Open Access. Powered by Scholars. Published by Universities.®
Numerical Analysis and Scientific Computing Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (338)
- Artificial Intelligence and Robotics (332)
- Computer Engineering (325)
- Operations Research, Systems Engineering and Industrial Engineering (322)
- Systems Science (315)
-
- Programming Languages and Compilers (104)
- Databases and Information Systems (37)
- Social and Behavioral Sciences (20)
- Data Science (17)
- Theory and Algorithms (15)
- Life Sciences (13)
- Applied Mathematics (11)
- Medicine and Health Sciences (11)
- Physics (10)
- Graphics and Human Computer Interfaces (9)
- Other Computer Sciences (9)
- Software Engineering (9)
- Mathematics (8)
- Numerical Analysis and Computation (8)
- Public Affairs, Public Policy and Public Administration (8)
- Chemistry (7)
- Communication (6)
- Electrical and Computer Engineering (6)
- Oceanography and Atmospheric Sciences and Meteorology (6)
- Statistics and Probability (6)
- Bioinformatics (5)
- Information Security (5)
- Institution
-
- China Simulation Federation (315)
- University of Nebraska - Lincoln (106)
- Singapore Management University (57)
- University of Arkansas, Fayetteville (14)
- Chapman University (5)
-
- University of Kentucky (4)
- American University in Cairo (3)
- City University of New York (CUNY) (3)
- Kennesaw State University (3)
- Southern Methodist University (3)
- Embry-Riddle Aeronautical University (2)
- Old Dominion University (2)
- Portland State University (2)
- The University of Akron (2)
- University of Louisville (2)
- University of Montana (2)
- California Polytechnic State University, San Luis Obispo (1)
- China Medical University (1)
- Clemson University (1)
- Columbus State University (1)
- Marshall University (1)
- Minnesota State University Moorhead (1)
- Murray State University (1)
- New Jersey Institute of Technology (1)
- Purdue University (1)
- San Jose State University (1)
- Stephen F. Austin State University (1)
- Technological University Dublin (1)
- The University of Southern Mississippi (1)
- University at Albany, State University of New York (1)
- Keyword
-
- Simulation (17)
- Deep learning (10)
- Reinforcement learning (8)
- COVID-19 (6)
- Computer generated forces (6)
-
- Modeling (6)
- Machine learning (5)
- Modeling and simulation (5)
- System dynamics (5)
- Body of knowledge (4)
- Datasets (4)
- Fault diagnosis (4)
- Genetic algorithm (4)
- Simulation platform (4)
- Sliding mode control (4)
- Visualization (4)
- Augmented reality (3)
- Bayesian optimization (3)
- Complex network (3)
- Digital twin (3)
- Dynamic model (3)
- Finite element (3)
- Knowledge area (3)
- Machine Learning (3)
- Neural networks (3)
- Optimization (3)
- Path planning (3)
- Python (3)
- Quantized state system (3)
- Simulated annealing (3)
- Publication
-
- Journal of System Simulation (315)
- The R Journal (103)
- Research Collection School Of Computing and Information Systems (54)
- Computer Science and Computer Engineering Undergraduate Honors Theses (5)
- Graduate Theses and Dissertations (5)
-
- Mathematics, Physics, and Computer Science Faculty Articles and Research (4)
- Dissertations (3)
- Mathematics Theses and Dissertations (3)
- Symposium of Student Scholars (3)
- Archived Theses and Dissertations (2)
- Computer Science Faculty Publications (2)
- Department of Agricultural Economics: Dissertations, Theses, and Student Research (2)
- Doctoral Dissertations and Master's Theses (2)
- Electronic Theses and Dissertations (2)
- Graduate Student Theses, Dissertations, & Professional Papers (2)
- Mathematical Sciences Spring Lecture Series (2)
- Publications and Research (2)
- Williams Honors College, Honors Research Projects (2)
- All Dissertations (1)
- Articles (1)
- BioMedicine (1)
- Capstone and Graduation Projects (1)
- Computational and Data Sciences (PhD) Dissertations (1)
- Computer Science ETDs (1)
- Computer Science and Computer Engineering Faculty Publications and Presentations (1)
- Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research (1)
- Discovery Undergraduate Interdisciplinary Research Internship (1)
- Dissertations and Theses Collection (Open Access) (1)
- Dissertations, Theses, and Capstone Projects (1)
- Graduate Theses, Dissertations, and Problem Reports (ETD) (1)
- Publication Type
- File Type
Articles 61 - 90 of 546
Full-Text Articles in Numerical Analysis and Scientific Computing
Hierarchical Control Of Multi-Agent Reinforcement Learning Team In Real-Time Strategy (Rts) Games, Weigui Jair Zhou, Budhitama Subagdja, Ah-Hwee Tan, Darren Wee Sze Ong
Hierarchical Control Of Multi-Agent Reinforcement Learning Team In Real-Time Strategy (Rts) Games, Weigui Jair Zhou, Budhitama Subagdja, Ah-Hwee Tan, Darren Wee Sze Ong
Research Collection School Of Computing and Information Systems
Coordinated control of multi-agent teams is an important task in many real-time strategy (RTS) games. In most prior work, micromanagement is the commonly used strategy whereby individual agents operate independently and make their own combat decisions. On the other extreme, some employ a macromanagement strategy whereby all agents are controlled by a single decision model. In this paper, we propose a hierarchical command and control architecture, consisting of a single high-level and multiple low-level reinforcement learning agents operating in a dynamic environment. This hierarchical model enables the low-level unit agents to make individual decisions while taking commands from the high-level …
Risk-Based Machine Learning Approaches For Probabilistic Transient Stability, Umair Shahzad
Risk-Based Machine Learning Approaches For Probabilistic Transient Stability, Umair Shahzad
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Power systems are getting more complex than ever and are consequently operating close to their limit of stability. Moreover, with the increasing demand of renewable wind generation, and the requirement to maintain a secure power system, the importance of transient stability cannot be overestimated. Considering its significance in power system security, it is important to propose a different approach for enhancing the transient stability, considering uncertainties. Current deterministic industry practices of transient stability assessment ignore the probabilistic nature of variables (fault type, fault location, fault clearing time, etc.). These approaches typically provide a conservative criterion and can result in expensive …
Intelligent Resource Prediction For Hpc And Scientific Workflows, Benjamin Shealy
Intelligent Resource Prediction For Hpc And Scientific Workflows, Benjamin Shealy
All Dissertations
Scientific workflows and high-performance computing (HPC) platforms are critically important to modern scientific research. In order to perform scientific experiments at scale, domain scientists must have knowledge and expertise in software and hardware systems that are highly complex and rapidly evolving. While computational expertise will be essential for domain scientists going forward, any tools or practices that reduce this burden for domain scientists will greatly increase the rate of scientific discoveries. One challenge that exists for domain scientists today is knowing the resource usage patterns of an application for the purpose of resource provisioning. A tool that accurately estimates these …
The R Developer Community Does Have A Strong Software Engineering Culture, Maëlle Salmon, Karthik Ram
The R Developer Community Does Have A Strong Software Engineering Culture, Maëlle Salmon, Karthik Ram
The R Journal
There is a strong software engineering culture in the R developer community. We recommend creating, updating and vetting packages as well as keeping up with community standards. We invite contributions to the rOpenSci project, where participants can gain experience that will shape their work and that of their peers.
Component Damage Source Identification For Critical Infrastructure Systems, Nathan Davis
Component Damage Source Identification For Critical Infrastructure Systems, Nathan Davis
Graduate Theses and Dissertations
Cyber-Physical Systems (CPS) are becoming increasingly prevalent for both Critical Infrastructure and the Industry 4.0 initiative. Bad values within components of the software portion of CPS, or the computer systems, have the potential to cause major damage if left unchecked, and so detection and locating of where these occur is vital. We further define features of these computer systems and create a use-based system topology. We then introduce a function to monitor system integrity and the presence of bad values as well as an algorithm to locate them. We then show an improved version, taking advantage of several system properties …
Analysis Of Titan's Fluvial Features Using Numerical Modeling, Jeshurun Horton
Analysis Of Titan's Fluvial Features Using Numerical Modeling, Jeshurun Horton
Mechanical Engineering Undergraduate Honors Theses
River channels have been observed near the Huygens probe landing site on the surface of Titan, along with evidence of rounded water ice boulders transported through fluid flow. Evidence near the landing site suggests active flow of liquid methane, which has motivated the study of the effects of sediment load and channel sizes on Titan’s fluvial features. A numerical model is used to determine the viscosity, flow velocity, and critical boulder transport diameter based on channel size, slope, and a range of sediment concentrations. This model achieves two ends: first, observed boulder diameters are used to determine the ideal channel …
Rapid Method For Consistency And Concentration Reporting Of Cannabidiol Using 1H-Nmr And Computer-Assisted Chemical Software, Michael A. Fernando
Rapid Method For Consistency And Concentration Reporting Of Cannabidiol Using 1H-Nmr And Computer-Assisted Chemical Software, Michael A. Fernando
University Honors Theses
An integrated computational method was demonstrated with hemp-derived Cannabidiol for an assessment of its purity and concentration. The sample was structurally verified, high purity, and 2.98 mmol/L in dissolved DMSO. The method presented is a general approach to assessing purity and concentration for any small organic molecule in CMC-Assist.
Decentralized Deterministic Multi-Agent Reinforcement Learning, Antoine Grosnit, Desmond Cai, Laura Wynter
Decentralized Deterministic Multi-Agent Reinforcement Learning, Antoine Grosnit, Desmond Cai, Laura Wynter
Research Collection School Of Computing and Information Systems
Recent work in multi-agent reinforcement learning (MARL) by [Zhang, ICML12018] provided the first decentralized actor-critic algorithm to offer convergence guarantees. In that work, policies are stochastic and are defined on finite action spaces. We extend those results to develop a provably-convergent decentralized actor-critic algorithm for learning deterministic policies on continuous action spaces. Deterministic policies are important in many real-world settings. To handle the lack of exploration inherent in deterministic policies we provide results for the off-policy setting as well as the on-policy setting. We provide the main ingredients needed for this problem: the expression of a local deterministic policy gradient, …
Efficient Reinforcement Learning In Resource Allocation Problems Through Permutation Invariant Multi-Task Learning, Desmond Cai, Shiau Hong Lim, Laura Wynter
Efficient Reinforcement Learning In Resource Allocation Problems Through Permutation Invariant Multi-Task Learning, Desmond Cai, Shiau Hong Lim, Laura Wynter
Research Collection School Of Computing and Information Systems
One of the main challenges in real-world reinforcement learning is to learn successfully from limited training samples. We show that in certain settings, the available data can be dramatically increased through a form of multi-task learning, by exploiting an invariance property in the tasks. We provide a theoretical performance bound for the gain in sample efficiency under this setting. This motivates a new approach to multi-task learning, which involves the design of an appropriate neural network architecture and a prioritized task-sampling strategy. We demonstrate empirically the effectiveness of the proposed approach on two real-world sequential resource allocation tasks where this …
Automated Doubt Identification From Informal Reflections Through Hybrid Sentic Patterns And Machine Learning Approach, Siaw Ling Lo, Kar Way Tan, Eng Lieh Ouh
Automated Doubt Identification From Informal Reflections Through Hybrid Sentic Patterns And Machine Learning Approach, Siaw Ling Lo, Kar Way Tan, Eng Lieh Ouh
Research Collection School Of Computing and Information Systems
Do my students understand? The question that lingers in every instructor’s mind after each lesson. With the focus on learner-centered pedagogy, is it feasible to provide timely and relevant guidance to individual learners according to their levels of understanding? One of the options available is to collect reflections from learners after each lesson to extract relevant feedback so that doubts or questions can be addressed in a timely manner. In this paper, we derived a hybrid approach that leverages a novel Doubt Sentic Pattern Detection (SPD) algorithm and a machine learning model to automate the identification of doubts from students’ …
Comparison Of Multiple Imputation Algorithms And Verification Using Whole-Genome Sequencing In The Cmuh Genetic Biobank, Ting-Yuan Liu, Chih-Fan Lin, Hsing-Tsung Wu, Ya-Lun Wu, Yu-Chia Chen, Chi-Chou Liao, Yu-Pao Chou, Dysan Chao, Hsing-Fang Lu, Ya-Sian Chang, Jan-Gowth Chang, Kai-Cheng Hsu, Fuu‑Jen Tsai
Comparison Of Multiple Imputation Algorithms And Verification Using Whole-Genome Sequencing In The Cmuh Genetic Biobank, Ting-Yuan Liu, Chih-Fan Lin, Hsing-Tsung Wu, Ya-Lun Wu, Yu-Chia Chen, Chi-Chou Liao, Yu-Pao Chou, Dysan Chao, Hsing-Fang Lu, Ya-Sian Chang, Jan-Gowth Chang, Kai-Cheng Hsu, Fuu‑Jen Tsai
BioMedicine
A genome-wide association study (GWAS) can be conducted to systematically analyze the contributions of genetic factors to a wide variety of complex diseases. Nevertheless, existing GWASs have provided highly ethnic specific data. Accordingly, to provide data specific to Taiwan, we established a large-scale genetic database in a single medical institution at the China Medical University Hospital. With current technological limitations, microarray analysis can detect only a limited number of single-nucleotide polymorphisms (SNPs) with a minor allele frequency of >1%. Nevertheless, imputation represents a useful alternative means of expanding data. In this study, we compared four imputation algorithms in terms of …
Molecular Dynamics Simulations Of Vibrational Infrared And Raman Spectra Of H5o2+, Oluwaseun Omodemi, Ivonne Meares, Gabriella Garofalo, Martina Kaledin
Molecular Dynamics Simulations Of Vibrational Infrared And Raman Spectra Of H5o2+, Oluwaseun Omodemi, Ivonne Meares, Gabriella Garofalo, Martina Kaledin
Symposium of Student Scholars
We report infrared (IR) and Raman vibrational spectra of H5O2+ protonated water dimer using computational chemistry methods, the normal mode analysis (NMA), and molecular dynamics (MD) simulations. Various computational methods and basis sets were used. We also located the H5O2+ stationary points on the potential energy surface using the Gaussian 16 program. The H5O2+ Zundel complex serves as a benchmark system to study the proton transfer process. We also investigated IR and Raman intensities of other deuterated analogs, such as D5O2+, D4 …
Fuzzy Information Granulation And Improved Rvm For Rolling Bearing Life Prediction, Xiaoman Hu, Wang Yan, Zhicheng Ji
Fuzzy Information Granulation And Improved Rvm For Rolling Bearing Life Prediction, Xiaoman Hu, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: Aiming at the low accuracy in life prediction and unpredictable problems of degenerative performance trends and fluctuation ranges, etc. Of the bearing life prediction, an improved complete ensemble empirical mode decomposition with adaptive noise analysis and fuzzy information granulating method of improved relevance vector machine is proposed. Focusing on bearing data containing a lot of noise, through the improved complete ensemble empirical mode decomposition with adaptive noise analysis in combination with wavelet packet denoising, the principal component analysis is carride out by exitracing a variety of characeteristics of the signal, the effective information is extracted by granulating the fuzzy …
Research On Moffjsp Based On Multi-Strategy Fusion Quantum Particle Swarm Optimization, Cai Min, Wang Yan, Zhicheng Ji
Research On Moffjsp Based On Multi-Strategy Fusion Quantum Particle Swarm Optimization, Cai Min, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: To improve the quality of the optimal scheduling solution set, a quantum particle swarm algorithm with multi-strategy fusion is proposed for the multi-objective fuzzy flexible job shop scheduling problem with fuzzy maximum completion time, fuzzy total machine load, and fuzzy bottleneck machine load as optimization objectives. Chaotic mapping is used to improve the initial population quality, and a Lévy flight strategy is introduced to enhance the algorithm's ability to jump out of the local optimum. The neighborhood search strategy based on machine mutation is designed for local search. Cross operation is used to maintain the diversity of elite individuals, …
Research On Stick-Slip Vibration Level Estimation Of Near-Bit Based On Optimized Xgboost, Hanwen Tang, Zhang Tao, Yumei Li, Li Lei, Jinghua Zhang, Dongliang Hu
Research On Stick-Slip Vibration Level Estimation Of Near-Bit Based On Optimized Xgboost, Hanwen Tang, Zhang Tao, Yumei Li, Li Lei, Jinghua Zhang, Dongliang Hu
Journal of System Simulation
Abstract: Stick-slip vibration is an important limiting factor affecting drilling speed, safety and cost. The establishment of a reliable stick-slip vibration classification model is very important for oil drilling decision-making. A new method based on Bayesian optimization and eXtreme Gradient Boosting (XGBoost) is proposed to evaluate the severity of stick-slip vibration near the bit. The classification processing of the near-bit stick-slip vibration data is carried out. The main feature vectors of the original data is extracted through time domain and frequency domain analysis. A stick-slip vibration level identification and prediction model based on XGBoost is established, and Bayesian algorithm is …
Simulation Of Pedestrian In Multifunctional Passageway Of Metro Station Area Based On Social Force Model, Wang Xi, Zhang Rui, Fei Shuo, Minghang Yang
Simulation Of Pedestrian In Multifunctional Passageway Of Metro Station Area Based On Social Force Model, Wang Xi, Zhang Rui, Fei Shuo, Minghang Yang
Journal of System Simulation
Abstract: Transitional passageway connecting subway stations and commercial facilities is generally designed as the multifunctional passageway, in which the traffic function is the main and the service function is the auxiliary. The impact of the service facilities on both sides of the passage on pedestrian traffic is difficult to be quantitatively analyzed and simulated and modeled. Through measurement, it is found that the viscous effect of service facilities on pedestrian traffic is mainly slowing down the speed or changing the trajectory direction. Through analyzing the horizontal influence range of service facilities, dividing the passage into different areas, and introducing the …
Midcourse Guidance Method Based On Fading Memory Filter For Intercepting Near-Space Gliding Target, Yonghua Fan, Yilun Huangfu, Xiaowen Guo, Chenlu Li, Guofei Li
Midcourse Guidance Method Based On Fading Memory Filter For Intercepting Near-Space Gliding Target, Yonghua Fan, Yilun Huangfu, Xiaowen Guo, Chenlu Li, Guofei Li
Journal of System Simulation
Abstract: Aiming at the interception of hypersonic gliding target in near space, a sliding mode guidance law based on fading memory filtering algorithm is proposed. The accurate motion parameters of the hypersonic target are obtained based on the current statistical model fading memory EKF(Extended Kalman Filter) algorithm. Based on the filtering information and sliding mode control theory, a sliding mode guidance law is designed to adjust the interception trajectory online according to the target maneuver law. The simulation results show that the proposed fading memory filtering algorithm can effectively track the gliding target with high filtering accuracy. For a …
Kernel Block Diagonal Representation Subspace Clustering And Its Convergence Analysis, Maoshan Liu, Zhicheng Ji, Wang Yan, Jianfeng Wang
Kernel Block Diagonal Representation Subspace Clustering And Its Convergence Analysis, Maoshan Liu, Zhicheng Ji, Wang Yan, Jianfeng Wang
Journal of System Simulation
Abstract: Focus on the problems that the linear block diagonal representation subspace clustering cannot effectively handle non-linear visual data, and the regular regularizers cannot directly pursue the k-block diagonal matrix, a kernel block diagonal representation subspace clustering is proposed. In the proposed algorithm, the original input space is mapped into the kernel Hilbert space which is linearly separable, and the spectral clustering is performed in the feature space. The convergence analysis is given, and the strong convex of variables and the boundedness of function is utilized to verify the monotonically decreasing of objective function and the boundedness and convergence of …
Simulation Of Zero-Speed Correction Algorithm For Underground Space Individual Positioning, Yijing Wang, Su Zhong, Li Qing, Li Lei
Simulation Of Zero-Speed Correction Algorithm For Underground Space Individual Positioning, Yijing Wang, Su Zhong, Li Qing, Li Lei
Journal of System Simulation
Abstract: In view of the complex and dangerous collapse environment of the tunnel, the related safety hazards of the positioning system of the tunnel rescuer are intensively analyzed, and the simulation of the inertial device worn on the chest, waist, calf, and foot surface shows that the correction on the foot surface is the best. Focus on the error accumulation of inertial devices, according to the fact that the speed is near zero when the sole of the foot fully touches the ground during walking, the algorithm of zero-speed correction for acceleration and angular velocity is compared, and a combination …
Research On Flexible Job-Shop Dynamic Scheduling Based On Game Theory, Yichen You, Wang Yan, Zhicheng Ji
Research On Flexible Job-Shop Dynamic Scheduling Based On Game Theory, Yichen You, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: To quickly and effectively respond to the machine fault disturbance events in Flexible Job-shop Scheduling Problem (FJSP), a flexible job-shop dynamic scheduling based on game theory is established. A pre-scheduling scheme is generated under Non-Dominated Sort Genetic Algorithm-Ⅱ (NSGA-Ⅱ) algorithm which introduces self-adapted crossover operators to improve the population diversity. For FJSP dynamic scheduling with machine fault, a multi-stage complete information game model is built to better balance the stability and robustness indicators and respond quickly to the machine fault, in which the stability and robustness indicators are mapped to the game players, and a hybrid Nash Equilibrium which …
Combination Forecasting Model Of Photovoltaic Power Based On Empirical Wavelet Transform, Chen Tao, Wang Yan, Zhicheng Ji
Combination Forecasting Model Of Photovoltaic Power Based On Empirical Wavelet Transform, Chen Tao, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: In order to improve the prediction accuracy of short-term photovoltaic power, a variable weight combined prediction model based on Empirical Wavelet Transform (EWT) and PSO-optimized random forest(RF) is proposed. Gray correlation analysis is used to select similar days, EWT is used to decompose the power time series into sub-modes of different frequencies, and three modes of high, medium, and low frequency are reconstructed according to the frequency, PSO-RF and PSO-BP and PSO-LSSVM prediction models are established to dynamically calculate their respective weights for reconstruction, and error correction is performed to output the prediction results. By predicting the output power …
Research On Six Degrees Of Freedom Platform Control In Special Vehicle Simulated Driving Training, Yihao Li, Zhili Zhang, Xiangyang Li, Long Yong
Research On Six Degrees Of Freedom Platform Control In Special Vehicle Simulated Driving Training, Yihao Li, Zhili Zhang, Xiangyang Li, Long Yong
Journal of System Simulation
Abstract: In order to simulate various postures of driving the special vehicles in a limited space, a set of six-degree-of-freedom motion platform for the simulation driving training system of special vehicles is developed. The mechanical structure of the six-degree-of-freedom motion platform is designed to meet the motion posture simulation requirement. The control of each degree of freedom in the motion platform is realized through the design of the embedded control system. The displacement of each electric cylinder is obtained by inverse solution algorithm, and the somatosensory simulation of acceleration and angular displacement is realized by the wash-out algorithm. It has …
Optizimation Of Vaccination Supply Chain Based On Scg In Nanshan District, Zhenning Dong, Shunzhou Huang, Jiajun Chen, Huiqiong Zheng
Optizimation Of Vaccination Supply Chain Based On Scg In Nanshan District, Zhenning Dong, Shunzhou Huang, Jiajun Chen, Huiqiong Zheng
Journal of System Simulation
Abstract: To optimize the vaccination network, inventory strategy and human resource allocation in Nanshan District, Supply Chain Guru's (SCG) network optimization method is used to select 50 alternative stations to decrease the fixed operating cost. SCG's inventory optimization method is used to set inventory strategy for each station, and simulation method is designed to compare total cost of all schemes. To optimize the opening days of vaccination stations, an medical personnel allocation rule is designed, which reduces some stations' opening days to 2 or 3 days and increases some stations' medical personnel. An simulation method is designed to compare the …
Single-Frame Image Motion Parallax Key Point Estimation Combined With Self-Supervised Learning, Zhihao Huo, Weidong Jin, Tang Peng
Single-Frame Image Motion Parallax Key Point Estimation Combined With Self-Supervised Learning, Zhihao Huo, Weidong Jin, Tang Peng
Journal of System Simulation
Abstract: The motion parallax key point FOE (Focus of Expansion) is an important parameter of railway catenary video inspection. The current method of calculating FOE requires multi-frame image matching estimation, which has high time complexity. Aiming at the single-frame image FOE estimation, a single-frame image FOE estimation algorithm fused with self-supervised learning is proposed. A full convolutional network F-VGG(Fully-Visual Geometry Group) is built as the FOE predictor, and the training label of the sample data is automatically generated through the fusion agent task, which realizes the end-to-end single-frame image FOE estimation. The experimental results show that the method has an …
Research On Intelligent Gait Recognition Method Based On Plantar Pressure Perception, Xueqin Liu, Liu Ning, Su Zhong, Jingxiao Wang, Chaojie Yuan
Research On Intelligent Gait Recognition Method Based On Plantar Pressure Perception, Xueqin Liu, Liu Ning, Su Zhong, Jingxiao Wang, Chaojie Yuan
Journal of System Simulation
Abstract: In view of the complexity and low accuracy of gait recognition in the past, an intelligent gait recognition method based on plantar pressure perception is proposed. The pressure data of the gait of plantar periodic motion is collected and the obtained gait data is classified by the vector machines,the intelligent gait recognition of plantar pressure perception is realized, and the accuracy of gait feature analysis is improved. Through experiment verification, the overall classification accuracy of the classifier is more than 90%, which verifies the rationality of the feature extraction. By evaluating the real state and the results of …
A Natural Computing Method Based On Spatial Division Search Strategy, Xiaoqing Sun, Cheng Hao, Luyao Zhang, Weidong Ji, Wang Xu
A Natural Computing Method Based On Spatial Division Search Strategy, Xiaoqing Sun, Cheng Hao, Luyao Zhang, Weidong Ji, Wang Xu
Journal of System Simulation
Abstract: A natural computing method based on spatial division search strategy is proposed. The strategy can map the high-dimensional space to the three-dimensional Cartesian coordinate system by grouping the dimensional space into a group of three dimensions. The individual after spatial segmentation is numbered into subindividual, to increases the particle number while reducing the dimension, thus the individual is distributed over wider search space to effectively increases the diversity of the population. The algorithm iterates to a certain extent and can synthesize the individual into the original individual through the numbered index. By calculating the fitness value, some poor …
Short-Term Wind Power Prediction Method Based On Random Forest, Liu Xing, Wang Yan, Zhicheng Ji
Short-Term Wind Power Prediction Method Based On Random Forest, Liu Xing, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: In order to effectively predict the power and value fluctuation range of the short-term wind, a wind power prediction method based on clustering and kernel principal component analysis combined with random forest algorithm is proposed. The clustering analysis data processing method is used to preprocess the meteorological wind power generation data to improve the data quality, and the kernel principal component analysis method is used to reduce the dimensionality of the eight groups of characteristic data to remove the correlation of the wind power data, the random forest algorithm is used to forecast the wind power, to obtain …
Adaptive Center Node Selection Method For Unmanned Cluster, Hua Xiang, Chenglong Shi, Baohua Li, Jietao Zhang, Jiaxian Zuo
Adaptive Center Node Selection Method For Unmanned Cluster, Hua Xiang, Chenglong Shi, Baohua Li, Jietao Zhang, Jiaxian Zuo
Journal of System Simulation
Abstract: In the unmanned cluster task execution, following the change of relative position of unmanned system, network changes in real time leads to the change of node importance of each unmanned system, and the corresponding change of data transmission and communication flow. For the better network management, the central node for controlling data communication needs to be selected. An adaptive selection method for the center node of unmanned cluster is proposed, and the mapping and feature of unmanned cluster network is expressed as graph theory. Laplacian centrality is introduced to evaluate the importance of nodes themselves. Weakening factors are …
Intelligent Evaluation Of Rescuing Persons From Water In Navigation Simulator, Haichao Wang, Yin Yong
Intelligent Evaluation Of Rescuing Persons From Water In Navigation Simulator, Haichao Wang, Yin Yong
Journal of System Simulation
Abstract: Aiming at the arbitrariness and inconsistent standards in the subjective assessment of the personnel overboard rescue training evaluation in the navigation simulator, the maneuvering process of Williamson turn rescue overboard personnel is analyzed. The evaluation index system is obtained by using the expert investigation method. The sample data of the personnel overboard rescue operation is obtained by the navigation simulator. Combining the expert investigation method, the subjective score of each sample is obtained. By using the BP neural network to train and test the samples, the intelligent evaluation model of personnel overboard rescue is obtained, and the intelligent evaluation …
Access Control Mechanism Of Uav Cluster Based On Blockchain Smart Contract, Ting Duan, Weiping Wang, Yifan Zhu, Wang Tao, Meigen Huang
Access Control Mechanism Of Uav Cluster Based On Blockchain Smart Contract, Ting Duan, Weiping Wang, Yifan Zhu, Wang Tao, Meigen Huang
Journal of System Simulation
Abstract: A Unmanned Aerial Vehicle (UAV) cluster access control mechanism based on Ethereum blockchain smart contract is proposed to solve the problems of the strategic stability and low security of UAV cluster access control mechanism. The role-based access control mechanism model is improved, and the formal definition of the access control model for UAV cluster is given. The access control architecture of UAV cluster based on blockchain technology is proposed, and the corresponding basic framework and execution process is proposed, which can effectively reduce the cost of UAV cluster operation management resources, solve the problem of incomplete state …