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An Optimizing Method of OFDM Radar Communication and Jamming Shared Waveform Based on improved greedy algorithm

IEEE ACCESS 2020年 8卷 186462-186473页

作者： Zhu, Shengkun Yang, Ruijuan Li, Xiaobai Zuo, Jiajun Li, Dongjin Ding, Yating Air Force Early Warning Acad Peoples Liberat Army Wuhan 430000 Peoples R China Wuhan Univ Dept Sociol Wuhan 430000 Peoples R China

Orthogonal frequency division multiplexing (OFDM) has been widely used as radar, communication, and jamming shared waveform. To improve the power utilization and efficiency of radar, communication, and jamming integrated system, we propose an adaptive OFDM shared waveform design method. Considering the problem of jamming path propagation loss and sensitivity of frequency response error of radar and communication channels, we propose a robust OFDM shared waveform design method. Firstly, the suppressed jamming entropy model, the detection probability (Pd) of the stationary point target model, the data information rate (DIR) model with a given bit error rate (BER) are formulated. With the constraints on total power and BER, the adaptive and the robust OFDM optimization problems are formulated. Then we derive the Karush-Kuhn-Tucker (KKT) conditions of the two optimization problems and an improved greedy algorithm is proposed to solve the optimization problems, and the optimal power and bit allocation schemes for the two problems are obtained. Finally, we present several numerical results to demonstrate the effectiveness of the proposed method.

关键词： OFDM Jamming Entropy Radar detection Adaptation models Optimization Orthogonal frequency division multiplexing (OFDM) adaptive OFDM shared waveform design robust OFDM shared waveform design suppressed jamming entropy detection probability data information rate improved greedy algorithm

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A personalised travel route recommendation method based on an improved greedy algorithm

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INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS 2023年第4期17卷 399-413页

作者： Shang, Qun Jiangsu Vocat Inst Commerce Coll Culture & Tourism Nanjing 211168 Peoples R China

In order to improve the low accuracy, recall rate, and popularity of the traditional method, this paper proposes a personalised tourism route recommendation method based on the improved greedy algorithm. Firstly, the attractiveness rating index of tourist attractions is established, the weight of the index is determined by the normalisation method, and the attractiveness rating is obtained by combining the condition evaluation matrix and potential evaluation matrix. Then, the greedy algorithm is improved by decomsolving the maximal link subgraph to find the biggest node of influence, and the individual contribution value of tourism route resource knowledge is calculated by using the improved greedy algorithm. Finally, personalised tourism route resources are recommended according to different individual contribution values. The results show that the maximum recommendation accuracy of this method can reach 96%, the maximum recall rate can reach 80%, and the maximum popularity is close to 4.8.

关键词： maximal unicom subgraph perceptual sorting greedy decision-making range attractiveness rating improved greedy algorithm personalised recommendation

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Temporary Parking Reservation for Trucks in Urban Commercial Districts Based on improved greedy algorithm 7

Temporary Parking Reservation for Trucks in Urban Commercial...

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IEEE 7th International Conference on Intelligent Transportation Engineering (ICITE)

作者： Wang, Yi Wang, Xiang Zan, Yuyao Gao, Ronghuan Miao, Lingyi Soochow Univ Sch Rail Transportat Suzhou Peoples R China

ISBN: (纸本)9781665460071

Urban commercial districts rely heavily on trucks for transportation of goods. The parking demand generated by trucks loading and unloading goods is high. Insufficient temporary parking spaces can cause trucks to park randomly while loading and unloading goods. This situation is susceptible to a variety of traffic problems, such as road congestion and occupied pedestrian paths. This study uses automatic vehicle identification (AVI) data to realize the perception of truck parking behavior in commercial districts. A time-sharing reservation method for truck parking in commercial districts based on improved greedy algorithm is proposed according to characteristics of concentrated truck parking demand and short parking duration. Parking space turnover rate improves by adjusting the time point of truck start parking within an acceptable time threshold. An urban commercial district is chosen for validation. Results showed that the total number of trucks in the district is 1,200 per day on weekdays and 1,000 per day on weekends. Heavy and light trucks are dominant and account for about 40% of the total number respectively, while medium-sized trucks account for 20%. Peak hour of truck parking is around 15:00 and the maximum volume can reach 102 vehicles/hour. The average parking time is 31 mins. Taking a weekday as example, 46 temporary parking spaces were needed before optimization, and it was reduced to 20 after optimization, saving 56% of the total temporary parking spaces. This study can effectively enhance the turnover rate of truck parking and save temporary parking space in urban commercial districts.

关键词： commercial district temporary parking truck improved greedy algorithm time-sharing appointment

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An improved greedy Reduction algorithm Based on Neighborhood Rough Set Model for Sensors Screening of Exoskeleton

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IEEE SENSORS JOURNAL 2021年第23期21卷 26964-26977页

作者： Qi, Zhuo Liu, Yali Song, Qiuzhi Zhou, Nengbing Beijing Inst Technol Sch Mechatron Engn Beijing 100081 Peoples R China Beijing Inst Technol Inst Adv Technol Jinan 250300 Peoples R China

The reasonable selection of sensors is essential for sensor fusion for gait recognition, and this paper proposes a reduction method based on an improved greedy algorithm, which can screen a suitable sensor combination with strong distinguishing ability. This novel reduces the multi-sensor system containing 17 sensors by optimizing the neighborhood rough set model, and uses grey relational analysis (GRA) for post-processing to get the optimal reduction. In addition, these reductions under three different terrains are restructured and extended to form the optimal combination. In order to verify the feasibility of the algorithm, we detect the gait phases and compare the accuracy. Results reveal that the number of sensors is reduced from 17 to 8, and the accuracies of three different terrains are increased by 1.05%, 2.633% and 5.934% respectively compared with previous sensors, and increased by 0.533%, 5.950% and 3.834% respectively compared with sensors using principal component analysis (PCA). The Wilcoxon rank sum test is carried out and the results show the algorithm has good performance. The experiments show that this method can screen a few sensors while maintaining or improving the classification ability, and it has high engineering practical significance in wearable robotics field and many other sensor fields.

关键词： Sensors Exoskeletons Robot sensing systems Legged locomotion Hip Sensor systems Sensor fusion Multiple sensors fusion rough set theory grey relation analysis improved greedy algorithm

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Sparse Time-Frequency Representation via greedy Method for Diagnosing Bearing Fault Under Variable Speed Conditions

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2025年 74卷

作者： Yu, Lichao Wang, Chenglong Zhang, Fanghong Luo, Huageng Xiamen Univ Sch Aerosp Engn Xiamen 361102 Peoples R China Chongqing Normal Univ Natl Ctr Appl Math Chongqing 401331 Peoples R China

Time-frequency analysis (TFA) is an effective tool for addressing the issue of bearing fault diagnosis under variable speed conditions. As a class of improved TFA methods, sparse time-frequency representation (STFR) enhances the detection capability for fault features through the pathway of sparse optimization. However, the existing STFR approaches necessitate the use of regularization, making the optimization results highly dependent on the selection of regularization parameters, and thus the optimization performance is difficult to guarantee. To overcome this drawback, a new STFR method using a sparsity adaptive matching pursuit by restricting atom distribution (SAMP-RAD) is proposed. This method resolves the optimization problem of STFR with an improved greedy algorithm, thereby freeing it from the issue of regularization parameter selection. Building upon orthogonal matching pursuit (OMP), SAMP-RAD introduces constraints on atom distribution to enhance noise suppression capabilities and achieves sparsity adaptation by limiting the maximum number of searches for feasible atoms. To accurately evaluate the performance of STFR methods, a new quantitative indicator is also introduced. The effectiveness of SAMP-RAD in overcoming parameter dependency while further enhancing TFA performance is verified with simulated and experimental bearing fault signals under variable speed conditions. Further comparison with other state-of-art methods validates the superiority of the proposed method.

关键词： Time-frequency analysis Optimization Fault diagnosis Transforms Matching pursuit algorithms Accuracy Sparse approximation Noise Interference greedy algorithms Bearing fault diagnosis improved greedy algorithm sparse representation sparsity adaptation time-frequency analysis

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An improved Heuristic algorithm for the Special Case of the Set Covering Problem

An Improved Heuristic Algorithm for the Special Case of the ...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Gonen Avrahami, T. Israeli, U. HIT Fac Management Technol Holon Israel

ISBN: (纸本)9781479909865

The set covering problem is well known as an NPcomplete problem. A common heuristic family of algorithms that solves the problem is the greedy type algorithm. In this study, we have to cover N sites by allocating a minimum number of servers. Each server covers a predefined pattern and, by locating it to a site K, it covers its neighbours according to its pattern. The improved Heuristic algorithm (IHA) presented here looks, at each iteration, for the most '' problematic '' site to be covered and selects the best server that covers it. The study compares the IHA with the greedy algorithm. The results show that in most cases, for symmetric severs, the IHA finds a better solution (more than 10,000 problems were tested). For big problems of above 600 sites, the probability of finding a better solution is over 80%. However, the computing time of the IHA is much higher than that of the greedy algorithm. Analyzing some cases where the greedy algorithm found better solutions than the IHA brought us to the conclusion that the weakness of the IHA resides in the selection part of the minimal server's location. However, we have not yet determined the best solution for these cases.

关键词： Set Covering Problem greedy algorithm improved greedy algorithm Heuristic algorithm

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Dynamic Load Transfer of Active Distribution Network Based on Prediction Information

Dynamic Load Transfer of Active Distribution Network Based o...

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China International Conference on Electricity Distribution (CICED)

作者： Ma, C. L. Ling, W. S. Wu, J. Y. Wang, K. L. Ding, J. Guiyang Power Supply Bur Guiyang Guizhou Peoples R China Shanghai Wiscom Sunest Elect Power Technol Co Ltd Shanghai Peoples R China

ISBN: (纸本)9781538667750

With the high penetration of distributed energy resource (DER), we can realize load transfer by changing switches' states when there is a fault. The computational efficiency can be improved sharply by improved greedy algorithm to "eat load". According to load, photovoltaic power generation and wind power generation prediction information, we can early estimate distribution network state to adjust load transfer solution. The minimum energy loss is set the goal in this paper and, combined with distribution network radial constraints, power flow constraints and output constraints of DERs, dynamic load transfer solution is obtained during fault period. The effectiveness and reliability of dynamic load transfer algorithm is verified by theoretical analysis and simulation.

关键词： Predictive control improved greedy algorithm Serial scenario Dynamic load transfer

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