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Search Results (231)
  • Open Access

    ARTICLE

    A Hybrid GABC-GA Algorithm for Mechanical Design Optimization Problems

    Hui Zhi1,2, Sanyang Liu1

    Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 815-825, 2019, DOI:10.31209/2019.100000085

    Abstract In this paper, we proposed a hybrid algorithm, which is embedding the genetic operators in the global-best-guided artificial bee colony algorithms called GABCGA to solve the nonlinear design optimization problems. The genetic algorithm has no memory function and good at find global optimization with large probability, but the artificial bee colony algorithm not have selection, crossover and mutation operator and most significant at local search. The hybrid algorithm balances the exploration and exploitation ability further by combining the advantages of both. The experimental results of five engineering optimization and comparisons with existing approaches show that the proposed approach is outperforms… 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 an effective fusion is necessary. More >

  • Open Access

    ARTICLE

    Virtual Machine Based on Genetic Algorithm Used in Time and Power Oriented Cloud Computing Task Scheduling

    Tongmao Ma1,2, Shanchen Pang1, Weiguang Zhang1, Shaohua Hao1

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 605-613, 2019, DOI:10.31209/2019.100000115

    Abstract In cloud computing, task scheduling is a challenging problem in cloud data center, and there are many different kinds of task scheduling strategies. A good scheduling strategy can bring good effectiveness, where plenty of parameters should be regulated to achieve acceptable performance of cloud computing platform. In this work, combined elitist strategy, three parameters values oriented genetic algorithms are proposed. Specifically, a model built by Generalized Stochastic Petri Nets (GSPN) is introduced to describe the process of scheduling in cloud datacenter, and then the workflow of the algorithms is showed. After that, the effectiveness of the algorithms is found to… More >

  • Open Access

    ARTICLE

    Development of Available Transfer Capability Enhancement Using Intelligent Genetic Algorithm for IEEE Bus System

    R. Rohini1, Dasari Narasimha Rao2, S. Ravi3, V. Sampath Kumar4

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 433-440, 2019, DOI:10.31209/2018.100000015

    Abstract Improving Available Transfer Capability is an important issue in the deregulated power systems. The Available Transfer Capability of a transmission network is the transfer capabilities of a transmission network for the transfer of power for further commercial activity, over and above already committed usage. It is a proven fact that Flexible Alternating Current Transmission System technology can control voltage magnitude, phase angle, and circuit reactance. Therefore, it is important to investigate the impact of Flexible Alternating Current Transmission System controllers on the available transfer capability. This paper is focuses on the evaluation impact of Thyristor controlled switched capacitors and static… More >

  • Open Access

    ARTICLE

    PID Tuning Method Using Single-Valued Neutrosophic Cosine Measure and Genetic Algorithm

    Jun Ye

    Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 15-23, 2019, DOI:10.31209/2018.100000067

    Abstract Because existing proportional-integral-derivative (PID) tuning method using similarity measures of single-valued neutrosophic sets (SVNSs) and an increasing step algorithm shows its complexity and inconvenience, this paper proposes a PID tuning method using a cosine similarity measure of SVNSs and genetic algorithm (GA) to improve the existing PID tuning method. In the tuning process, the step response characteristic values (rising time, settling time, overshoot ratio, undershoot ratio, peak time, and steady-state error) of the control system are converted into the single-valued neutrosophic set (SVNS) by the neutrosophic membership functions (Neutrosophication). Then the values of three appropriate parameters in a PID controller… More >

  • Open Access

    ARTICLE

    An Intelligent Predictive Model-Based Multi-Response Optimization of EDM Process

    N. Ganesh1, R. K. Ghadai2, A. K. Bhoi3, K. Kalita4,*, Xiao-Zhi Gao5

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 459-476, 2020, DOI:10.32604/cmes.2020.09645

    Abstract Electrical Discharge Machining (EDM) is a popular non-traditional machining process that is widely used due to its ability to machine hard and brittle materials. It does not require a cutting tool and can machine complex geometries easily. However, it suffers from drawbacks like a poor rate of machining and excessive tool wear. In this research, an attempt is made to address these issues by using an intelligent predictive model coupled global optimization approach to predict suitable combinations of input parameters (current, pulse on-time and pulse off-time) that would effectively increase the material removal rate and minimize the tool wear. The… More >

  • Open Access

    ARTICLE

    Directional Modulation Based on a Quantum Genetic Algorithm for a Multiple-Reflection Model

    Yuwei Huang1, 2, Xiubo Chen1, 3, *, Kaiguo Yuan1, 3, Jianyi Zhang4, Biao Liu2

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1771-1783, 2020, DOI:10.32604/cmc.2020.09905

    Abstract Directional modulation is one of the hot topics in data security researches. To fulfill the requirements of communication security in wireless environment with multiple paths, this study takes into account the factors of reflections and antenna radiation pattern for directional modulation. Unlike other previous works, a novel multiple-reflection model, which is more realistic and complex than simplified two-ray reflection models, is proposed based on two reflectors. Another focus is a quantum genetic algorithm applied to optimize antenna excitation in a phased directional modulation antenna array. The quantum approach has strengths in convergence speed and the globe searching ability for the… More >

  • Open Access

    ARTICLE

    A Genetic Algorithm to Solve Capacity Assignment Problem in a Flow Network

    Ahmed Y. Hamed1, Monagi H. Alkinani2, M. R. Hassan3, *

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1579-1586, 2020, DOI:10.32604/cmc.2020.010881

    Abstract Computer networks and power transmission networks are treated as capacitated flow networks. A capacitated flow network may partially fail due to maintenance. Therefore, the capacity of each edge should be optimally assigned to face critical situations—i.e., to keep the network functioning normally in the case of failure at one or more edges. The robust design problem (RDP) in a capacitated flow network is to search for the minimum capacity assignment of each edge such that the network still survived even under the edge’s failure. The RDP is known as NP-hard. Thus, capacity assignment problem subject to system reliability and total… More >

  • Open Access

    ARTICLE

    A Statistical Model for Phase Difference Spectrum of Ground-Motion and Its Application in Generating Non-Stationary Seismic Waves

    Dongsheng Du1,*, Sheng Shi1, Weizhi Xu1, Chen Kong2, Shuguang Wang1, Weiwei Li1

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.1, pp. 265-285, 2020, DOI:10.32604/cmes.2020.09151

    Abstract The intensity non-stationarity is one of the most important features of earthquake records. Modeling of this feature is significant to the generation of arti- ficial earthquake waves. Based on the theory of phase difference spectrum, an intensity non-stationary envelope function with log-normal form is proposed. Through a tremendous amount of earthquake records downloaded on Kik-net, a parameter fitting procedure using the genetic algorithm is conducted to obtain the value of model parameters under different magnitudes, epicenter distances and site conditions. A numerical example is presented to describe the procedure of generating fully non-stationary ground motions via spectral representation, and the… More >

  • Open Access

    ARTICLE

    Privacy-Preserving Genetic Algorithm Outsourcing in Cloud Computing

    Leqi Jiang1, 2, Zhangjie Fu1, 2, *

    Journal of Cyber Security, Vol.2, No.1, pp. 49-61, 2020, DOI:10.32604/jcs.2020.09308

    Abstract Genetic Algorithm (GA) has been widely used to solve various optimization problems. As the solving process of GA requires large storage and computing resources, it is well motivated to outsource the solving process of GA to the cloud server. However, the algorithm user would never want his data to be disclosed to cloud server. Thus, it is necessary for the user to encrypt the data before transmitting them to the server. But the user will encounter a new problem. The arithmetic operations we are familiar with cannot work directly in the ciphertext domain. In this paper, a privacy-preserving outsourced genetic… More >

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