Ocean Wave Prediction And Characterization For Intelligent Maritime Transportation,
2022
University of New Orlenas
Ocean Wave Prediction And Characterization For Intelligent Maritime Transportation, Pujan Pokhrel
LSU New Orleans Theses and Dissertations
The national Earth System Prediction (ESPC) initiative aims to develop the predictions
for the next generation predictions of atmosphere, ocean, and sea-ice interactions in the scale of days to decades. This dissertation seeks to demonstrate the methods we can use to improve the ESPC models, especially the ocean prediction model. In the application side of the weather forecasts, this dissertation explores imitation learning with constraints to solve combinatorial optimization problems, focusing on the weather routing of surface vessels. Prediction of ocean waves is essential for various purposes, including vessel routing, ocean energy harvesting, agriculture, etc. Since the machine learning approaches …
Extract Human Mobility Patterns Powered By City Semantic Diagram,
2022
Fudan University
Extract Human Mobility Patterns Powered By City Semantic Diagram, Zhangqing Shan, Weiwei Shan, Baihua Zheng
Research Collection School Of Computing and Information Systems
With widespread deployment of GPS devices, massive spatiotemporal trajectories became more accessible. This booming trend paved the solid data ground for researchers to discover the regularities or patterns of human mobility. However, there are still three challenges in semantic pattern extraction including semantic absence, semantic bias and semantic complexity. In this paper, we invent and apply a novel data structure namely City Semantic Diagram to overcome above three challenges. First, our approach resolves semantic absence by exactly identifying semantic behaviours from raw trajectories. Second, the delicate design of semantic purification helps us to detect semantic complexity from human mobility. Third, …
Aligning Dual Disentangled User Representations From Ratings And Textual Content,
2022
Singapore Management University
Aligning Dual Disentangled User Representations From Ratings And Textual Content, Nhu Thuat Tran, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Classical recommendation methods typically render user representation as a single vector in latent space. Oftentimes, a user's interactions with items are influenced by several hidden factors. To better uncover these hidden factors, we seek disentangled representations. Existing disentanglement methods for recommendations are mainly concerned with user-item interactions alone. To further improve not only the effectiveness of recommendations but also the interpretability of the representations, we propose to learn a second set of disentangled user representations from textual content and to align the two sets of representations with one another. The purpose of this coupling is two-fold. For one benefit, we …
P-Meta: Towards On-Device Deep Model Adaptation,
2022
Singapore Management University
P-Meta: Towards On-Device Deep Model Adaptation, Zhongnan Qu, Zimu Zhou, Yongxin Tong, Lothar Thiele
Research Collection School Of Computing and Information Systems
Data collected by IoT devices are often private and have a large diversity across users. Therefore, learning requires pre-training a model with available representative data samples, deploying the pre-trained model on IoT devices, and adapting the deployed model on the device with local data. Such an on-device adaption for deep learning empowered applications demands data and memory efficiency. However, existing gradient-based meta learning schemes fail to support memory-efficient adaptation. To this end, we propose p-Meta, a new meta learning method that enforces structure-wise partial parameter updates while ensuring fast generalization to unseen tasks. Evaluations on few-shot image classification and reinforcement …
Interpreting Trajectories From Multiple Views: A Hierarchical Self-Attention Network For Estimating The Time Of Arrival,
2022
South China University of Technology
Interpreting Trajectories From Multiple Views: A Hierarchical Self-Attention Network For Estimating The Time Of Arrival, Zebin Chen, Xiaolin Xiao, Yue-Jiao Gong, Jun Fang, Nan Ma, Hua Chai, Zhiguang Cao
Research Collection School Of Computing and Information Systems
Estimating the time of arrival is a crucial task in intelligent transportation systems. Although considerable efforts have been made to solve this problem, most of them decompose a trajectory into several segments and then compute the travel time by integrating the attributes from all segments. The segment view, though being able to depict the local traffic conditions straightforwardly, is insufficient to embody the intrinsic structure of trajectories on the road network. To overcome the limitation, this study proposes multi-view trajectory representation that comprehensively interprets a trajectory from the segment-, link-, and intersection-views. To fulfill the purpose, we design a hierarchical …
Systems And Methods For Contrastive Learning With Self-Labeling Refinement,
2022
Singapore Management University
Systems And Methods For Contrastive Learning With Self-Labeling Refinement, Pan Zhou, Caiming Xiong, Steven Hoi
Research Collection School Of Computing and Information Systems
Embodiments described herein provide a contrastive learning mechanism with self - labeling refinement , which iteratively employs the network and data themselves to generate more accurate and informative soft labels for contrastive learning . Specifically , the contrastive learning framework includes a self - labeling refinery module to explicitly generate accurate labels , and a momentum mix - up module to increase similarity between a query and its positive , which in turn implicitly improves label accuracy.
Academic Hats And Ice Cream: Two Optimization Problems,
2022
Moscow Power Engineering Institute (National Research University)
Academic Hats And Ice Cream: Two Optimization Problems, Valery F. Ochkov, Yulia V. Chudova
Journal of Humanistic Mathematics
This article describes the use of computer software to optimize the design of an academic hat and an ice cream cone!
Student
Computational Models To Detect Radiation In Urban Environments: An Application Of Signal Processing Techniques And Neural Networks To Radiation Data Analysis, Jose Nicolas Gachancipa
Beyond: Undergraduate Research Journal
Radioactive sources, such as uranium-235, are nuclides that emit ionizing radiation, and which can be used to build nuclear weapons. In public areas, the presence of a radioactive nuclide can present a risk to the population, and therefore, it is imperative that threats are identified by radiological search and response teams in a timely and effective manner. In urban environments, such as densely populated cities, radioactive sources may be more difficult to detect, since background radiation produced by surrounding objects and structures (e.g., buildings, cars) can hinder the effective detection of unnatural radioactive material. This article presents a computational model …
A Modified Point Matching Method For Non-Rigid Image Registration,
2022
1.Dept. of Computer Science and Technology, Changzhi College, Changzhi 046011, China;
A Modified Point Matching Method For Non-Rigid Image Registration, Jintai Shangguan, Yawen Dang, Wei Lian
Journal of System Simulation
Abstract: Aiming at the problem that the registration results tend to converge to local minima due to the complexity of the relative position changes between two point sets in the non-rigid body point matching process, a joint estimation method for non-rigid body point matching based on precenter alignment is proposed, a modified matching method for non-rigid image registration based on centre preregistration is proposed. To better achieve the point matching accuracy between two point sets, a centre preregistration step is applied before the iterative closest point matching algorithm, which converges to a solution more close to a global optimum and …
Transfer Method Of Operational Simulation Experiment Scope Using Compromised Case-Based Reasoning,
2022
1.Graduate school, National Defense University, Beijing 100091;2.Joint Operations College, National Defense University, Beijing 100091;
Transfer Method Of Operational Simulation Experiment Scope Using Compromised Case-Based Reasoning, Jun Ma, Jingyu Yang, Xi Wu
Journal of System Simulation
Abstract: The scope of operational simulation experiment is usually determined by experts, which costs relatively high. In order to transfer the knowledge of experimental scope selection from historical data of operational simulation experiment to new operational experiment cases, the method of compromised case-based reasoning is proposed. According to the data characteristics of the case, the representation method of the operational simulation experiment case is proposed; according to the structure and attribute characteristics of the case, the hybrid similarity calculation method of subjective and objective comprehensive weighting is proposed; aiming at the problems of retrieval failure and less information content …
Optimal Dispatch Of Integrated Energy System Considering Ladder-Type Carbon Trading,
2022
1.North China Electric Power University, Beijing 102206, China;
Optimal Dispatch Of Integrated Energy System Considering Ladder-Type Carbon Trading, Liying Wang, Jialin Lin, Houqi Dong, Ming Zeng, Yuqing Wang
Journal of System Simulation
Abstract: With the development of the electricity market and carbon market,the introduction of demand response and carbon trading mechanisms into the operation and dispatch of integrated energy systems will help guide users and system operators to optimize electricity consumption and dispatch plans.The comprehensive incentive measures such as time-of-use electricity prices and demand response incentive subsidies are used to guide users to participate in demand response.A two-layer stochastic optimal scheduling model for a comprehensive energy system considering the ladder-type carbon trading mechanism and demand response is constructed based on IGDT (information gap decision theory) theory.The two-layer model is converted …
Bi-Level Optimization Of Distribution Network For Hybrid Energy Storage System Of Storage Battery And Hydrogen Storage,
2022
1.State Grid Anhui Electric Power Company, Bengbu Power Supply Company, Bengbu 233000, China;
Bi-Level Optimization Of Distribution Network For Hybrid Energy Storage System Of Storage Battery And Hydrogen Storage, Feibo Feng, Xingde Yan, Baoqiang Zheng, Xiaofeng Yin, Mengzhen Zhou, Xin Jiang
Journal of System Simulation
Abstract: Under the background of carbon neutralization and emission peaking goals and the utilization of clean hydrogen energy, aiming at the demand of distribution network configuring electrochemical energy storage and hydrogen energy storage system to form a hybrid energy storage system to improve power quality, a bi-level optimization model of the hybrid energy storage system is established. The upper level location and capacity model comprehensively considers the investment cost, network loss cost and voltage offset, while the lower level optimization operation model considers the operation cost of hybrid energy storage system, and the voltage stability index is introduced for evaluation. …
Modeling And Simulation Of Optimal Strategy For Electric Vehicles Participating In Power Grid Frequency Regulation,
2022
1.State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources, North China Electric Power University, Beijing 102206, China;
Modeling And Simulation Of Optimal Strategy For Electric Vehicles Participating In Power Grid Frequency Regulation, Li Yao, Junjie Hu, Wenshuai Ma, Zhile Yang
Journal of System Simulation
Abstract: Electric vehicles (EVs) have similar characteristics of distributed energy storage, and making full use of the flexibility of EVs can provide ancillary services to the grid and gain benefits. Considering the influence of uncertain factors, a bidding model for electric vehicle aggregator (EVA) to participate in the day-ahead energy market and frequency regulation ancillary service market is constructed with the maximum revenue expectation of EVA as the target. A real-time energy distribution incentive strategy based on contract theory is proposed to realize the distribution of EVA's frequency regulation demand under the condition of maximizing social welfare. Through case studies, …
Simulation Model Of Forest Fire Spread Based On Swarm Intelligence,
2022
1.School of Computer and Information Engineering, Central South University of Forestry & Technology, Changsha 410004, China;
Simulation Model Of Forest Fire Spread Based On Swarm Intelligence, Aibin Chen, Fubo Ding, Guoxiong Zhou, Bo Zhou
Journal of System Simulation
Abstract: Aiming at the shortcomings of high computational complexity and low simulation accuracy of traditional forest fire spread model, a forest fire spread simulation model based on swarm intelligence is proposed.By establishing fuel factor matrix and landform factor matrix, and combining with the real-time meteorological information, the computational complexity is reduced; the spread behavior of the forest fire is abstracted as the cluster behavior of each module fire point, and the correlation between modules is considered to improve the accuracy of forest fire spread simulation model.The model is compared with Wang Zhengfei model and two-dimensional cellular automata model. …
Two Stage Optimization Algorithm To Solve The Green Packing Vehicle Routing Problem,
2022
1.Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China;
Two Stage Optimization Algorithm To Solve The Green Packing Vehicle Routing Problem, Rong Hu, Wen Jiang, Bin Qian, Naikang Yu
Journal of System Simulation
Abstract: The green open vehicle routing problem with two-dimensional loading constraints (2L-GOVRP) is integration of the green open vehicle routing problem and two-dimensional bin packing problem. The model of 2L-GOVRP is established and a two-stage optimization algorithm (TSOA) is proposed to minimize fuel consumption. In the first stage of TSOA, adaptive whale optimization algorithm (AWOA) is designed to solve the vehicle routing problem, which determine the initial delivery route of the vehicle (the initial solution of 2L-GOVRP). The algorithm has four kinds of variable neighborhoods local operation to perform a local search. In the second stage of TSOA, the skyline …
A Method Of Loose Coupling Entity Modeling Based On Variable Rules,
2022
Electronic Encounter Institution, National University of Defense Technology, Hefei 230037, China;
A Method Of Loose Coupling Entity Modeling Based On Variable Rules, Zheng Yang, Zhimin Xiang, Shiwen Ma
Journal of System Simulation
Abstract: Operational Entity Modeling is a hot research topic in the field of combat simulation. A loose coupling entity modeling method based on variable rules is proposed. The architecture of operational entity model based on variable rules and the internal and external interaction mechanism of the model are presented in terms of entity, mission, action, interaction, event and rule. On this basis, the running framework of operational entity model is designed, and the entity model uniform scheduling mechanism is standardized, which solves the problems of over-tight coupling of operational rules in the operational entity model and low reliability of the …
Research On Prediction Of Model Based On Multi-Scale Lstm,
2022
School of Information Science and Engineering, East Chines of Science and Technology, Shanghai 200237, China;
Research On Prediction Of Model Based On Multi-Scale Lstm, Junjie Qiu, Hong Zheng, Yunhui Cheng
Journal of System Simulation
Abstract: Aircraft engine remaining useful life (RUL) prediction is the core issue in equipmentfailure prognostics and health management (PHM). Aiming at the characteristics of high dimensionality, high lag and complexity of engine data, a multi-scale attention-based bidirectional long short-term memory neural network model based on self-training weights is proposed. Multi-scale features are extracted through bidirectional long short-term memory neural network (BiLSTM) of different scales. A fusion algorithm based on self-training weights is proposed, and an attention mechanism is introduced to screen features at different scales to improve prediction accuracy. Various models are compared on the NASA's C-MAPSS data set. The …
Space Science Satellite Data Processing Framework Research And System Implementation,
2022
1.Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China;2.National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China;3.University of Chinese Academy of Sciences, Beijing 100049, China;
Space Science Satellite Data Processing Framework Research And System Implementation, Wenzhen Ma, Ziming Zou, Jianhui Li, Qinsi Yu, Jizhou Tong, Jingjing Li
Journal of System Simulation
Abstract: Based on the needs of China's space science strategy and series of on-orbit and forthcoming satellite missions in China's Strategic Priority Program on space science, data processing framework and key technologies of the satellite ground segment are studied. A general technical framework SDPF (space science satellite data processing framework) is proposed with two-layer scheduling engine, including mission-level and resource-level. The design and implementation of an automatic, efficient, real-time and standard space science satellite data processing system has been established. In this way, complicated processing procedures on large-scale data from multi-satellite missions and multi-payload can be completed quickly in parallel. …
Ultra-Real-Time Visual Simulation System For Multi-View Rendering Tasks,
2022
Academy of Military Science, Beijing 100091, China;
Ultra-Real-Time Visual Simulation System For Multi-View Rendering Tasks, Xunyun Liu, Xinhai Xu, Chengzhang Zhu, Hao Li, Lei Zeng
Journal of System Simulation
Abstract: For multi-view rendering tasks, a theoretical analysis of ultra-real-time visual simulation is given in terms of implementation principle and feasibility. Based on the theoretical results, an ultra-real-time visual simulation architecture is designed, which decouples the simulation and rendering computation. A parallel-rendering-based ultra-real-time visual simulation method is proposed to solve the problems of rendering task assignment, simulation world synchronization, and rendering-execution time selection. An ultra-real-time visual simulation system is implemented based on Unreal Engine 4 (UE4), the performance of which is demonstrated on a designated application case per rendering efficiency and ultra-real-time simulation.
Verification Of Transaction Ordering Dependence Vulnerability Of Smart Contract Based On Cpn,
2022
School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China;
Verification Of Transaction Ordering Dependence Vulnerability Of Smart Contract Based On Cpn, Hong Zheng, Zerun Liu, Jianhua Huang, Shihui Qian
Journal of System Simulation
Abstract: The formal verification of smart contracts researches mainly focus on programming language-level vulnerabilities, and the transaction ordering dependence is more difficult to be detected as a blockchain-level vulnerability.The latent transaction ordering dependence vulnerability in smart contracts is formally verified based on colored Petri nets.The latent vulnerability in the Decode reward contractis analyzed, anda colored Petri net model of the contract itself and its execution environment is established from top to bottom.The attacker model is introduced to consider the situation that the contract is attacked. By running the model to verify the existence of transaction ordering dependence vulnerability in …
