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An Innovative K-Anonymity Privacy-Preserving algorithm to Improve Data Availability in the Context of Big Data

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Computers, Materials & Continua 2024年第4期79卷 1561-1579页

作者： Linlin Yuan Tiantian Zhang Yuling Chen Yuxiang Yang Huang Li State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China College of Information Engineering Guizhou Open UniversityGuiyang550025China Guizhou Academy of Tobacco Science Guiyang550025China

The development of technologies such as big data and blockchain has brought convenience to life,but at the same time,privacy and security issues are becoming more and more prominent.The K-anonymity algorithm is an effective and low computational complexity privacy-preserving algorithm that can safeguard users’privacy by anonymizing big data.However,the algorithm currently suffers from the problem of focusing only on improving user privacy while ignoring data availability.In addition,ignoring the impact of quasi-identified attributes on sensitive attributes causes the usability of the processed data on statistical analysis to be reduced.Based on this,we propose a new K-anonymity algorithm to solve the privacy security problem in the context of big data,while guaranteeing improved data usability.Specifically,we construct a new information loss function based on the information quantity theory.Considering that different quasi-identification attributes have different impacts on sensitive attributes,we set weights for each quasi-identification attribute when designing the information loss function.In addition,to reduce information loss,we improve K-anonymity in two ways.First,we make the loss of information smaller than in the original table while guaranteeing privacy based on common artificial intelligence algorithms,i.e.,greedy algorithm and 2-means clustering algorithm.In addition,we improve the 2-means clustering algorithm by designing a mean-center method to select the initial center of mass.Meanwhile,we design the K-anonymity algorithm of this scheme based on the constructed information loss function,the improved 2-means clustering algorithm,and the greedy algorithm,which reduces the information loss.Finally,we experimentally demonstrate the effectiveness of the algorithm in improving the effect of 2-means clustering and reducing information loss.

关键词： Blockchain big data K-anonymity 2-means clustering greedy algorithm mean-center method

A greedy path planning algorithm based on pre-path-planning and real-time-conflict for multiple automated guided vehicles in large-scale outdoor scenarios

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High Technology Letters 2023年第3期29卷 279-287页

作者：王腾达 WU Wenjun YANG Feng SUN Teng GAO Qiang Faculty of Information Technology Beijing University of TechnologyBeijing 100124P.R.China The 54th Research Institute of CETC Shijiazhuang 050081P.R.China

With the wide application of automated guided vehicles(AGVs) in large scale outdoor scenarios with complex terrain,the collaborative work of a large number of AGVs becomes the main trend.The effective multi-agent path finding(MAPF) algorithm is urgently needed to ensure the efficiency and realizability of the whole system. The complex terrain of outdoor scenarios is fully considered by using different values of passage cost to quantify different terrain types. The objective of the MAPF problem is to minimize the cost of passage while the Manhattan distance of paths and the time of passage are also evaluated for a comprehensive comparison. The pre-path-planning and real-time-conflict based greedy(PRG) algorithm is proposed as the solution. Simulation is conducted and the proposed PRG algorithm is compared with waiting-stop A^(*) and conflict based search(CBS) algorithms. Results show that the PRG algorithm outperforms the waiting-stop A^(*) algorithm in all three performance indicators,and it is more applicable than the CBS algorithm when a large number of AGVs are working collaboratively with frequent collisions.

关键词： automated guided vehicle(AGV) multi-agent path finding(MAPF) complex terrain greedy algorithm

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Learning capability of the truncated greedy algorithm

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Science China(Information Sciences) 2016年第5期59卷 49-63页

作者： Lin XU Shaobo LIN Zongben XU Institute for Information and System Sciences Xi'an Jiaotong University College of Mathematics and Information Science Wenzhou University

Pure greedy algorithm(PGA), orthogonal greedy algorithm(OGA) and relaxed greedy algorithm(RGA) are three widely used greedy type algorithms in both nonlinear approximation and supervised learning.In this paper, we apply another variant of greedy-type algorithm, called the truncated greedy algorithm(TGA)in the realm of supervised learning and study its learning performance. We rigorously prove that TGA is better than PGA in the sense that TGA possesses the faster learning rate than PGA. Furthermore, in some special cases, we also prove that TGA outperforms OGA and RGA. All these theoretical assertions are verified by both toy simulations and real data experiments.

关键词： supervised learning learning theory generalization capability greedy algorithm truncated greedy algorithm

A greedy algorithm based on joint assignment of airport gates and taxiways in large hub airports

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High Technology Letters 2020年第4期26卷 417-423页

作者：聂彤彤 Wu Wenjun He Qichang Zhang Xuanyi Sun Yang Zhang Yanhua Faculty of Information Technology Beijing University of TechnologyBeijing 100124P.R.China Beijing Capital International Airport Co. LtdBeijing 100621P.R.China

With the rapid development of civil aviation in recent years,the management and assignment of airport resources are becoming more and more difficult.Among the various airport resources,gates and taxiways are very important,therefore,many researchers focus on the airport gate and taxiway assignment problem.However,the joint assignment algorithm of airport gates and taxiways with realistic airport data has not been well studied.A greedy algorithm based on joint assignment of airport gates and taxiways using the data of a large hub airport in China is proposed.The objective is maximizing the ratio of fixed gates and minimizing the ratio of taxiway collisions.Simulation results show that it outperforms other assignment schemes.

关键词： greedy algorithm airport gate taxiway resources assignment

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Using greedy algorithm: DBSCAN revisited II

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2004年第11期 94-101页

作者：岳士弘李平郭继东周水庚 Institute of Industrial Process Control Yining 835000 Hangzhou 310027 China Zhejiang University Yili Teacher’s College

The density-based clustering algorithm presented is different from the classical Density-Based Spatial Clus- tering of Applications with Noise (DBSCAN) (Ester et al., 1996), and has the following advantages: first, greedy algorithm substitutes for R*-tree (Bechmann et al., 1990) in DBSCAN to index the clustering space so that the clustering time cost is decreased to great extent and I/O memory load is reduced as well; second, the merging condition to approach to arbi- trary-shaped clusters is designed carefully so that a single threshold can distinguish correctly all clusters in a large spatial dataset though some density-skewed clusters live in it. Finally, authors investigate a robotic navigation and test two artificial datasets by the proposed algorithm to verify its effectiveness and efficiency.

关键词： DBSCAN algorithm greedy algorithm Density-skewed cluster

A greedy algorithm for Solving the Weapon-Target Assignment Problem

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A Greedy Algorithm for Solving the Weapon-Target Assignment ...

greedy Genetic algorithm to Bounded Knapsack Problem

2010 Third International Conference on Education Technology and Training (ETT 2010)

作者： Gaojun Fan Shihai Guo and Xiaodong Liu Aviation Theory Teaching and Researching Department Naval Flying Academy 125001 Huludao Liaoning Province China

The Weapon-Target Assignment （WTA） problem is to find a proper assignment of weapons to targets in order to minimize （maximize） the expected damage of own-force assets （enemy-force assets）. In this paper, we propose a novel greedy algorithm to solve the WTA problem, known as a NP-complete problem. The proposed algorithm according to a greedy rule is successfully applied to the WTA problems based on readjusting the weight of target. Simulation results show that the proposed algorithm can indeed have great efficiency among the different number of weapons and targets.

关键词： Combinatorial optimization greedy algorithm readjusting rule Weapon-Target Assignment （WTA）.

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Greedy Genetic Algorithm to Bounded Knapsack Problem

Automatic spectrum recognition system for charge state analysis in electron cyclotron resonance ion sources

2010 3rd IEEE International Conference on Computer Science and Information Technology—ICCSIT 2010

作者： Sarsij Kaystha Computer Science and Engineering Department Motilal Nehru National Institute of Technology Allahabad India Suneeta Agarwal Computer Science and Engineering Department Motilal Nehru National Institute of Technology Allahabad India

@Sarsij Kaystha$Computer Science and Engineering Department Motilal Nehru National Institute of Technology Allahabad!India@Suneeta Agarwal$Computer Science and Engineering Department Motilal Nehru National Institute o... 详细信息

关键词： component: Bounded Knapsack greedy algorithm Genetic algorithm Combinatorial Problem Optimization

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Nuclear Science and Techniques 2023年第11期34卷 199-211页

作者： Rui Wang Cheng Qian Yu‑Hui Guo Peng Zhang Jin‑Dou Ma Institute of Modern Physics Chinese Academy of SciencesLanzhou 730000China University of Chinese Academy of Sciences Beijing 100049China

The Electron Cyclotron Resonance(ECR)ion source is a critical device for producing highly charged ion beams in various applications.Analyzing the charge-state distribution of the ion beams is essential,but the manual analysis is labor-intensive and prone to inaccuracies due to impurity ions.An automatic spectrum recognition system based on intelligent algorithms was proposed for rapid and accurate chargestate analysis of ECR ion sources.The system employs an adaptive window-length Savitzky-Golay(SG)filtering algorithm,an improved automatic multiscale peak detection(AMPD)algorithm,and a greedy matching algorithm based on the relative distance to accurately match different peaks in the spectra with the corresponding charge-state ion species.Additionally,a user-friendly operator interface was developed for ease of use.Extensive testing on the online ECR ion source platform demonstrates that the system achieves high accuracy,with an average root mean square error of less than 0.1 A for identifying charge-state spectra of ECR ion sources.Moreover,the system minimizes the stand-ard deviation of the first-order derivative of the smoothed signal to 81.1846 A.These results indicate the capability of the designed system to identify ion beam spectra with mass numbers less than Xe,including Xe itself.The proposed automatic spectrum recognition system represents a significant advancement in ECR ion source analysis,offering a rapid and accurate approach for charge-state analysis while enhancing supply efficiency.The exceptional performance and successful imple-mentation of the proposed system on multiple ECR ion source platforms at IMPCAS highlight its potential for widespread adoption in ECR ion source research and applications.

关键词： ECRIS Spectrum recognition SG filtering AMPD algorithm greedy algorithm

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Contact pattern,current immune barrier,and pathogen virulence determines the optimal strategy of further vaccination

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Infectious Disease Modelling 2023年第1期8卷 192-202页

作者： Xiaohao Guo Ziyan Liu Shiting Yang Zeyu Zhao Yichao Guo Guzainuer Abudurusuli Shanlu Zhao Ge Zeng Shixiong Hu Kaiwei Luo Tianmu Chen State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics School of Public HealthXiamen UniversityXiamen City361102Fujian ProvincePeople's Republic of China Hunan Provincial Center for Disease Control and Prevention 405 Furong Middle Road Section OneKaifu DistrictChangsha City410001Hunan ProvincePeople's Republic of China

Background:The current outbreak of novel coronavirus disease 2019 has caused a seriousdisease burden worldwide.Vaccines are an important factor to sustain the epidemic.Although with a relatively high-vaccination worldwide,the decay of vaccine efficacy andthe arising of new variants lead us to the challenge of maintaining a sufficient immunebarrier to protect the population.Method:A case-contact tracking data in Hunan,China,is used to estimate the contactpattern of cases for scenarios including school,workspace,etc,rather than ordinary susceptible population.Based on the estimated vaccine coverage and efficacy,a multi-groupvaccinated-exposed-presymptomatic-symptomatic-asymptomatic-removed model(VEFIAR)with 8 age groups,with each partitioned into 4 vaccination status groups isdeveloped.The optimal dose-wise vaccinating strategy is optimized based on the currentlyestimated immunity barrier of coverage and efficacy,using the greedy algorithm thatminimizes the cumulative cases,population size of hospitalization and fatality respectivelyin a certain future interval.Parameters of Delta and Omicron variants are used respectivelyin the optimization.Results:The estimated contact matrices of cases showed a concentration on middle ages,and has compatible magnitudes compared to estimations from contact surveys in otherstudies.The VEFIAR model is numerically stable.The optimal controled vaccination strategy requires immediate vaccination on the un-vaccinated high-contact population of age30e39 to reduce the cumulative cases,and is stable with different basic reproductionnumbers(R_(0)).As for minimizing hospitalization and fatality,the optimized strategy requires vaccination on the un-vaccinated of both aged 30e39 of high contact frequencyand the vulnerable older.Conclusion:The objective of reducing transmission requires vaccination in age groups ofthe highest contact frequency,with more priority for un-vaccinated than un-fully or fullyvaccinated.The objective of reducing total hospitalization and fatality requires not only tor

关键词： Vaccine Allocation strategy SARS-CoV-2 Optimal control Immune barrier Contact pattern greedy algorithm