A Two-Layer Network Propagation Model Of Awareness Diffusion And Seir Epidemic,
2022
1.School of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;
A Two-Layer Network Propagation Model Of Awareness Diffusion And Seir Epidemic, Yurong Song, Yulin Bao, Ruqi Li
Journal of System Simulation
Abstract: In order to understand the transmission characteristics of epidemics similar to COVID-19 (coronavirus disease 2019) with obvious expose period, a two-layer network transmission model considering time-varying factors is proposed to make corresponding predictions and measures. The UAU (unaware-aware-unaware) information transmission model is used to represent the diffusion process of conscious information about epidemic. In the underlying network, the susceptible-exposed-infected- recovered (SEIR) epidemic-like transmission model with latent state is used to describe the epidemic transmission process affected by conscious information. The MMCA (microscopic Markov chain approach) is used to deduce the transmission threshold of epidemics diseases. By analyzing the key …
Multi-Market Coupling Trading Simulation Of Electricity Green Certificate And Excess Consumption Under New Renewable Portfolio Standard,
2022
1.North China Electric Power University, Beijing 102206, China;2.Beijing Key Laboratory of New Energy and Low-Carbon Development (North China Electric Power University), Beijing 102206, China;
Multi-Market Coupling Trading Simulation Of Electricity Green Certificate And Excess Consumption Under New Renewable Portfolio Standard, Peng Wang, Xiaohua Song, Haowen Yang, Xiaoying Zhai, Jingjing Han, Liwei Ju
Journal of System Simulation
Abstract: In order to clarify the multi-scale market coupling interaction relationship of electricity, green certificate, excess consumption under the renewable portfolio standards (RPS), the system dynamics is introduced, and the interactive trading model is constructed and simulated. Taking the logistics transformation of three market transaction targets as the clue, this paper designs a multi-scale market coupling transaction framework, constructs the complex causality of coupling transaction based on system dynamics method, and analyzes the impact of RPS on the revenue or cost of market participants. Simulation results show that under the new RPS, the electricity price will gradually decline, the …
Simulation And Experiment Of An Intelligent Control Model For The Cleaning Of A Rice-Wheat Combine Harvester,
2022
1.Faculty of Electronic and Information Engineering, West Anhui University, Lu’an 237012, China;
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 …
Unoapi: Balancing Performance, Portability, And Productivity (P3) In Hpc Education,
2022
Loyola University Chicago
Unoapi: Balancing Performance, Portability, And Productivity (P3) In Hpc Education, Konstantin Laufer, George K. Thiruvathukal
Computer Science: Faculty Publications and Other Works
oneAPI is a major initiative by Intel aimed at making it easier to program heterogeneous architectures used in high-performance computing using a unified application programming interface (API). While raising the abstraction level via a unified API represents a promising step for the current generation of students and practitioners to embrace high- performance computing, we argue that a curriculum of well- developed software engineering methods and well-crafted exem- plars will be necessary to ensure interest by this audience and those who teach them. We aim to bridge the gap by developing a curriculum—codenamed UnoAPI—that takes a more holistic approach by looking …
Physics-Informed Neural Networks For Informed Vaccine Distribution In Heterogeneously Mixed Populations,
2022
George Mason University
Physics-Informed Neural Networks For Informed Vaccine Distribution In Heterogeneously Mixed Populations, Alvan Arulandu, Padmanabhan Seshaiyer
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Meta-Complementing The Semantics Of Short Texts In Neural Topic Models,
2022
Singapore Management University
Meta-Complementing The Semantics Of Short Texts In Neural Topic Models, Ce Zhang, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Topic models infer latent topic distributions based on observed word co-occurrences in a text corpus. While typically a corpus contains documents of variable lengths, most previous topic models treat documents of different lengths uniformly, assuming that each document is sufficiently informative. However, shorter documents may have only a few word co-occurrences, resulting in inferior topic quality. Some other previous works assume that all documents are short, and leverage external auxiliary data, e.g., pretrained word embeddings and document connectivity. Orthogonal to existing works, we remedy this problem within the corpus itself by proposing a Meta-Complement Topic Model, which improves topic quality …
Efficient Navigation For Constrained Shortest Path With Adaptive Expansion Control,
2022
Singapore Management University
Efficient Navigation For Constrained Shortest Path With Adaptive Expansion Control, Wenwen Xia, Yuchen Li, Wentian Guo, Shenghong Li
Research Collection School Of Computing and Information Systems
In many route planning applications, finding constrained shortest paths (CSP) is an important and fundamental problem. CSP aims to find the shortest path between two nodes on a graph while satisfying a path constraint. Solving CSPs requires a large search space and is prohibitively slow on large graphs, even with the state-of-the-art parallel solution on GPUs. The reason lies in the lack of effective navigational information and pruning strategies in the search procedure. In this paper, we propose SPEC, a Shortest Path Enhanced approach for solving the exact CSP problem. Our design rationales of SPEC rely on the observation that …
Daot: Domain-Agnostically Aligned Optimal Transport For Domain-Adaptive Crowd Counting,
2022
Singapore Management University
Daot: Domain-Agnostically Aligned Optimal Transport For Domain-Adaptive Crowd Counting, Huilin Zhu, Jingling Yuan, Xian Zhong, Zhengwei Yang, Zheng Wang, Shengfeng He
Research Collection School Of Computing and Information Systems
Domain adaptation is commonly employed in crowd counting to bridge the domain gaps between different datasets. However, existing domain adaptation methods tend to focus on inter-dataset differences while overlooking the intra-differences within the same dataset, leading to additional learning ambiguities. These domain-agnostic factors,e.g., density, surveillance perspective, and scale, can cause significant in-domain variations, and the misalignment of these factors across domains can lead to a drop in performance in cross-domain crowd counting. To address this issue, we propose a Domain-agnostically Aligned Optimal Transport (DAOT) strategy that aligns domain-agnostic factors between domains. The DAOT consists of three steps. First, individual-level differences …
Graph Neural Network With Self-Attention And Multi-Task Learning For Credit Default Risk Prediction,
2022
University of Technology Sydney
Graph Neural Network With Self-Attention And Multi-Task Learning For Credit Default Risk Prediction, Zihao Li, Xianzhi Wang, Lina Yao, Yakun Chen, Guandong Xu, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
We propose a graph neural network with self-attention and multi-task learning (SaM-GNN) to leverage the advantages of deep learning for credit default risk prediction. Our approach incorporates two parallel tasks based on shared intermediate vectors for input vector reconstruction and credit default risk prediction, respectively. To better leverage supervised data, we use self-attention layers for feature representation of categorical and numeric data; we further link raw data into a graph and use a graph convolution module to aggregate similar information and cope with missing values during constructing intermediate vectors. Our method does not heavily rely on feature engineering work and …
A Quality Metric For K-Means Clustering Based On Centroid Locations,
2022
Singapore Management University
A Quality Metric For K-Means Clustering Based On Centroid Locations, Manoj Thulasidas
Research Collection School Of Computing and Information Systems
K-Means clustering algorithm does not offer a clear methodology to determine the appropriate number of clusters; it does not have a built-in mechanism for K selection. In this paper, we present a new metric for clustering quality and describe its use for K selection. The proposed metric, based on the locations of the centroids, as well as the desired properties of the clusters, is developed in two stages. In the initial stage, we take into account the full covariance matrix of the clustering variables, thereby making it mathematically similar to a reduced chi2. We then extend it to account for …
Continual Learning With Neural Networks,
2022
Singapore Management University
Continual Learning With Neural Networks, Pham Hong Quang
Dissertations and Theses Collection (Open Access)
Recent years have witnessed tremendous successes of artificial neural networks in many applications, ranging from visual perception to language understanding. However, such achievements have been mostly demonstrated on a large amount of labeled data that is static throughout learning. In contrast, real-world environments are always evolving, where new patterns emerge and the older ones become inactive before reappearing in the future. In this respect, continual learning aims to achieve a higher level of intelligence by learning online on a data stream of several tasks. As it turns out, neural networks are not equipped to learn continually: they lack the ability …
Development Of A Smartphone Application As An Asset To Pavement Management Engineers, Smartp3m,
2022
University of Texas at Tyler
Development Of A Smartphone Application As An Asset To Pavement Management Engineers, Smartp3m, Damien Stephens
Electrical Engineering Theses
An application specific multi-platform smartphone application can utilize on-board accelerometer, gyroscope, and GPS sensors, along with software derived signals from the same sensors, to sample vibrational and geolocation datasets to capture pavement distresses such as potholes when mounted in a standardized configuration in a vehicle. Several observations were made with regard to the signals obtained from the accelerometer, gyroscope, and GPS sensors, and it was determined that the raw sensor outputs are capable of sampling statistically significant datasets which can be used to distinguish pavement distress from normal driving conditions. Furthermore, an approximate sensor noise margin is established, and a …
Review On Ecological Construction Of Domestic High-Performance Parallel Application Software In Post Moore Era,
2022
1.Science and Technology on Parallel and Distribute Processing Laboratory, National University of Defense Technology, Changsha 410073, China;
Review On Ecological Construction Of Domestic High-Performance Parallel Application Software In Post Moore Era, Chunye Gong, Jie Liu, Weimin Bao, Dongmei Pan, Xinbiao Gan, Shengguo Li, Xuguang Chen, Tiaojie Xiao, Bo Yang, Ruibo Wang
Journal of System Simulation
Abstract: Domestic high performance computing (HPC) system is world-leading and the system chip architectures are in varied forms. The system operation relied on National Supercomputing Center has a good development trend. Several technical key points of domestic high-performance parallel application software are word-leading and the application supporting environment is developing fast. But industrial software and team building are facing huge challenges. In post Moore era, based on the progress of human civilization, it is necessary to promote the ecological development of parallel application software, and from the viewpoint of software products the industrial software must be aim foreign commercial software …
Research On Improved Feature Pyramid Algorithm Integrating Border Supervision Strategy,
2022
School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;
Research On Improved Feature Pyramid Algorithm Integrating Border Supervision Strategy, Hong Sun, Yuelan Ling, Yuxiang Zhang
Journal of System Simulation
Abstract: Aiming at the inaccurate boundary division in semantic segmentation and the existence of multi-scale targets, an improved feature pyramid algorithm fused with boundary supervision strategies is proposed. By fusing the boundary supervision strategy and the improved feature pyramid algorithm, the problems of inaccurate boundary division and the existence of multi-scale targets are sloved respectively, and an attention mechanism is added in the upsampling process to further improve the segmentation effect. The experimental results show that the algorithm can reach 58.69% and 78.59% MIOU (mean intersection over union) indicators on the Camvid and PASCAL VOC2012 data sets respectively, and has …
Real-Time Scheduling Method For Railway Passenger Station Operations Based On Digital Twin,
2022
1.School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China;2.National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 611756, China;3.Comprehensive Transportation Key Laboratory of Sichuan Province, Southwest Jiaotong University, Chengdu 611756, China;
Real-Time Scheduling Method For Railway Passenger Station Operations Based On Digital Twin, Bisheng He, Peng Chen, Hongxiang Zhang, Gongyuan Lu, Chunhui Zhang
Journal of System Simulation
Abstract: To improve the operation scheduling of railway passenger stations and reduce the train delays, digital twin technology is used to establish a railway passenger station operation model. Through real-time data acquisition, based on the operation time prediction of random forest method, operation simulation and decision-making, a real-time scheduling method of railway passenger station operations based on digital twin is proposed, and applied in a real railway passenger station. The experimental results show that the method can effectively forecast and simulate the actual operation. Three kinds of digital twin scheduling rules have been used, which can reduce the delay time …
A Quantum Krill Herd Fusion Algorithm And Its Application,
2022
1.School of Building Services Science and Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China;2.Anhui Key Laboratory of Intelligent Building and Building Energy Conservation, Anhui Jianzhu University, Hefei 230022, China;
A Quantum Krill Herd Fusion Algorithm And Its Application, Zengxi Feng, Jintong Zhao, Shiyan Li, Yalong Yang, Haiyue Chen, Cong Zhang
Journal of System Simulation
Abstract: Aiming at the defects of krill herd algorithm and quantum evolutionary algorithm, a quantum krill herd fusion algorithm (QKH) is proposed. The algorithm uses double-chain real numbers to encode the krill position, which can speed up the convergence speed, and avoids the randomness and complexity of quantum observations. The dynamically adjusted quantum krill herd rotation phase update strategy improves the convergence accuracy, and the efficiency of determining the quantum rotation phase. The introduction of an improved quantum full interference crossover strategy can prevent the fusion algorithm from falling into a local optimum, and can improve the optimization efficienal. The …
Control Of Quadruped Robot Based On Impedance And Virtual Model,
2022
1.School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;
Control Of Quadruped Robot Based On Impedance And Virtual Model, Chikun Gong, Xunwei Wu, Lipeng Yuan
Journal of System Simulation
Abstract: In order to improve the motion stability of quadruped robot, a control method based on impedance and virtual model is proposed. The force-based impedance control method is used to control the leg swing phase to realize the more accurate trajectory tracking and leg compliance control. The virtual model control method is used to control the support phase to realize the attitude control of the robot body and the stable walking of the quadruped robot. Combined with the lateral stride strategy and the yaw angle control strategy based on virtual model, a robot anti-lateral impact control method is proposed, which …
Adaptive Crowd Evacuation Simulation Model Based On Bounded Rationality Constraints,
2022
1.College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China;
Adaptive Crowd Evacuation Simulation Model Based On Bounded Rationality Constraints, Liqiang Zhao, Mengqian Guo, Shuixiong Tang, Jinjin Tang
Journal of System Simulation
Abstract: To effectively improve the accuracy of evacuation simulation of a crowded environment, an adaptive crowd evacuation simulation model based on social force model and bounded rationality constraints is proposed. The desired direction and desired speed of the self-driving force that affects the pedestrian movement in the traditional social force model is improved. The adaptive calculation is used in the optimization of direction and speed of pedestrian in an obstacle avoidance situation. The rational route decision mechanism is proposed to describe the route selection behavior of pedestrians in a congested state more accurately. The results show that the proposed model …
Research On Modeling And Simulation Of Optimization Deployment For Cooperative Localization By Multiple Detection Sensors In Complex Environment,
2022
Northwest Institute of Nuclear Technology, Xi'an 710024, China;
Research On Modeling And Simulation Of Optimization Deployment For Cooperative Localization By Multiple Detection Sensors In Complex Environment, Gongguo Xu, Libing Cai, Peibing Du, Yu Liu
Journal of System Simulation
Abstract: Aiming at the difficulty of accurate cooperative localization by multi-sensor network in complex environment, an optimization deployment method is proposed. The GDOP evaluation index of target positioning accuracy is constructed based on PCRLB. The influence of undulating terrain, clutter jamming and illumination on sensor detection and positioning ability in complex environment is analyzed. An optimization deployment model of multi-sensor cooperative location is built and the intelligent optimization algorithm is used to quickly solve the model. Simulation results show that the proposed method can effectively improve the cooperative localization ability of multi-sensor network and can guide the multi-sensor cooperative …
Tactical Maneuver Strategy Learning From Land Wargame Replay Based On Convolutional Neural Network,
2022
1.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China;2.Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;
Tactical Maneuver Strategy Learning From Land Wargame Replay Based On Convolutional Neural Network, Jiale Xu, Haidong Zhang, Donghai Zhao, Wancheng Ni
Journal of System Simulation
Abstract: Aiming at collecting the high valuable knowledge of action decisions in "man-in-the-loop" wargame's replay data, a method of using convolutional neural network to learn the tactical maneuver strategy model from the replay data of wargame is proposed. In this method, the tactical maneuver strategy is modeled as a classification problem of making a good choice from the target candidate locations under the influence of current situation. The key factors affecting commander's decision-making are summarized, and the basic situation features are defined, which are composed of seven attributes such as "maneuverability range and observation range". The feature dataset with positive …
