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  • Open Access

    ARTICLE

    An Optimization Scheme for Task Offloading and Resource Allocation in Vehicle Edge Networks

    Yuxin Xu1, Zilong Jin1,2,*, Xiaorui Zhang1, Lejun Zhang3

    Journal on Internet of Things, Vol.2, No.4, pp. 163-173, 2020, DOI:10.32604/jiot.2020.011792 - 22 September 2020

    Abstract The vehicle edge network (VEN) has become a new research hotspot in the Internet of Things (IOT). However, many new delays are generated during the vehicle offloading the task to the edge server, which will greatly reduce the quality of service (QOS) provided by the vehicle edge network. To solve this problem, this paper proposes an evolutionary algorithm-based (EA) task offloading and resource allocation scheme. First, the delay of offloading task to the edge server is generally defined, then the mathematical model of problem is given. Finally, the objective function is optimized by evolutionary algorithm, More >

  • Open Access

    ARTICLE

    Improved Teaching Learning Based Optimization and Its Application in Parameter Estimation of Solar Cell Models

    Qinqin Fan1,*, Yilian Zhang2, Zhihuan Wang1

    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 1-12, 2020, DOI:10.31209/2018.100000042

    Abstract Weak global exploration capability is one of the primary drawbacks in teaching learning based optimization (TLBO). To enhance the search capability of TLBO, an improved TLBO (ITLBO) is introduced in this study. In ITLBO, a uniform random number is replaced by a normal random number, and a weighted average position of the current population is chosen as the other teacher. The performance of ITLBO is compared with that of five meta-heuristic algorithms on a well-known test suite. Results demonstrate that the average performance of ITLBO is superior to that of the compared algorithms. Finally, ITLBO More >

  • Open Access

    ARTICLE

    Analysis of Twitter Data Using Evolutionary Clustering during the COVID-19 Pandemic

    Ibrahim Arpaci1, Shadi Alshehabi2, Mostafa Al-Emran3, *, Mahmoud Khasawneh4, Ibrahim Mahariq4, Thabet Abdeljawad5, 6, 7, Aboul Ella Hassanien8, 9

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 193-204, 2020, DOI:10.32604/cmc.2020.011489 - 23 July 2020

    Abstract People started posting textual tweets on Twitter as soon as the novel coronavirus (COVID-19) emerged. Analyzing these tweets can assist institutions in better decision-making and prioritizing their tasks. Therefore, this study aimed to analyze 43 million tweets collected between March 22 and March 30, 2020 and describe the trend of public attention given to the topics related to the COVID-19 epidemic using evolutionary clustering analysis. The results indicated that unigram terms were trended more frequently than bigram and trigram terms. A large number of tweets about the COVID-19 were disseminated and received widespread public attention… More >

  • Open Access

    ARTICLE

    Bilateral Collaborative Optimization for Cloud Manufacturing Service

    Bin Xu1, 2, Yong Tang1, Yi Zhu1, Wenqing Yan1, Cheng He3, Jin Qi1, *

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 2031-2042, 2020, DOI:10.32604/cmc.2020.011149 - 30 June 2020

    Abstract Manufacturing service composition of the supply side and scheduling of the demand side are two important components of Cloud Manufacturing, which directly affect the quality of Cloud Manufacturing services. However, the previous studies on the two components are carried out independently and thus ignoring the internal relations and mutual constraints. Considering the two components on both sides of the supply and the demand of Cloud Manufacturing services at the same time, a Bilateral Collaborative Optimization Model of Cloud Manufacturing (BCOM-CMfg) is constructed in this paper. In BCOM-CMfg, to solve the manufacturing service scheduling problem on… More >

  • Open Access

    ARTICLE

    Discrete Circular Distributions with Applications to Shared Orthologs of Paired Circular Genomes

    Tomoaki Imoto1, *, Grace S. Shieh2, *, Kunio Shimizu3

    CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.3, pp. 1131-1149, 2020, DOI:10.32604/cmes.2020.08466 - 28 May 2020

    Abstract For structural comparisons of paired prokaryotic genomes, an important topic in synthetic and evolutionary biology, the locations of shared orthologous genes (henceforth orthologs) are observed as binned data. This and other data, e.g., wind directions recorded at monitoring sites and intensive care unit arrival times on the 24-hour clock, are counted in binned circular arcs, thus modeling them by discrete circular distributions (DCDs) is required. We propose a novel method to construct a DCD from a base continuous circular distribution (CCD). The probability mass function is defined to take the normalized values of the probability… More >

  • Open Access

    ARTICLE

    Feature Selection and Representation of Evolutionary Algorithm on Keystroke Dynamics

    Purvashi Baynath, Sunjiv Soyjaudah, Maleika Heenaye-Mamode Khan

    Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 651-661, 2019, DOI:10.31209/2018.100000060

    Abstract The goal of this paper is (i) adopt fusion of features (ii) determine the best method of feature selection technique among ant Colony optimisation, artificial bee colony optimisation and genetic algorithm. The experimental results reported that ant colony Optimisation is a promising techniques as feature selection on Keystroke Dynamics as it outperforms in terms of recognition rate for our inbuilt database where the distance between the keys has been considered for the password derivation with recognition rate 97.85%. Finally the results have shown that a small improvement is obtained by fused features, which suggest that More >

  • Open Access

    ARTICLE

    A New Method Based on Evolutionary Algorithm for Symbolic Network Weak Unbalance

    Yirong Jiang1, Weijin Jiang2,3,4,*, Jiahui Chen2,*, Yang Wang2, Yuhui Xu2, Lina Tan2, Liang Guo5

    Journal on Internet of Things, Vol.1, No.2, pp. 41-53, 2019, DOI:10.32604/jiot.2019.07231

    Abstract The symbolic network adds the emotional information of the relationship, that is, the “+” and “-” information of the edge, which greatly enhances the modeling ability and has wide application in many fields. Weak unbalance is an important indicator to measure the network tension. This paper starts from the weak structural equilibrium theorem, and integrates the work of predecessors, and proposes the weak unbalanced algorithm EAWSB based on evolutionary algorithm. Experiments on the large symbolic networks Epinions, Slashdot and WikiElections show the effectiveness and efficiency of the proposed method. In EAWSB, this paper proposes a More >

  • Open Access

    ARTICLE

    Localization Based Evolutionary Routing (LOBER) for Efficient Aggregation in Wireless Multimedia Sensor Networks

    Ashwinth Janarthanan1,*, Dhananjay Kumar1

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 895-912, 2019, DOI:10.32604/cmc.2019.06805

    Abstract Efficient aggregation in wireless sensor nodes helps reduce network traffic and reduce energy consumption. The objective of this work Localization Based Evolutionary Routing (LOBER) is to achieve global optimization for aggregation and WMSN lifetime. Improved localization is achieved by a novel Centroid Based Octant Localization (CBOL) technique considering an arbitrary hexagonal region. Geometric principles of hexagon are used to locate the unknown nodes in the centroid positions of partitioned regions. Flower pollination algorithm, a meta heuristic evolutionary algorithm that is extensively applied in solving real life, complex and nonlinear optimization problems in engineering and industry More >

  • Open Access

    ARTICLE

    On an Optimization Method Based on Z-Numbers and the Multi-Objective Evolutionary Algorithm

    Dong Qiu, Rongwen Dong, Shuqiao Chen, Andi Li

    Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 147-150, 2018, DOI:10.1080/10798587.2017.1327153

    Abstract In this paper, we research the optimization problems with multiple Z-number valued objectives. First, we convert Z-numbers to classical fuzzy numbers to simplify the calculation. A new dominance relationship of two fuzzy numbers based on the lower limit of the possibility degree is proposed. Then according to this dominance relationship, we present a multi-objective evolutionary algorithm to solve the optimization problems. Finally, a simple example is used to demonstrate the validity of the suggested algorithm. More >

  • Open Access

    ARTICLE

    Grey Wolf Optimizer to Real Power Dispatch with Non-Linear Constraints

    G. R. Venkatakrishnan1,*, R. Rengaraj2, S. Salivahanan3

    CMES-Computer Modeling in Engineering & Sciences, Vol.115, No.1, pp. 25-45, 2018, DOI:10.3970/cmes.2018.115.025

    Abstract A new and efficient Grey Wolf Optimization (GWO) algorithm is implemented to solve real power economic dispatch (RPED) problems in this paper. The nonlinear RPED problem is one the most important and fundamental optimization problem which reduces the total cost in generating real power without violating the constraints. Conventional methods can solve the ELD problem with good solution quality with assumptions assigned to fuel cost curves without which these methods lead to suboptimal or infeasible solutions. The behavior of grey wolves which is mimicked in the GWO algorithm are leadership hierarchy and hunting mechanism. The More >

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