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Harris Hawks Algorithm Incorporating Tuna Swarm Algorithm and Differential Variance Strategy
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作者 XU Xiaohan YANG Haima +4 位作者 ZHENG Heqing LI Jun LIU Jin ZHANG Dawei HUANG Hongxin 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2023年第6期461-473,共13页
Because of the low convergence accuracy of the basic Harris Hawks algorithm,which quickly falls into the local optimal,a Harris Hawks algorithm combining tuna swarm algorithm and differential mutation strategy(TDHHO)i... Because of the low convergence accuracy of the basic Harris Hawks algorithm,which quickly falls into the local optimal,a Harris Hawks algorithm combining tuna swarm algorithm and differential mutation strategy(TDHHO)is proposed.The escape energy factor of nonlinear periodic energy decline balances the ability of global exploration and regional development.The parabolic foraging approach of the tuna swarm algorithm is introduced to enhance the global exploration ability of the algorithm and accelerate the convergence speed.The difference variation strategy is used to mutate the individual position and calculate the fitness,and the fitness of the original individual position is compared.The greedy technique is used to select the one with better fitness of the objective function,which increases the diversity of the population and improves the possibility of the algorithm jumping out of the local extreme value.The test function tests the TDHHO algorithm,and compared with other optimization algorithms,the experimental results show that the convergence speed and optimization accuracy of the improved Harris Hawks are improved.Finally,the enhanced Harris Hawks algorithm is applied to engineering optimization and wireless sensor networks(WSN)coverage optimization problems,and the feasibility of the TDHHO algorithm in practical application is further verified. 展开更多
关键词 Harris Hawks optimization nonlinear periodic energy decreases differential mutation strategy wireless sensor networks(WSN)coverage optimization results
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Comparison of diagnostic value of TIRADS,BSRTC,BRAF^(V600E) mutation detection and their combined use in differentiating thyroid nodules
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作者 张于芝 《China Medical Abstracts(Internal Medicine)》 2016年第3期147-148,共2页
Objective To compare the diagnostic efficiency of the thyroid imaging reporting and data system(TIRADS),the Bethesda system for reporting thyroid cytopathology(BSRTC)and BRAFV600Edetection,and their combined use in th... Objective To compare the diagnostic efficiency of the thyroid imaging reporting and data system(TIRADS),the Bethesda system for reporting thyroid cytopathology(BSRTC)and BRAFV600Edetection,and their combined use in the differentiation between benign and malignant thyroid nodules.Methods One hundred 展开更多
关键词 FNAC Comparison of diagnostic value of TIRADS BSRTC BRAF V600E mutation detection and their combined use in differentiating thyroid nodules
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A Discrete Bat Algorithm for Disassembly Sequence Planning 被引量:6
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作者 焦庆龙 徐达 《Journal of Shanghai Jiaotong university(Science)》 EI 2018年第2期276-285,共10页
Based on the bat algorithm(BA), this paper proposes a discrete BA(DBA) approach to optimize the disassembly sequence planning(DSP) problem, for the purpose of obtaining an optimum disassembly sequence(ODS) of a produc... Based on the bat algorithm(BA), this paper proposes a discrete BA(DBA) approach to optimize the disassembly sequence planning(DSP) problem, for the purpose of obtaining an optimum disassembly sequence(ODS) of a product with a high degree of automation and guiding maintenance operation. The BA for solving continuous problems is introduced, and combining with mathematical formulations, the BA is reformed to be the DBA for DSP problems. The fitness function model(FFM) is built to evaluate the quality of disassembly sequences. The optimization performance of the DBA is tested and verified by an application case, and the DBA is compared with the genetic algorithm(GA), particle swarm optimization(PSO) algorithm and differential mutation BA(DMBA). Numerical experiments show that the proposed DBA has a better optimization capability and provides more accurate solutions than the other three algorithms. 展开更多
关键词 disassembly sequence planning(DSP) bat algorithm(BA) discrete BA(DBA) fitness function model(FFM) genetic algorithm(GA) particle swarm optimization(PSO) algorithm differential mutation BA(DMBA)
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