Fuzzy Shannon wavelet finite element methodology of coupled heat transfer analysis for clearance leakage flow of single screw compressor

Zhao, Bin; Song, Haoyang

doi:10.1007/s00366-020-01259-6

Cited by 17 publications

(9 citation statements)

References 30 publications

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“…The control with I d = 0 is adopted. At this time, exciting magnetic field of exciting winding occurs on d axis along [12].…”

Section: Mathematical Model Of Mlsmmentioning

confidence: 99%

Retracted: Research on wavelet neural network PID control of maglev linear synchronous motor

Mao

2022

IET Circuits, Devices & Syst

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Retraction: [Jun Mao, Jun Ma, Research on wavelet neural network PID control of maglev linear synchronous motor, IET Circuits, Devices & Systems 2022 (https://doi.org/10.1049/cds2.12136)]. The above article from IET Circuits, Devices & Systems, published online on 8 December 2022 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor‐in‐Chief, Harry E. Ruda, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.

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“…The control with I d = 0 is adopted. At this time, exciting magnetic field of exciting winding occurs on d axis along [12].…”

Section: Mathematical Model Of Mlsmmentioning

confidence: 99%

Retracted: Research on wavelet neural network PID control of maglev linear synchronous motor

Mao

2022

IET Circuits, Devices & Syst

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“…System can give full play to the advantages of WSN technology, supervise vehicles and goods on the way, realize the whole process monitoring and real-time alarm, improve the coverage of information collection and the stability of information transmission, ensure the security of goods and vehicles, and improve the efficiency and level of logistics management. B-MAC protocol is applied in WSN in this research [12,13].…”

Section: Design Of Wsn In Logistics Carriage Supervisorymentioning

confidence: 99%

Research on Efficiency Optimization of Logistics Vehicle Monitoring Model Based on Wireless Sensor Network

Zhou¹

2023

JICTS

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For enhance running effectiveness efficiency of logistics carriage supervisory depended on wireless sensor network (WSN), a novel wireless sensor network optimized by improved bat algorithm is established. Firstly, working theory and system framework of WSN depended on logistics monitoring system are analyzed. Secondly, B-MAC protocol is used in proposed wireless sensor network, and corresponding models are established, and recovery ratio of wireless sensor network is defined, and node deployment optimization of wireless sensor network is constructed. Thirdly, the optimization algorithm of node deployment of WSN is designed based on amended bat algorithm, and analysis procedure of this algorithm is established. Finally, a simulation analysis is carried out, analysis results show that performance of proposed WSN logistics carriage supervisory based on improved bat algorithm is better, which has quicker convergence speed and higher convergence precision, and reliability of proposed WSN logistics carriage supervisory is improved, the energy consumption of sensor node data transmission is reduced, and the life of WSN is improved. Proposed WSN based on logistics carriage supervisory based on improved BA has higher coverage ratio and higher efficiency. Therefore proposed wireless sensor network based on logistics carriage supervisory based on improved bat algorithm can obtain better monitoring efficiency, which has prospect application view.

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“…As the statistical results have shown the efficiency of TPDA, it should be concerned whether TPDA increases the time complexity of the algorithm [28,29]. In this section, we compare the computational time complexity of TPDA with PSO and DA.…”

Section: Computational Time Complexitymentioning

confidence: 99%

Tent Chaotic Map and Population Classification Evolution Strategy-Based Dragonfly Algorithm for Global Optimization

Wang

Zhang

et al. 2022

Mathematical Problems in Engineering

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Dragonfly algorithm (DA) is a recently proposed optimization algorithm based on swarm intelligence, which has been successfully applied in function optimization, feature selection, parameter adjustment, etc. However, it fails to take individual optimal position into consideration but only relies on population optimal position and 5 behaviours to update individual position, leading to low accuracy, slow convergence, and local optima. To overcome these drawbacks, Tent Chaotic Map and Population Classification Evolution Strategy-Based Dragonfly Algorithm (TPDA) is proposed. Tent chaotic map is used to initialize the population, making individuals distributed more uniformly in search space to improve population diversity and search efficiency. Population is classified according to individual fitness value, and different position update methods are adopted for different types of individuals to guide the search process and improve the ability of TPDA to jump out of local optima, thus realizing a balance between exploration and exploitation. The efficiency of TPDA has been validated by tests on 18 basic unconstrained benchmark functions. A comparative performance analysis between TPDA, Particle Swarm Optimization (PSO), DA, and Adaptive Learning Factor and Differential Evolution-Based Dragonfly Algorithm (ADDA) has been carried out. Experimental and statistical results demonstrate that TPDA gives significantly better performances compared with PSO, DA, and ADDA on the average and standard deviation in all 18 functions. The global optimization capability of TPDA on high-dimensional functions and the comparison of the time complexity of TPDA and other swarm intelligence algorithms is also verified in the paper. The results indicate that TPDA is able to perform better on optimizing functions without consuming more computational time.

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Fuzzy Shannon wavelet finite element methodology of coupled heat transfer analysis for clearance leakage flow of single screw compressor

Cited by 17 publications

References 30 publications

Retracted: Research on wavelet neural network PID control of maglev linear synchronous motor

Retracted: Research on wavelet neural network PID control of maglev linear synchronous motor

Research on Efficiency Optimization of Logistics Vehicle Monitoring Model Based on Wireless Sensor Network

Tent Chaotic Map and Population Classification Evolution Strategy-Based Dragonfly Algorithm for Global Optimization

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