS 2013年第3期328-335,共8页
Aiming at the real-time fluctuation and nonlinear characteristics of the expressway short-term traffic flow forecasting the parameter projection pursuit regression PPPR model is applied to forecast the expressway traf... Aiming at the real-time fluctuation and nonlinear characteristics of the expressway short-term traffic flow forecasting the parameter projection pursuit regression PPPR model is applied to forecast the expressway traffic flow where the orthogonal Hermite polynomial is used to fit the ridge functions and the least square method is employed to determine the polynomial weight coefficient c.In order to efficiently optimize the projection direction a and the number M of ridge functions of the PPPR model the chaos cloud particle swarm optimization CCPSO algorithm is applied to optimize the parameters. The CCPSO-PPPR hybrid optimization model for expressway short-term traffic flow forecasting is established in which the CCPSO algorithm is used to optimize the optimal projection direction a in the inner layer while the number M of ridge functions is optimized in the outer layer.Traffic volume weather factors and travel date of the previous several time intervals of the road section are taken as the input influencing factors. Example forecasting and model comparison results indicate that the proposed model can obtain a better forecasting effect and its absolute error is controlled within [-6,6] which can meet the application requirements of expressway traffic flow forecasting. 展开更多
关键词 expressway traffic flow forecasting projectionpursuit regression particle swarm algorithm chaoticmapping cloud model
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Encryption Algorithm for Securing Non-Disclosure Agreements in Outsourcing Offshore Software Maintenance
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作者 Atif Ikram Masita Abdul Jalil +6 位作者 Amir Bin Ngah Nadeem Iqbal Nazri Kama Azri Azmi Ahmad Salman Khan Yasir Mahmood Assad Alzayed 《Computers, Materials & Continua》 SCIE EI 2022年第11期3827-3845,共19页
Properly created and securely communicated,non-disclosure agreement(NDA)can resolve most of the common disputes related to outsourcing of offshore software maintenance(OSMO).Occasionally,these NDAs are in the form of ... Properly created and securely communicated,non-disclosure agreement(NDA)can resolve most of the common disputes related to outsourcing of offshore software maintenance(OSMO).Occasionally,these NDAs are in the form of images.Since the work is done offshore,these agreements or images must be shared through the Internet or stored over the cloud.The breach of privacy,on the other hand,is a potential threat for the image owners as both the Internet and cloud servers are not void of danger.This article proposes a novel algorithm for securing the NDAs in the form of images.As an agreement is signed between the two parties,it will be encrypted before sending to the cloud server or travelling through the public network,the Internet.As the image is input to the algorithm,its pixels would be scrambled through the set of randomly generated rectangles for an arbitrary amount of time.The confusion effects have been realized through an XOR operation between the confused image,and chaotic data.Besides,5D multi-wing hyperchaotic system has been employed to spawn the chaotic vectors due to good properties of chaoticity it has.The machine experimentation and the security analysis through a comprehensive set of validation metric vividly demonstrate the robustness,defiance to the multifarious threats and the prospects for some real-world application of the proposed encryption algorithm for the NDA images. 展开更多
关键词 Non-disclosure agreement encryption DECRYPTION secret key chaoticmap CONFUSION diffusion
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Hybrid Particle Swarm Optimization with Differential Evolution for Numerical and Engineering Optimization 被引量:3
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作者 Guo-Han Lin Jing Zhang Zhao-Hua Liu 《International Journal of Automation and computing》 EI CSCD 2018年第1期103-114,共12页
In this paper, a hybrid particle swarm optimization (PSO) algorithm with differential evolution (DE) is proposed for numerical benchmark problems and optimization of active disturbance rejection controller (ADRC... In this paper, a hybrid particle swarm optimization (PSO) algorithm with differential evolution (DE) is proposed for numerical benchmark problems and optimization of active disturbance rejection controller (ADRC) parameters. A chaotic map with greater Lyapunov exponent is introduced into PSO for balancing the exploration and exploitation abilities of the proposed algorithm. A DE operator is used to help PSO jump out of stagnation. Twelve benchmark function tests from CEC2005 and eight real world opti- mization problems from CEC2011 are used to evaluate the performance of the proposed algorithm. The results show that statistically, the proposed hybrid algorithm has performed consistently well compared to other hybrid variants. Moreover, the simulation results on ADRC parameter optimization show that the optimized ADRC has better robustness and adaptability for nonlinear discrete-time systems with time delays. 展开更多
关键词 Particle swarm optimization (PSO) active disturbance rejection control (ADRC) differential evolution algorithm chaoticmap parameter tuning.
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