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RISS 인기검색어
- 검색키워드
- 저자 : Jingmin Wei (검색결과 5 건)
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WEI Zhendong,DU Jingmin,LIAO Lihui,Yang Gang,LI Baoren 유공압건설기계학회 2015 유공압건설기계학회 학술대회논문집 Vol.2015 No.10
According to theory of phononic crystals (PCs), a ship hydraulic pipeline isolator with one-dimensional periodic composite structure is designed, which is composed of metal and rubber. The vibration of ship hydraulic pipeline can be suppressed by the band gaps (BGs) of the isolator. The band structure and frequency response function (FRF) of the isolator is figured out by the finite element method (FEM). To obtain the best frequency ranges and width of the BGs, the influences of various material, lattice constant and fineness ratio are considered, and the best structure parameters were also obtained. The results revealed that the isolator has axial vibration BGs with frequencies from 400 Hz to 10000 Hz, and the maximum vibration attenuation is up to 150 dB. The research provides a new technical method to control vibration of ship hydraulic pipeline.
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Load Prediction Based on Optimization Ant Colony Algorithm
Li Wei,Tang Jingmin,Ma Han,Fan Min,Liu Simiao,Wang Jie 대한전기학회 2023 Vol.18 No.1
Short-term load in the power system is associated with huge computational consumption and low model utilization. Large input fl uctuation tends to increase the training error of the neural network prediction model and reduce its generalization ability. To cope with this problem, this study aimed to introduce a method of radial basis function neural network algorithm based on least squares support vector machine algorithm. Based on the electricity market in an area of Yunnan province, the short-term loads were forecasted with historical data. First, the ant colony algorithm was improved using the chaos theory. Second, the improved ant colony was used to search least squares support vector machine and output the optimal parameters of the model. Then, the optimized model was used to train the data samples, and the output regression machine was used to provide better structures and parameters for the radial basis function neural network. The fi ndings showed that compared with multiple prediction methods, the algorithm in this paper reduces the learning time and improves the fi tting degree of the algorithm on the basis of improving the prediction accuracy. It shows that the algorithm in this paper has great advantages and good application prospects.
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Load Prediction Based on Optimization Ant Colony Algorithm
Li Wei,Tang Jingmin,Ma Han,Fan Min,Liu Simiao,Wang Jie 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.1
Short-term load in the power system is associated with huge computational consumption and low model utilization. Large input fluctuation tends to increase the training error of the neural network prediction model and reduce its generalization ability. To cope with this problem, this study aimed to introduce a method of radial basis function neural network algorithm based on least squares support vector machine algorithm. Based on the electricity market in an area of Yunnan province, the short-term loads were forecasted with historical data. First, the ant colony algorithm was improved using the chaos theory. Second, the improved ant colony was used to search least squares support vector machine and output the optimal parameters of the model. Then, the optimized model was used to train the data samples, and the output regression machine was used to provide better structures and parameters for the radial basis function neural network. The findings showed that compared with multiple prediction methods, the algorithm in this paper reduces the learning time and improves the fitting degree of the algorithm on the basis of improving the prediction accuracy. It shows that the algorithm in this paper has great advantages and good application prospects.
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Research on Low Shock Optimization Control of Ship Steering Hydraulic System
Lihui Liao,Baoren Li,Jingmin DU,Zhendong Wei 유공압건설기계학회 2015 유공압건설기계학회 학술대회논문집 Vol.2015 No.10
In this study, the valve control ship steering hydraulic system (SSHS) is designed and set up for research on the low hydraulic shock control. As the hydraulic shock phenomenon is serious with traditional PID control, a fuzzy control method is proposed to replace the traditional proportional-integral-differential (PID) control method for low shock optimization control of the valve control ship steering hydraulic system (VCSSHS) through reasonable design of fuzzy control rules. Simulation models of the VCSSHS are set up to have a comparative research of the traditional PID control method and the proposed fuzzy control method, which indicates that the proposed fuzzy control method could greatly reduce the amplitude of hydraulic shock in the process of ship rudder position adjustment.
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DNALS : A Recommendation Algorithm Based on Chinese Vocabulary Emotion Analysis of Songs
Chengzhou Fu,Weiquan Zeng,Yong Tang,Lingxiao Chen,Jingmin Wei 보안공학연구지원센터 2016 International Journal of u- and e- Service, Scienc Vol.9 No.9
The lyrics play important roles in emotion expression of songs, as well as the emotion words of the lyrics reveal the emotion theme of songs. By extracting the lyrics’ emotion information, this paper uses songs’ emotion themes as the recommended standard. We get all kinds of emotion information extraction coefficient combining emotion gene sequences of lyrics which named DNALS (DNA for Lyrics of Songs), and then put forward the DNALS recommendation algorithm based on emotion analysis. By analyzing the emotion information of user’s historical music data, we recommend to the user a list of songs with similar themes emotion, so as to help the users to find songs for mood.
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