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Articles 1261 - 1290 of 6663

Full-Text Articles in Numerical Analysis and Scientific Computing

Sis-Based Modeling And Simulation Analysis On Exercise Benefit Perception Transmission, Lei Wang, Jinhai Sun, Tuojian Li Dec 2022

Sis-Based Modeling And Simulation Analysis On Exercise Benefit Perception Transmission, Lei Wang, Jinhai Sun, Tuojian Li

Journal of System Simulation

Abstract: In order to distinguish the relationship between individual health behavior change and collective health behavior emergence, deal with the challenges of mathematical description of typical health information dissemination processes in social networks and social experiments, SIS(susceptible-infected-susceptible)model is introduced to simulate the dissemination process of classical health information exercise effect perception to meet the requirements of social system complexity, individual diversity and intelligence. To carry out numerical experiments on the propagation process of exercise effect perception to identify the phase change process of the collective health behavior emergence, agent-based modeling and simulation are utilized through NetLogo. Experimental results show …


Research On Low Computational Predictive Control Strategy Of Three-Level Four-Arm Apf, Guifeng Wang, Jinxing Guo Dec 2022

Research On Low Computational Predictive Control Strategy Of Three-Level Four-Arm Apf, Guifeng Wang, Jinxing Guo

Journal of System Simulation

Abstract: Four-arm active power filter(APF) is an ideal device to the power quality of three-phase four-wire distribution network. Owing to the sufficient number of base vectors, three-level four-arm APF has better current tracking performance, but the prediction calculation amount is too large when model predictive current control is applied. A model prediction voltage control strategy based on the idea of space stratification is proposed. Based on the deadbeat control idea and the discrete mathematical model in αβγ coordinate system, the expected reference voltage is predicted from the reference current, and the multiple current predictions are converted into the single voltage …


Computer Simulation Of The Light Absorption Band Of The Jumping Spider Isorhodopsin, Noah Zoldak Dec 2022

Computer Simulation Of The Light Absorption Band Of The Jumping Spider Isorhodopsin, Noah Zoldak

Honors Projects

In order to simulate the photoisomerization of the 9-cis Jumping Spider Isorhodopsin (JSiR-1) it is necessary to first simulate its light-absorption band. Here we report on the absorption band simulated using protein models constructed using the advanced Automatic Rhodopsin Modeling (a-ARM) program. A population of S0 models was created and the corresponding S0 to S1 transitions were determined for each member of the resulting population. The calculation resulted in a Gaussian plot showing that the wavelength of the absorption maximum of 560 nm (a violet color) that is consistent, but red-shifted, with respect the experimentally observed value.


Hydrogen Bonding In Small Model Peptides; The Dft And Mp2 Study, Gracie Smith, Martina Kaledin Dec 2022

Hydrogen Bonding In Small Model Peptides; The Dft And Mp2 Study, Gracie Smith, Martina Kaledin

Symposium of Student Scholars

Formamide is a small model compound for the study of the peptide bond. The peptide bond links amino acids together, specifies rigidity to the protein backbone, and includes the essential docking sites for hydrogen-bond-mediated protein folding and protein aggregation, namely, the C=O acceptor and the N-H donor parts. Therefore, the infrared C=O (amide-I) and N-H (amide-A) vibrations provide sensitive and widely used probes into the structure of peptides. This computational chemistry work, we study hydrogen bonds in formamide dimer isomers. We evaluate the accuracy of the density functional theory (DFT) and many-body perturbation theory to the 2nd order (MP2) …


Data-Driven Deep Learning-Based Analysis On Thz Imaging, Haoyan Liu Dec 2022

Data-Driven Deep Learning-Based Analysis On Thz Imaging, Haoyan Liu

Graduate Theses and Dissertations

Breast cancer affects about 12.5% of women population in the United States. Surgical operations are often needed post diagnosis. Breast conserving surgery can help remove malignant tumors while maximizing the remaining healthy tissues. Due to lacking effective real-time tumor analysis tools and a unified operation standard, re-excision rate could be higher than 30% among breast conserving surgery patients. This results in significant physical, physiological, and financial burdens to those patients. This work designs deep learning-based segmentation algorithms that detect tissue type in excised tissues using pulsed THz technology. This work evaluates the algorithms for tissue type classification task among freshly …


Probability Distributions Of The Scalar Potential, Candace Mathews Dec 2022

Probability Distributions Of The Scalar Potential, Candace Mathews

Legacy Theses & Dissertations (2009 - 2024)

In the study of cosmological inflation, string theory and supersymmetry have motivated a wide range of possible inflationary models. These models can be parameterized by a scalar potential V, which is a function of N scalar fields, and determines cosmological parameters such as the vacuum stability and energy density. In principle, we can determine V through high energy physics, such as string theory. In practice, though we may not know the details of V we might have clues about a distribution of plausible V’s, which we can build statistics on to further analyze. The purpose of this thesis defense is …


Turning Density Functional Theory Calculations Into Molecular Mechanics Simulations : Establishing The Fluctuating Density Model For Rna Nucleobases, Christopher A. Myers Dec 2022

Turning Density Functional Theory Calculations Into Molecular Mechanics Simulations : Establishing The Fluctuating Density Model For Rna Nucleobases, Christopher A. Myers

Legacy Theses & Dissertations (2009 - 2024)

Molecular mechanics (MD) simulations and density functional theory (DFT) have been the backbone of computational chemistry for decades. Due to its accuracy and computational feasibility, DFT has become the go-to method for theoretically predicting interaction energies, polarizability, and other electronic properties of small molecules at the quantum mechanical level. Although less fundamental than DFT, molecular mechanics (MM) algorithms have been just as influential in the fields of biology and chemistry, owing their success to the ability to compute measurable, macroscopic quantities for systems with tens of thousands to hundreds of thousands of atoms at a time. Nevertheless, MD simulations would …


Denoising And Deconvolving Sperm Whale Data In The Northern Gulf Of Mexico Using Fourier And Wavelet Techniques, Kendal Mccain Leftwich Dec 2022

Denoising And Deconvolving Sperm Whale Data In The Northern Gulf Of Mexico Using Fourier And Wavelet Techniques, Kendal Mccain Leftwich

LSU New Orleans Theses and Dissertations

The use of underwater acoustics can be an important component in obtaining information from the oceans of the world. It is desirable (but difficult) to compile an acoustic catalog of sounds emitted by various underwater objects to complement optical catalogs. For example, the current visual catalog for whale tail flukes of large marine mammals (whales) can identify even individual whales from their individual fluke characteristics. However, since sperm whales, Physeter microcephalus, do not fluke up when they dive, they cannot be identified in this manner. A corresponding acoustic catalog for sperm whale clicks could be compiled to identify individual …


Conreader: Exploring Implicit Relations In Contracts For Contract Clause Extraction, Weiwen Xu, Yang Deng, Wenqiang Lei, Wenlong Zhao, Tat-Seng Chua, Wai Lam Dec 2022

Conreader: Exploring Implicit Relations In Contracts For Contract Clause Extraction, Weiwen Xu, Yang Deng, Wenqiang Lei, Wenlong Zhao, Tat-Seng Chua, Wai Lam

Research Collection School Of Computing and Information Systems

We study automatic Contract Clause Extraction (CCE) by modeling implicit relations in legal contracts. Existing CCE methods mostly treat contracts as plain text, creating a substantial barrier to understanding contracts of high complexity. In this work, we first comprehensively analyze the complexity issues of contracts and distill out three implicit relations commonly found in contracts, namely, 1) Long-range Context Relation that captures the correlations of distant clauses; 2) Term-Definition Relation that captures the relation between important terms with their corresponding definitions; and 3) Similar Clause Relation that captures the similarities between clauses of the same type. Then we propose a …


Understanding Sentiment Through Context, Richard M.Crowley, M.H. Franco Wong Dec 2022

Understanding Sentiment Through Context, Richard M.Crowley, M.H. Franco Wong

Research Collection School Of Accountancy

We examine whether empirical results using text-based sentiment of U.S. annual reports depend on the underlying context, within documents, from which sentiment is measured. We construct a clause-level measure of context, showing that sentiment is driven by many different contexts and that positive and negative sentiment are driven by different contexts. We then construct context-level sentiment measures and examine whether sentiment works as expected at the context-level across four prediction problems. Our results demonstrate that document-level sentiment exhibits significant noise in prediction and suggest that document-level aggregation of sentiment leads to missed empirical nuances. The contexts driving sentiment results vary …


Pacific: Towards Proactive Conversational Question Answering Over Tabular And Textual Data In Finance, Yang Deng, Wenqiang Lei, Wenxuan Zhang, Wai Lam, Tat-Seng Chua Dec 2022

Pacific: Towards Proactive Conversational Question Answering Over Tabular And Textual Data In Finance, Yang Deng, Wenqiang Lei, Wenxuan Zhang, Wai Lam, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

To facilitate conversational question answering (CQA) over hybrid contexts in finance, we present a new dataset, named PACIFIC. Compared with existing CQA datasets, PACIFIC exhibits three key features: (i) proactivity, (ii) numerical reasoning, and (iii) hybrid context of tables and text. A new task is defined accordingly to study Proactive Conversational Question Answering (PCQA), which combines clarification question generation and CQA. In addition, we propose a novel method, namely UniPCQA, to adapt a hybrid format of input and output content in PCQA into the Seq2Seq problem, including the reformulation of the numerical reasoning process as code generation. UniPCQA performs multi-task …


A Unified Dialogue User Simulator For Few-Shot Data Augmentation, Dazhen Wan, Zheng Zhang, Qi Zhu, Lizi Liao, Minlie Huang Dec 2022

A Unified Dialogue User Simulator For Few-Shot Data Augmentation, Dazhen Wan, Zheng Zhang, Qi Zhu, Lizi Liao, Minlie Huang

Research Collection School Of Computing and Information Systems

Pre-trained language models have shown superior performance in task-oriented dialogues. However, existing datasets are on limited scales, which cannot support large-scale pre-training. Fortunately, various data augmentation methods have been developed to augment largescale task-oriented dialogue corpora. However, they heavily rely on annotated data in the target domain, which require a tremendous amount of data collection and human labeling work. In this paper, we build a unified dialogue user simulation model by pre-training on several publicly available datasets. The model can then be tuned on a target domain with fewshot data. The experiments on a target dataset across multiple domains show …


Detecting Selfish Mining Attacks Against A Blockchain Using Machine Learing, Matthew A. Peterson Dec 2022

Detecting Selfish Mining Attacks Against A Blockchain Using Machine Learing, Matthew A. Peterson

Graduate Theses and Dissertations (2019 - present)

Selfish mining is an attack against a blockchain where miners hide newly discovered blocks instead of publishing them to the rest of the network. Selfish mining has been a potential issue for blockchains since it was first discovered by Eyal and Sirer. It can be used by malicious miners to earn a disproportionate share of the mining rewards or in conjunction with other attacks to steal money from network users. Several of these attacks were launched in 2018, 2019, and 2020 with the attackers stealing as much as $18 Million. Developers made several different attempts to fix this issue, but …


Dronlomaly: Runtime Detection Of Anomalous Drone Behaviors Via Log Analysis And Deep Learning, Lwin Khin Shar, Wei Minn, Nguyen Binh Duong Ta, Jianli Fan, Lingxiao Jiang, Daniel Wai Kiat Lim Dec 2022

Dronlomaly: Runtime Detection Of Anomalous Drone Behaviors Via Log Analysis And Deep Learning, Lwin Khin Shar, Wei Minn, Nguyen Binh Duong Ta, Jianli Fan, Lingxiao Jiang, Daniel Wai Kiat Lim

Research Collection School Of Computing and Information Systems

Drones are increasingly popular and getting used in a variety of missions such as area surveillance, pipeline inspection, cinematography, etc. While the drone is conducting a mission, anomalies such as sensor fault, actuator fault, configuration errors, bugs in controller program, remote cyber- attack, etc., may affect the drone’s physical stability and cause serious safety violations such as crashing into the public. During a flight mission, drones typically log flight status and state units such as GPS coordinates, actuator outputs, accelerator readings, gyroscopic readings, etc. These log data may reflect the above-mentioned anomalies. In this paper, we propose a novel, deep …


Innovative And Effective Spreadsheet Tool For Learning Sentiment Analysis And Prediction, Michelle L. F. Cheong, Jean Yun-Chen Chen Dec 2022

Innovative And Effective Spreadsheet Tool For Learning Sentiment Analysis And Prediction, Michelle L. F. Cheong, Jean Yun-Chen Chen

Research Collection School Of Computing and Information Systems

In this paper, we describe a spreadsheet tool which was developed and implemented to teach sentiment analysis and prediction to university students who are less technically inclined. We adopted the “Use-Modify-Create” cycle to ensure that the students learn the computing concepts and practices in a progressive and active learning manner, and we evaluated the effectiveness of the tool using the Learning Object Evaluation Scale for Students (LOES-S). The evaluation shows that our tool performed well in terms of quality, learn and engagement constructs, and our paired T-test shows strong evidence that, on average, the course module with the tool does …


A Recommendation On How To Teach K-Means In Introductory Analytics Courses, Manoj Thulasidas Dec 2022

A Recommendation On How To Teach K-Means In Introductory Analytics Courses, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

We teach K-Means clustering in introductory data analytics courses because it is one of the simplest and most widely used unsupervised machine learning algorithms. However, one drawback of this algorithm is that it does not offer a clear method to determine the appropriate number of clusters; it does not have a built-in mechanism for K selection. What is usually taught as the solution for the K Selection problem is the so-called elbow method, where we look at the incremental changes in some quality metric (usually, the sum of squared errors, SSE), trying to find a sudden change. In addition to …


An Efficient Annealing-Assisted Differential Evolution For Multi-Parameter Adaptive Latent Factor Analysis, Qing Li, Guansong Pang, Mingsheng Shang Dec 2022

An Efficient Annealing-Assisted Differential Evolution For Multi-Parameter Adaptive Latent Factor Analysis, Qing Li, Guansong Pang, Mingsheng Shang

Research Collection School Of Computing and Information Systems

A high-dimensional and incomplete (HDI) matrix is a typical representation of big data. However, advanced HDI data analysis models tend to have many extra parameters. Manual tuning of these parameters, generally adopting the empirical knowledge, unavoidably leads to additional overhead. Although variable adaptive mechanisms have been proposed, they cannot balance the exploration and exploitation with early convergence. Moreover, learning such multi-parameters brings high computational time, thereby suffering gross accuracy especially when solving a bilinear problem like conducting the commonly used latent factor analysis (LFA) on an HDI matrix. Herein, an efficient annealing-assisted differential evolution for multi-parameter adaptive latent factor analysis …


Mining Competitively-Priced Bundle Configurations, Ezekiel Ong Young, Hady W. Lauw Dec 2022

Mining Competitively-Priced Bundle Configurations, Ezekiel Ong Young, Hady W. Lauw

Research Collection School Of Computing and Information Systems

We examine the bundle configuration problem in the presence of competition. Given a competitor's bundle configuration and pricing, we determine what to bundle together, and at what prices, to maximize the target firm's revenue. We highlight the difficulty in pricing bundles and propose a scalable alternative and an efficient search heuristic to refine the approximate prices. Furthermore, we extend the heuristics proposed by previous work to accommodate the presence of a competitor. We analyze the effectiveness of our proposed models through experimentation on real-life ratings-based preference data.


A Wind Turbine Fault Diagnosis Method Based On Siamese Deep Neural Network, Jiarui Liu, Guotian Yang, Xiaowei Wang Nov 2022

A Wind Turbine Fault Diagnosis Method Based On Siamese Deep Neural Network, Jiarui Liu, Guotian Yang, Xiaowei Wang

Journal of System Simulation

Abstract: In order to effectively extract the fault features of time series data in supervisory control and data acquisition (SCADA), considering the advantages of one-dimensional convolutional neural network (1-D CNN) for extracting local time series features and the advantages of long-term memory (LSTM) which can extract long-term dependent features, a method for fault diagnosis of wind turbines based on 1-D CNN-LSTM is proposed. To solve the problem of the scarcity of fault samples of wind turbines based on the siamese network architecture, a wind fault diagnosis method based on siamese 1-D CNN-LSTM is proposed. The proposed siamese 1-D CNN-LSTM …


Transmission Line Insulator Recognition Based On Artificial Images Data Expansion, Yaru Wang, Kai Yang, Yongjie Zhai, Congbin Guo, Wenqing Zhao, Jie Su Nov 2022

Transmission Line Insulator Recognition Based On Artificial Images Data Expansion, Yaru Wang, Kai Yang, Yongjie Zhai, Congbin Guo, Wenqing Zhao, Jie Su

Journal of System Simulation

Abstract: Deep learning method has developed rapidly in the field of computer vision, but relies on a large quantities of training data. In the task of transmission line insulator automatic detection, problems such as insufficient number of aerial insulator images and poor diversity affect the accuracy of insulator recognition. An artificial insulator images data expansion method is proposed. Artificial insulator images are created by modeling software, and a compensation network is constructed. The artificial images are compensated and optimized by compensation network, and the aerial insulator image data set is expanded by the compensated artificial insulator images. The insulator recognition …


Contribution Rate Calculation Method To System-Of-Systems Based On Interval-Valued Intuitionistic Fuzzy Number Anp, Zejian Ding, Songtao Sun, Zhiwen He, Fei Liu Nov 2022

Contribution Rate Calculation Method To System-Of-Systems Based On Interval-Valued Intuitionistic Fuzzy Number Anp, Zejian Ding, Songtao Sun, Zhiwen He, Fei Liu

Journal of System Simulation

Abstract: Contribution rate to system-of-systems (CRSoS) is mainly used to measure the contribution of an equipment to system of systems (SoS) in system construction. In order to solve some problems in the calculation of CRSoS, a multi-level equipment indicator architecture of "task-ability-indicator- equipment" is proposed. At the same time, considering the characteristics of the equipment indicator architecture, ANP (analytic network process) and IVIFN (interval-valued intuitionistic fuzzy number), a IVIF-ANP calculation method is proposed to obtain more accurate CRSoS. Experiments show that this method can not only solve the problem of the calculation formula of CRSoS, but also obtain more …


Simulation And Effectiveness Evaluation System For Joint Delivery Mission Planning Of Airlift Fleets, Guochen Wang Nov 2022

Simulation And Effectiveness Evaluation System For Joint Delivery Mission Planning Of Airlift Fleets, Guochen Wang

Journal of System Simulation

Abstract: Airlift fleet plays an important role in modern war. Compared with other countries such as the USA and Russia, China's airlift fleet still has obvious shortcomings and deficiencies. To analysis and optimize the future fleet alternatives, a software tool is established with the modules of model construction and management, scenarios editing, mission planning, simulation deduction, effectiveness analysis. This tool mainly focuses on the interactive relationship between the transport aircraft and cargo, airport and so on, as well as the cooperative relationship of different types of aircraft, which can realize the functions of automatic generation of loading schemes, automatic planning …


Bilevel Distributed Optimal Dispatch Of Active Distribution Network With Multi-Microgrids, Yongjun Lin, Xin Chen, Kai Yang, Shanshan Zhou, Qingfei Bai Nov 2022

Bilevel Distributed Optimal Dispatch Of Active Distribution Network With Multi-Microgrids, Yongjun Lin, Xin Chen, Kai Yang, Shanshan Zhou, Qingfei Bai

Journal of System Simulation

Abstract: With continuous increase of the penetration proportion of renewable energy in the distribution network, the traditional centralized dispatching is facing problems such as high pressure of power flow calculation and difficulty in recycling renewable energy, which makes it difficult to guarantee the operation quality of the system. A distributed optimal two-layer scheduling method for active distribution networks with multiple micro-grids is proposed. The upper-level aims to minimize the loss of regional distribution network, the second-order conical relaxation method and synchronous ADMM (alternating direction method of multipliers) algorithm are used to solve the scheduling instructions of the micro-grid connection lines. …


Research On Key Technology Of Uavs Autonomous Landing Based On Relative Precise Point Position, Guohua Kang, Teng Zhao, Yao Fu, Weizheng Xu, Jianyu Wei, Yuhuan Qiu, Junfeng Wu Nov 2022

Research On Key Technology Of Uavs Autonomous Landing Based On Relative Precise Point Position, Guohua Kang, Teng Zhao, Yao Fu, Weizheng Xu, Jianyu Wei, Yuhuan Qiu, Junfeng Wu

Journal of System Simulation

Abstract: In complex sea conditions with wind and waves, the relative motion between unmanned aerial vehicles (UAVs) requiring autonomous landing and ships is highly uncertain. In order to improve the accuracy of relative positioning and control during autonomous landing, and to ensure the safety and reliability of autonomous landing, a relative precise point positioning (RPPP) technique based on differential tropospheric error is proposed. The technology only relies on data link and carrier satellite positioning receiver to eliminate the same error of satellite positioning in the same environment and obtain accurate relative positioning. The combination of proportional navigation and linear quadratic …


Robust Optimal Configuration Of Pv-Energy Storage In Industrial Parks Considering The Uncertainty Of Photovoltaics, Guiting Xue, Boya Shan, Ti Wang, Xiao Wang, Wei Xing, Weiqing Sun Nov 2022

Robust Optimal Configuration Of Pv-Energy Storage In Industrial Parks Considering The Uncertainty Of Photovoltaics, Guiting Xue, Boya Shan, Ti Wang, Xiao Wang, Wei Xing, Weiqing Sun

Journal of System Simulation

Abstract: Research on using rooftop resources in industrial parks to develop photovoltaic projects and reasonable configuration of energy storage will help improve the park's energy economy. To obtain the optimal PV-storage configuration scheme, an industrial park with three types of load demand, namely, cold, heat and electricity, is selected, and a robust optimization allocation model of park PV-storage is established with optimal operating profit as the objective function, considering the increased cost of power purchase caused by the PV uncertainty. The model uses the box uncertainty set in robust optimization for PV intensity, and linearizes the model using pairwise …


Evacuation Model Considering The Restricted View Of The Sign, Yinghua Song, Zheqian Zhang, Feizhou Huo, Danhui Fang Nov 2022

Evacuation Model Considering The Restricted View Of The Sign, Yinghua Song, Zheqian Zhang, Feizhou Huo, Danhui Fang

Journal of System Simulation

Abstract: In order to study the influence of restricted vision on the process of pedestrian evacuation, a cellular automata model of pedestrian evacuation under restricted vision is established. In the model, the evacuation space is divided into three different areas according to the field of view radius, pedestrians have different ways of moving in different areas. Different income parameters are defined to calculate the pedestrian movement income matrix and determine the target position of the pedestrian in the next time step. An evacuation scene is established to simulate the initial density of different pedestrians, the change of the field of …


Simulation Of O2o Platform Transaction Considering The Constituted Information, Wen Zheng, Ke Shi, Jingyi Zhu Nov 2022

Simulation Of O2o Platform Transaction Considering The Constituted Information, Wen Zheng, Ke Shi, Jingyi Zhu

Journal of System Simulation

Abstract: In the transactions concluded with the help of APP, the information intervenes into the transaction process in the form of constituted information. The constituted information is classified into three degrees in a two-sided market. By introducing the three degrees of the constituted information: information acceptance (IA), information diversity (ID) and information loss (IL), the Swarm Class Library and the interactive Agents are designed to construct a systematic O2O (online to offline)platform transaction model, which encapsulates the Consumer/Seller/PlatformAgents. The constituted information acts as the systematic conditions of invoking and judging, and the graphical user interface (GUI) outputs the …


Simulation And Experiment Of An Intelligent Control Model For The Cleaning Of A Rice-Wheat Combine Harvester, Qing Jiang, Rujing Wang Nov 2022

Simulation And Experiment Of An Intelligent Control Model For The Cleaning Of A Rice-Wheat Combine Harvester, Qing Jiang, Rujing Wang

Journal of System Simulation

Abstract: Modeling and simulation of cleaning intelligent control according to the changes of cleaning loss rate and trash content rate is the focus of research and hot issues of intelligent control of rice-wheat combine harvester. A method for acquiring knowledge of the experts' experience and knowledge is constructed based on the flow chart of cleaning control, and a cleaning intelligent control knowledge base for the intelligent control of the field operation environment based on the production rule is proposed. Based on the principle of human-simulating intelligent control, a knowledge inference algorithm for adaptive selection of cleaning regulation strategy is …


Research On Mobile Edge Computing Resource Allocation With Energy Harvesting Device, Changyun Li, Jianbo Li, Xi Xu, Tingli Li Nov 2022

Research On Mobile Edge Computing Resource Allocation With Energy Harvesting Device, Changyun Li, Jianbo Li, Xi Xu, Tingli Li

Journal of System Simulation

Abstract: In order to solve the problem of computing resource allocation of mobile edge computing system with energy gathering ability, an algorithm based on Lyapunov greed optimization (LGO) is proposed. This paper presents a dynamic optimization problem to minimize the combined cost of time delay and energy consumption of mobile devices under the gradual convergence of equipment battery power. Using Lyapunov dynamic optimization theory, the optimization problem is decomposed into three sub-problems of optimal local execution, unloading execution and energy harvesting for each time slot, and the optimal solution of the sub-problems is obtained by linear programming. By selecting the …


Multi-Uav Trajectory Planning Based On Adaptive Segmented Potential Field Method, Guangjian Tian, Jiyang Dai, Jin Ying, Ning Wang Nov 2022

Multi-Uav Trajectory Planning Based On Adaptive Segmented Potential Field Method, Guangjian Tian, Jiyang Dai, Jin Ying, Ning Wang

Journal of System Simulation

Abstract: To solve the problems that the traditional artificial potential field method is prone to fall into the local extreme value, target unreachability and excessive curvature of the planned trajectory curvature in the application of UAV trajectory planning, on the basis of the layered potential field method, a method of adding a second local attractive field at the target point and an attractive set composed of the target attractive field is proposed. This method overcomes the defects of unreachable targets and easy falling into local extremes. In addition, a piecewise function is introduced into the original layered potential field method, …