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Improved DV-Hop based on parallel compact Willow Catkin Optimization algorithm for 3D nodes localization in WSN

WIRELESS NETWORKS 2024年第4期30卷 2017-2039页

作者： Wang, Ruo-Bin Hu, Rui-Bin Geng, Fang-Dong Xu, Lin North China Univ Technol Sch Informat Sci & Technol Beijing 100144 Peoples R China Univ South Australia STEM Adelaide SA 5095 Australia

Wireless sensor networks (WSNs) play a critical role in environmental sensing and data transmission. However, their performances are often hindered by challenges like localization accuracy and storage capacity. Existing variants of DV-Hop algorithm suffer from issues like high memory usage, low localization accuracy, and limited applicability in realistic three-dimensional (3D) environments. To overcome these challenges and solve the localization problem for DV-Hop based WSN nodes in 3D space, this research proposes a novel hybrid optimizer called PCWCO (Parallel compact Willow Catkin Optimization Algorithm). The PCWCO algorithm incorporates compact technique and a new parallel strategy into the Willow Catkin Optimization (WCO) framework, aiming to reduce memory usage while enhancing solution quality. Rigorous numerical validations are conducted using benchmark functions from the CEC2017 to assess the performance of the proposed PCWCO optimizer. The results demonstrate that PCWCO exhibits competitive performance compared to classical intelligent optimization algorithms. Moreover, we synergistically integrate the PCWCO algorithm with DV-Hop to form a hybrid approach called PCWCO-3D-DV-Hop to facilitate the localization efficiency of WSN nodes in 3D space.

关键词： Wireless sensor networks DV-Hop compact technique Parallel strategy Node localization Three-dimensional space

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Improved DV-Hop based on parallel and compact whale optimization algorithm for localization in wireless sensor networks

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WIRELESS NETWORKS 2022年第8期28卷 3411-3428页

作者： Wang, Ruo-Bin Wang, Wei-Feng Xu, Lin Pan, Jeng-Shyang Chu, Shu-Chuan North China Univ Technol Sch Informat Sci & Technol Beijing 100043 Peoples R China North China Univ Technol Beijing Urban Governance Res Ctr Beijing 100043 Peoples R China Univ South Australia STEM Adelaide SA 5095 Australia Shandong Univ Sci & Technol Coll Comp Sci & Engn Qingdao 266590 Peoples R China Flinders Univ S Australia Coll Sci & Engn 1284 South Rd Tonsley SA 5042 Australia

Improving localization performance is one of the critical issues in Wireless Sensor Networks (WSN). As a range-free localization algorithm, Distance Vector-Hop(DV-Hop) is well-known for its simplicity but is hindered by its low accuracy and poor stability. Therefore, it is necessary to improve DV-Hop to achieve a competitive performance. However, the comprehensive performance of WSN is limited by computing and storage capabilities of sensor nodes. In this paper, we propose an algorithm with parallel and compact techniques based on Whale Optimization Algorithm (PCWOA) to improve DV-Hop performance. The compact technique saves memory consumption by reducing the original population. The parallel techniques enhance the ability to jump out of local optimization and improve the solution accuracy. The proposed algorithm is tested on CEC2013 benchmark functions and compared with some popular algorithms and compact algorithms. Experimental results show that the improved algorithm achieves competitive results over compared algorithms. Finally, simulation research is conducted to verify the localization performance of our proposed algorithm.

关键词： Whale optimization algorithm compact technique Parallel technique DV-Hop Wireless sensor networks

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An Efficient 2-D compact Precise-Integration Time-Domain Method for Longitudinally Invariant Waveguiding Structures

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IEEE TRANSACTIONS ON MICROWAVE THEORY AND techniqueS 2013年第7期61卷 2535-2544页

作者： Kang, Zhen Ma, Xikui Xu Zhuansun Xi An Jiao Tong Univ Sch Elect Engn Key Lab Elect Insulat & Power Equipment Xian 710049 Shaanxi Peoples R China

Based on both the compact technique and the precise-integration (PI) technique, a 2-D compact precise-integration time-domain method (CPITD) is developed in order to mitigate the rapidly growing numerical dispersion errors of a recently proposed compact finite-difference time-domain (FDTD) algorithm with increased time-step size when modeling electrically large and longitudinally invariant waveguiding structures. The stability condition and the dispersion equation of the new algorithm are both derived analytically. The provided enhancement over the FDTD, compact FDTD, and the conventional PITD methods is exhibited through theoretical examination of the dispersion performance, and subsequently, validated by means of numerical experimentation. It is found that with the PI technique, the maximum limit of the time step allowable by the new algorithm's stability criterion is much larger than the Courant-Friedrich-Levy limit of the compact-FDTD method, more particularly, numerical dispersion errors can be made nearly independent of time-step size, i.e., an appreciable reduction of numerical dispersion error is achievable at any time-step size in the simulations. Numerical experimentations of typical waveguide structures verify and validate the very promising theoretical results. This CPITD algorithm will be very useful in electrically large and longitudinally invariant waveguiding structures since the decreased number of grid points in the 2-D domain greatly reduces the memory requirements and also the overall computational time, and the PI technique nearly removes the impact of time-step size on the numerical dispersion, and as a consequence, significantly reduces numerical dispersion error for any time-step size.

关键词： compact technique electrically large and longitudinally invariant precise-integration time-domain (PITD) method waveguides

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Optimal operation of multiple integrated energy systems based on a hybrid Taguchi-compact salp swarm algorithm

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IET RENEWABLE POWER GENERATION 2023年第13期17卷 3355-3372页

作者： Fu, Yang Shan, Jie Li, Zhenkun Xie, Bolin Shanghai Univ Elect Power Shanghai Peoples R China South China Univ Technol Guangzhou Peoples R China

With the rapid development of integrated energy system (IES), it has become a trend to form multiple integrated energy systems (MIESs) in a certain region. However, there is a lack of coordination and cooperation among MIESs. This paper proposes an optimal operation model of MIESs with four cost objectives, which focuses on energy interaction among MIESs. As a non-linear and large optimization problem, it is difficult for conventional mathematical methods to solve. Hence, this paper proposes a hybrid Taguchi-compact salp swarm algorithm (TCSSA). The compact technique can save the operation memory of model. Taguchi method can improve the convergence speed and solution accuracy of model. The proposed algorithm is tested on 28 benchmark functions and applied to optimal operation of MIESs. Results demonstrate that: (1) compared with other famous algorithms, TCSSA can provide more efficient execution and better solutions. (2) The optimal operation of MIESs based on TCSSA can achieve the complementary of energy advantages, which effectively reduces the total cost of MIESs (up to 9.67%). An optimal operation model of multiple energy integrated systems with four cost objectives are proposed, which considers energy interaction. Improved and implemented two different compact salp swarm algorithm, and then propose the hybrid Taguchi-compact salp swarm ***

关键词： compact technique integrated energy system multiple systems salp swarm algorithm Taguchi method

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UAV path planning in mountain areas based on a hybrid parallel compact arithmetic optimization algorithm

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NEURAL COMPUTING & APPLICATIONS 2023年 1-16页

作者： Wang, Ruo-Bin Wang, Wei-Feng Geng, Fang-Dong Pan, Jeng-Shyang Chu, Shu-Chuan Xu, Lin North China Univ Technol Sch Informat Sci & Technol Beijing 100144 Peoples R China North China Univ Technol Beijing Urban Governance Res Ctr Beijing 100144 Peoples R China Univ South Australia STEM Adelaide 5095 Australia Shandong Univ Sci & Technol Coll Comp Sci & Engn Qingdao 266590 Peoples R China Flinders Univ S Australia Coll Sci & Engn 1284 South Rd Tonsley SA 5042 Australia

Unmanned Aerial Vehicle (UAV) path planning is one of the core components of its entire autonomous control system. The main challenge lies in efficiently obtaining an optimal flight route in complex environments, especially in mountain areas. To address this, we propose a novel version of arithmetic optimization algorithm (AOA), named parallel and compact AOA (PCAOA). In PCAOA, the compact technique can save the memory of UAV and shorten the calculation time, and the parallel technique can quicken the convergence speed and improve the solution accuracy. In addition, the flight path generated by PCAOA is smoothed with cubic B-spline curves, making the path suitable for a UAV. The performance of PCAOA is demonstrated on 23 benchmark functions. Experimental results show that PCAOA achieves competitive results. Finally, the simulation studies are conducted to verify that PCAOA can successfully acquire a feasible and effective route in different mountain areas.

关键词： UAV path planning Parallel technique compact technique Arithmetic optimization algorithm

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A High-Order 2-D CPITD Method for Electrically Large Waveguide Analysis

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IEEE MICROWAVE AND WIRELESS COMPONENTS LETTERS 2016年第2期26卷 83-85页

作者： Kang, Zhen Ma, Xikui Liu, Qi Xi An Jiao Tong Univ Sch Elect Engn State Key Lab Elect Insulat & Power Equipment Xian 710049 Shaanxi Peoples R China

Based on the fourth-order finite difference (FD) scheme, a modified compact two dimensional precise integration time domain (CPITD) method, called CPITD(4), is proposed to mitigate the numerical dispersion errors of the CPITD algorithm when modeling electrically large and longitudinally invariant wave-guiding structures. Both the stability condition and the dispersion equation of the CPITD(4) method are derived analytically. It is found that the dispersion error of the CPITD(4) method is much smaller than that of the CPITD method. In particular, it should be pointed out that the CPITD(4) method can improve the performance of the CPITD method when beta(z)/beta leaves away from 1. Numerical experiments of typical waveguide structures validate and verify that the CPITD(4) method can decrease the calculated error without increasing the memory requirement and the execution time for all the cases.

关键词： compact technique electrically large and longitudinally invariant fourth-order finite difference scheme precise integration time domain method waveguides

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Stability Condition and Numerical Dispersion of Fourth-Order compact Precise-Integration Time-Domain Method

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IEEE TRANSACTIONS ON MAGNETICS 2019年第6期55卷 1-4页

作者： Kang, Zhen Ma, Xikui Yang, Fang Li, Weilin Zhao, Xin Wu, Xuanlyu Wu, Xiaohua Northwestern Polytech Univ Sch Automat Dept Elect Engn Xian 710072 Shaanxi Peoples R China Xi An Jiao Tong Univ State Key Lab Elect Insulat & Power Equipment Sch Elect Engn Xian 710049 Shaanxi Peoples R China Xian Univ Sci & Technol Sch Elect & Control Engn Xian 710054 Shaanxi Peoples R China

In order to mitigate the numerical dispersion errors of the compact precise integration time-domain (CPITD) algorithm, the fourth-order CPITD [CPITD(4)] method is proposed recently which is based on the fourth-order finite-difference scheme and the precise integration technique. Both the stability condition and the numerical dispersion equation have been obtained. In this paper, the numerical dispersion characteristics of the CPITD(4) method, especially the improvement of the numerical dispersion by using the fourth-order finite-difference scheme are discussed in detail. It is found that the numerical dispersion errors of the CPITD(4) method are much less than those of the CPITD, compact finite-difference time-domain (CFDTD), and CFDTD(2,4) methods and can be made nearly independent of the time-step size. Furthermore, the numerical experiments validate the accuracy and the efficiency of the CPITD(4) method, and also verify our analysis of the numerical dispersion characteristics of the CPITD(4) method.

关键词： compact technique fourth-order finite-difference scheme numerical dispersion precise-integration (PI) time-domain method stability

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A parallel compact firefly algorithm for the control of variable pitch wind turbine

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2022年第0期111卷

作者： Shan, Jie Chu, Shu-Chuan Weng, Shao-Wei Pan, Jeng-Shyang Jiang, Shi-Jie Zheng, Shi-Guang Fujian Univ Technol Sch Elect Engn & Phys Fuzhou 350000 Peoples R China Shandong Univ Sci & Technol Coll Comp Sci & Engn Qingdao 266590 Peoples R China Flinders Univ S Australia Coll Sci & Engn 1284 South Rd Clovelly Pk SA 5042 Australia Shanghai Univ Elect Power Sch Elect Power Engn Shanghai 200090 Peoples R China

Firefly algorithm (FA) is a meta-heuristic optimization algorithm inspired by the flickering behavior of fireflies. Due to its excellent performance, it has been widely used in engineering field. However, FA is a population-based algorithm, which needs to occupy a lot of running memory. It is adverse for some small wind turbines or scenarios with limited memory Therefore, this paper proposes an improved firefly algorithm, called parallel compact firefly algorithm (PCFA). The compact technique helps FA save operation memory, which is advantageous for some usage scenarios limited memory. And the parallel technique helps compact FA achieve better solutions and faster convergence. The proposed PCFA was tested on 28 benchmark functions and applied to the proportional-integral-derivative (PID) parameter tuning of the variable pitch wind turbine. Results demonstrate that (1) PCFA is superior to common compact optimization algorithms not only on less memory consumption, but also on more competitive solutions and faster convergence. (2) PCFA shows the better applicability in the PID parameter tuning of variable pitch wind turbine. It can availably smooth the power output of wind turbine under less memory consumption.

关键词： Firefly algorithm compact technique Parallel technique Communication strategies Variable pitch wind turbine

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