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An edge-based model for non-Markovian sexually transmitted infections in coupled network

International Journal of Biomathematics 2020年第2期13卷 119-153页

作者： Xiaofeng Luo Junyuan Yang Zhen Jin School of Computer and Information Technology Shanxi University Taiyuan 030006P.R.China Complex System Research Center Shanxi University Taiyuan 030006ShanxiP.R.China Shanxi Key Laboratory of Mathematical Techniques and Big DataAnalysis on Disease Control and Prevention Shanxi University Taiyuan 030006ShanxiP.R.China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Taiyuan 030006 P.R.China

In this paper,allowing for general transmission and recovery times distributions,we proposed an edge-based age-structured-like compartmental model for STIs(EBACMS)in a coupled *** considered sexual transmissions between men with also heterosexual ***,we gave the general approach of proving the nonnegativity of solutions for the system coupling ordinary and partial differen-tial equations,which can be applied to all edge-based compartment *** then analyzed the epidemic threshold Ro with different distributions which couples the thresholds of the single-layer and bipartite networks in the percolation *** also studied the global stability of disease-free equilibrium with R0<1 and the final epidemic size F(the proportion of the population experiencing infection during the epidemic)with R0>*** addition,numerical simulations indicated that given a fixed exponential transmission distribution,a higher variance(with same mean)in general recovery distribution gives smaller R0 and *** analysis on Ro and F in terms of the parameters illustrated that male-to-male transmission routes have a greater impact on Rg and F than the heterosexual transmission routes for the Markovian transmission process and arbitrary recovery *** results provide a good theoretical guideline to consider the distributions of real-world STIs.

关键词： Coupled network EBCM non-Markovian process sexually transmitted disease epidemic age-structured

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Grey Wolf Optimizer with Ranking-Based Mutation Operator for IIR Model Identification

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Chinese Journal of Electronics 2018年第5期27卷 1071-1079页

作者： ZHANG Sen ZHOU Yongquan College of Information Science and Engineering Guangxi University for Nationalities School Key Laboratory of Guangxi High Schools Complex System and Computational Intelligence

A variant of Grey wolf optimizer(GWO),called grey wolf optimizer with Ranking-based mutation operator(RGWO) is applied to the Infinite impulse response(IIR) system identification problem. RGWO makes GWO faster and more robust. In RGWO, the rankingbased mutation operator is integrated into the GWO to accelerate the convergence speed, and thus enhance the performance. The simulation results over several models are presented and statistically validated. Compared to other robust evolutionary algorithms, RGWO performs significantly better in terms of the quality, speed, and the stability of the final solutions.

关键词： system identification IIR system Grey wolf optimizer Ranking-based mutation operator

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BFPA: Butterfly Strategy Flower Pollination Algorithm 15th

BFPA: Butterfly Strategy Flower Pollination Algorithm

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15th International Conference on Intelligent Computing, ICIC 2019

作者： Lei, Mengyi Luo, Qifang Zhou, Yongquan Tang, Chengmei Gao, Yuanyuan College of Information Science and Engineering Guangxi University for Nationalities Nanning530006 China Key Laboratory of Guangxi High Schools Complex System and Computational Intelligence Nanning530006 China

ISBN: (纸本)9783030267629

Aiming at the shortcomings of slow convergence and low precision of flower pollination algorithm, a flower pollination algorithm based on butterfly pollination strategy (BFPA) was proposed. The algorithm first uses the butterfly pollination strategy to accelerate the convergence speed of the global search phase. Second, in the local search phase, the beetle antenna search help algorithm is used to jump out of the local optimum. The experiment uses five Benchmark test functions to test, and the results show that the BFPA algorithm has better performance than other versions of the pollination algorithm. © 2019, Springer Nature Switzerland AG.

关键词： Global optimization

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A complex-Valued Encoding Moth-Flame Optimization Algorithm for Global Optimization 15th

A Complex-Valued Encoding Moth-Flame Optimization Algorithm ...

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15th International Conference on Intelligent Computing, ICIC 2019

作者： Wang, Pengchuan Zhou, Yongquan Luo, Qifang Fan, Chencheng Xiang, Zhehong College of Information Science and Engineering Guangxi University for Nationalities Nanning530006 China Guangxi High School Key Laboratory of Complex System and Computational Intelligence Nanning530006 China

ISBN: (纸本)9783030267629

The real-valued moth-flame optimization algorithm (MFO) is a new bio-inspired algorithm. It simulates the navigation mechanism of moth lateral positioning under moonlight. MFO has excellent performance in solving optimization problems and has strong ability in solving power optimization combination. In order to improve the global search ability of the algorithm, a complex-valued encoding moth-flame optimization algorithm (CMFO) is proposed. The real and imaginary parts of the population are updated by using the diploid structure of complex-valued encoding. The diversity of the population was increased. The effectiveness of CMFO algorithm has been verified by 4 benchmark problems. Statistically significant results and analysis show that the proposed complex-valued encoding moth-flame optimization algorithm is very promising and occasionally competitive compared with other well-established meta-heuristic techniques. © 2019, Springer Nature Switzerland AG.

关键词： Global optimization

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An Enhanced Whale Optimization Algorithm with Simplex Method 15th

An Enhanced Whale Optimization Algorithm with Simplex Method

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15th International Conference on Intelligent Computing, ICIC 2019

作者： Niu, Yanbiao Tang, Zhonghua Zhou, Yongquan Wang, Zhongmin College of Information Science and Engineering Guangxi University for Nationalities Nanning530006 China Guangxi High School Key Laboratory of Complex System and Computational Intelligence Nanning530006 China

ISBN: (纸本)9783030267629

This paper proposes an enhanced whale optimization algorithm with the simplex method named SMWOA algorithm. SMWOA make WOA faster, more robust, and avoid premature convergence. The simplex method (SM) iteratively optimizes the current worst step size, avoids the population search at the edge, and improves the convergence accuracy and speed of the algorithm. The SMWOA algorithm is compared with other well-known meta-heuristic algorithms on 5 benchmarks and 1 classical engineering design problem. The experimental results show that the SMWOA algorithm has better performance than other meta-heuristic optimization algorithms in low and high dimensions. © 2019, Springer Nature Switzerland AG.

关键词： Heuristic algorithms

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A novel DV-Hop method based on coupling algorithm used for Wireless Sensor Network localisation

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International Journal of Wireless and Mobile Computing 2019年第2期16卷 128-137页

作者： Wang, Yechuang Wang, Penghong Zhang, Jiangjiang Cai, Xingjuan Li, Wuchao Ma, Yanyan Complex System and Computational Intelligence Laboratory TaiYuan University of Science and Technology Taiyuan003024 China Jiaxing Vocational Technical College Zhejiang Sheng314001 China Shanxi Cloud Era TISCO Information Automation Technology Co. Ltd. Taiyuan030003 China

Wireless Sensor Network (WSN) localisation is an essential requirement in the increasing prevalence of WSN applications. It is an important part of the Internet of Things (IOT) and has become a hot research area. Distance Vector-Hop algorithm (DV-Hop), a range-free algorithm, is widely deployed to solve the localisation problem in WSN. However, the results of the estimation precision are usually not satisfactory. In order to improve the WSN positioning accuracy, in this paper, we propose a new coupling algorithm based on Bacterial Foraging Algorithm (BFA) and Glow-worm Swarm Optimisation (GSO) (BFO-GSO). The algorithm has good convergence speed, local search ability of BFO and global convergence of GSO. The optimisation performance is verified by CEC2013 benchmarks in those designs against the original algorithm. Furthermore, Wilcoxon’s rank-sum nonparametric statistical test and Friedman test are carried out to judge whether the results of the proposed algorithm differ from those of the other algorithms in a statistically significant way. The numerical results prove that it is able to significantly outperform others on majority of the benchmark functions. Finally, the proposed algorithm is also combined into the DV-Hop algorithm to improve the WSN positioning accuracy. Experimental results show that our improved algorithm achieves better performance when compared with other DV-Hop algorithms. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Wireless sensor networks

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Demand estimation of water resources based on algorithm comparison

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International Journal of Wireless and Mobile Computing 2019年第2期16卷 110-116页

作者： Wang, Junyan Zhang, Jiangjiang Cai, Xingjuan Ma, Yanyan Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology Nanchang330099 China Complex System and Computational Intelligence Laboratory TaiYuan University of Science and Technology Taiyuan003024 China Shanxi Cloud Era TISCO Information Automation Technology Co. Ltd. Taiyuan030003 China

Water is the source of life and the correct assessment of water resources is an important prerequisite for the rational utilisation of water resources. In this paper, water resources are evaluated and predicted by three different algorithms, including Bat Algorithm (BA), Particle Swarm Optimisation (PSO) and Pigeon-Inspired Optimisation (PIO). Comparing the errors of water resources assessed for the three algorithms, we select an algorithm of the minimum error to predict the future water demand. In the experiments, firstly, the water data from 2003 to 2012 are used to find the optimal weights of the models. Then, the weight factor is combined with the given model to gain the error between predicted value and the remaining data (2013–2015). Finally, the simulation results show that PIO algorithm has a better performance compared with the BA and PSO algorithms. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Water resources

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IDP - OPTICS: Improvement of Differential Privacy Algorithm in Data Histogram Publishing Based on Density Clustering 15th

IDP - OPTICS: Improvement of Differential Privacy Algorithm ...

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15th International Conference on Intelligent Computing, ICIC 2019

作者： Ge, Lina Hu, Yugu Wang, Hong He, Zhonghua Meng, Huazhi Tang, Xiong Wu, Liyan College of Information Science and Engineering Guangxi University for Nationalities Nanning China Key Laboratory of Network Communication Engineering Guangxi University for Nationalities Nanning China Key Laboratory of Guangxi High Schools Complex System and Computational Intelligence Nanning China

ISBN: (纸本)9783030269685

In recent years, incidents of privacy leaks have frequently occurred. How to protect the group and personal privacy has become a focus issue in the field of information security. Differential privacy technology can protect the privacy of published data by adding noise. In this paper, we propose the IDP-OPTICS algorithm to solve the problem of excessive noise accumulation and low data availability in the histogram data release under the static data set. First, we preprocess the data with a density-based clustering algorithm. Then, we apply differential privacy to the data and finally add noise to the processed data by adding heteroscedasticity. The experimental data shows that IDP-OPTICS achieves a reduction in the problem of excessive noise accumulation and a balance of noise distribution as a whole. © 2019, Springer Nature Switzerland AG.

关键词： Laplace transforms

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Research on Full Homomorphic Encryption Algorithm for Integer in Cloud Environment 1

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15th International Conference on Intelligent Computing, ICIC 2019

作者： Wang, Lijuan Ge, Lina Hu, Yugu He, Zhonghua Zhao, Zerong Wei, Hangui College of Information Science and Engineering Guangxi University for Nationalities Nanning China Key Laboratory of Network Communication Engineering Guangxi University for Nationalities Nanning China Key Laboratory of Guangxi High Schools Complex System and Computational Intelligence Nanning China

ISBN: (数字)9783030267667

ISBN: (纸本)9783030267650

With the continuous development of computer networks, cloud storage is now the mainstream way for people to store information, but some important information leaks in the process of storage, and information security issues have become the most concerned issue at present. Homomorphic encryption not only has the property of data encryption of traditional encryption algorithm, but also has the result of ciphertext operation equivalent to the corresponding plaintext operation. This paper proposes an improved scheme based on DGHV, it (MDGHV) is mainly implemented from two points: changing the encryption formula c = pq + 2r + m to c = pqr + m, the domain of clear text m is expanded to a custom value, which can be used as a parameter;without acquiring sensitive information, data owners can directly calculate multiple ciphertexts and ensure high efficiency to meet the security requirements of cloud environment. An improved scheme based on DGHV, which expands the plaintext domain and enable search encryption operation to encrypt larger values, thus improving the efficiency. The security of this algorithm still depends on the similar GCD problem, which can solve some practical security problems in the cloud environment. © 2019, Springer Nature Switzerland AG.

关键词： Cloud storage

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A pigeon-inspired optimization algorithm for many-objective optimization problems

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Science China(Information Sciences) 2019年第7期62卷 131-138页

作者： Zhihua CUI Jiangjiang ZHANG Yechuang WANG Yang CAO Xingjuan CAI Wensheng ZHANG Jinjun CHEN Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Beijing Institute of Petrochemical Technology Faculty of Information Technology Beijing University of Technology State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences School of Software University of Technology Sydney

Dear editor,Swarm intelligence optimization algorithms are inspired by the behaviour of biological groups in nature. Such algorithms have the advantages of a clear structure, simple operation, comprehensible principles, strong parallelism, effective search abilities, and strong robustness. They can effectively solve difficult problems that traditional methods cannot. Pigeon-inspired optimization (PIO), a novel biomimetic swarm intelligence optimization algorithm, was proposed by Duan and Qiao in

关键词： A pigeon-inspired optimization algorithm for many-objective optimization problems Pareto

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