Joint Distribution Location-Routing Problem And Large Neighborhood Search Algorithm,
2021
1. School of Information, Beijing Wuzi University, Beijing 101149, China; ;
Joint Distribution Location-Routing Problem And Large Neighborhood Search Algorithm, Zhenping Li, Yuwei Zhao, Yuwei Zhang, Lining Xing, Ren Teng
Journal of System Simulation
Abstract: Based on the characteristics of two-echelon, multi-center, and heterogeneous fleets in urban logistics joint distribution system, the two-echelon joint distribution location routing problem is studied. The problem is formulated into a mixed integer programming model to minimize the total costs. An adaptive large neighborhood search algorithm (ALNS) for solving the model with multiple deletion and insertion operators is proposed to obtain neighborhood solution. The selection probability of each operator is adjusted according to the neighborhood solution to accelerate the convergence speed. Several test examples are generated based on the benchmark of location-routing problem. Both ALNS algorithm and Gurobi software …
Research On Simulation And Optimization Of Maintenance Support Mode And Human Resources Auocation For Complex Equipment,
2021
1. Department of Equipment Support and Remanufacture of Army Academy of Armored Forces, Beijing 100072, China; ;
Research On Simulation And Optimization Of Maintenance Support Mode And Human Resources Auocation For Complex Equipment, Junhai Cao, Yiming Guo, Chuang Zhang, Qingyi Guo
Journal of System Simulation
Abstract: Aiming at the single maintenance support mode of the army’s complex equipment and the strong randomness of human resource allocation, the military-level equipment maintenance process is taken as the research object, the complex equipment maintenance plan, maintenance support mode, human resource configuration, and maintenance process flow are analyzed. The simulation model of a complex equipment maintenance workshop is constructed, the influence of maintenance plans, maintenance support modes, and human resource allocation on indicators of “maintenance support time” and “human resource satisfaction rate” is explored, the internal laws is analyzed and the manpower optimal allocation for the maintenance of …
Optimized-Xgboost Early Warning Of Wind Turbine Generator Front Bearing Fault,
2021
1. School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China; ;
Optimized-Xgboost Early Warning Of Wind Turbine Generator Front Bearing Fault, Le Wei, Xiaodong Hu, Yin Shi
Journal of System Simulation
Abstract: In order to identify the abnormal running state of the generator in time, a wind turbine generator front bearing fault early warning method based on Bayesian optimized extreme gradient boosting algorithm is proposed. The historical data collected by SCADA (Supervisory Control And Data Acquisition) are preprocessed by effective data preprocessing methods. The temperature prediction model of the front bearing of wind turbine generator is constructed based on the Bayesian-optimized XGBoost (eXtreme Gradient Boosting) algorithm and the fault early warning threshold of the front bearing of the wind turbine generator is determined based on the 3σ criterion. The experimental …
Reusability Analysis And Application For Complex System Simulation Model,
2021
1. College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; ;
Reusability Analysis And Application For Complex System Simulation Model, Zhu Feng, Yiping Yao, Wenjie Tang, Li Jin
Journal of System Simulation
Abstract: Model reuse is an important way to improve the development efficiency of complex system simulation application. At present, there are few researches on the reusability of simulation model and its impact on the development efficiency of complex system simulation application integration by using qualitative/quantitative methods. A simulation model reusability analysis method is proposed. By introducing the simulation application integration development speedup ratio, the simulation model reusability analysis mathematical model is constructed, and the requirements of model interface, model testing and information description for improving model reusability are analyzed qualitatively. Through two typical case studies, the influence of reusable simulation …
Scheduling Optimization Research Based On Tabu Algorithm For Uncertainty Carrier Aircraft Support,
2021
Qingdao Campus of Naval Aviation University, Qingdao 266041, China;
Scheduling Optimization Research Based On Tabu Algorithm For Uncertainty Carrier Aircraft Support, Yangkai Meng, Wang Zheng, Jiali Fan
Journal of System Simulation
Abstract: In order to improve the scheduling stability of ship-borne and reduce the uncertainty risk during the operation, the deck scheduling mathematical model is designed. For the refueling uncertainty, the equipment failure distribution function is established, and the research method of guarantee operation risk factor value and fault opportunity influence factor is proposed. The uncertainty target function calculation model is derived and solved using the improved taboo algorithm to obtain the scheduling optimization scheme. Simulation experimental results verify the effectiveness and feasibility of the proposed research method.
Research On Assocoation Information Mining Of Space Reconnaissance Equipment System Index,
2021
Space Engineering University, Beijing 101416, China;
Research On Assocoation Information Mining Of Space Reconnaissance Equipment System Index, Han Chi, Xiong Wei
Journal of System Simulation
Abstract: The system effectiveness and system contribution rate of the Space Reconnaissance Equipment System (SRES) has a large number of mutally associated indicators. How to identify relationships the association, select the key indicators and clarify the assocition between core indicators and system contribution rate are the key of the evaluation of system effectiveness and contribution rate. Through the joint simulation of MATLAB and STK, the underlying index data of SRES is obtained. Based on the Frequent Pattern-Tree (FP-Tree) algorithm, the assocition information is discovered, the redundancy is removed and the type of indicator assocition is determined, and an optimization model …
Research On The Network Of 3d Smoke Flow Super-Resolution Data Generation,
2021
Beijing University of Technology, Faculty of Information Technology, Beijing 100029, China;
Research On The Network Of 3d Smoke Flow Super-Resolution Data Generation, Jinlian Du, Shufei Li, Xueyun Jin
Journal of System Simulation
Abstract: Aiming at the problem of low data generation efficiency due to the high complexity of solving the N-S equation of smoke flow field, a deep learning model which can generate high-resolution smoke flow data based on low-resolution smoke flow data solved by N-S equation is explored and designed. Based on the Generative Adversarial Network, the smoke data reconstruction network based on the sub voxel convolution layer is constructed. Considering the fluidity of smoke, time loss based on advection step is introduced into the loss function to realize high-precision smoke simulation. By extending the image super-resolution quality evaluation index, the …
Modeling And Simulation Of Channel Passage Capacity Based On Cellular Automata,
2021
1. School of Navigation, Wuhan University of Technology, Wuhan 430063, China; ;2. Hubei Key Laboratory of Inland Shipping Technology, Wuhan 430063, China;
Modeling And Simulation Of Channel Passage Capacity Based On Cellular Automata, Zongyang Liu, Chunhui Zhou, Junnan Zhao, Jinli Xiao, Langxiong Gan
Journal of System Simulation
Abstract: In order to study the passage capacity of the seaport and explore the service level of the channel, the cellular automata theory is used to discretize and model the main channel of the seaport, and the movement rules of the cell in the channel are processed in sections. In addition, this study focuses on the existence of a traffic "warning zone" in the curved channel section. The ship motion rules of the straight channel section and the curved channel section are respectively constrained, through simulation experiments, the vessel traffic flow of the channel and the maximum ship passing …
A Large-Scale Benchmark For Food Image Segmentation,
2021
Singapore Management University
A Large-Scale Benchmark For Food Image Segmentation, Xiongwei Wu, Xin Fu, Ying Liu, Ee-Peng Lim, Steven C. H. Hoi, Qianru Sun
Research Collection School Of Computing and Information Systems
Food image segmentation is a critical and indispensible task for developing health-related applications such as estimating food calories and nutrients. Existing food image segmentation models are underperforming due to two reasons: (1) there is a lack of high quality food image datasets with fine-grained ingredient labels and pixel-wise location masks—the existing datasets either carry coarse ingredient labels or are small in size; and (2) the complex appearance of food makes it difficult to localize and recognize ingredients in food images, e.g., the ingredients may overlap one another in the same image, and the identical ingredient may appear distinctly in different …
Interactive Probing Of Multivariate Time Series Prediction Models: A Case Of Freight Rate Analysis,
2021
Singapore Management University
Interactive Probing Of Multivariate Time Series Prediction Models: A Case Of Freight Rate Analysis, Haonan Xu, Haotian Li, Yong Wang
Research Collection School Of Computing and Information Systems
We present an interactive probing tool to create, modify and analyze what-if scenarios for multivariate time series models. The solution is applied to freight trading, where analysts can carry out sensitivity analysis on freight rates by changing demand and supply-related econometric variables and observing their resultant effects on freight indexes. We utilize various visualization techniques to enable intuitive scenario creation, alteration, and comprehension of time series inputs and model predictions. Our tool proved to be useful to the industry practitioners, demonstrated by a case study where freight traders are given hypothetical market scenarios and successfully generated quantitative freight index projection …
Noahqa: Numerical Reasoning With Interpretable Graph Question Answering Dataset,
2021
Singapore Management University
Noahqa: Numerical Reasoning With Interpretable Graph Question Answering Dataset, Qiyuan Zhang, Lei Wang, Sicheng Yu, Shuohang Wang, Yang Wang, Jing Jiang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
While diverse question answering (QA) datasets have been proposed and contributed significantly to the development of deep learning models for QA tasks, the existing datasets fall short in two aspects. First, we lack QA datasets covering complex questions that involve answers as well as the reasoning processes to get the answers. As a result, the state-of-the-art QA research on numerical reasoning still focuses on simple calculations and does not provide the mathematical expressions or evidences justifying the answers. Second, the QA community has contributed much effort to improving the interpretability of QA models. However, these models fail to explicitly show …
Burst-Induced Multi-Armed Bandit For Learning Recommendation,
2021
Singapore Management University
Burst-Induced Multi-Armed Bandit For Learning Recommendation, Rodrigo Alves, Antoine Ledent, Marius Kloft
Research Collection School Of Computing and Information Systems
In this paper, we introduce a non-stationary and context-free Multi-Armed Bandit (MAB) problem and a novel algorithm (which we refer to as BMAB) to solve it. The problem is context-free in the sense that no side information about users or items is needed. We work in a continuous-time setting where each timestamp corresponds to a visit by a user and a corresponding decision regarding recommendation. The main novelty is that we model the reward distribution as a consequence of variations in the intensity of the activity, and thereby we assist the exploration/exploitation dilemma by exploring the temporal dynamics of the …
Occluded Person Re-Identification With Single-Scale Global Representations,
2021
Singapore Management University
Occluded Person Re-Identification With Single-Scale Global Representations, Cheng Yan, Guansong Pang, Jile Jiao, Xiao Bai, Xuetao Feng, Chunhua Shen
Research Collection School Of Computing and Information Systems
Occluded person re-identification (ReID) aims at re-identifying occluded pedestrians from occluded or holistic images taken across multiple cameras. Current state-of-the-art (SOTA) occluded ReID models rely on some auxiliary modules, including pose estimation, feature pyramid and graph matching modules, to learn multi-scale and/or part-level features to tackle the occlusion challenges. This unfortunately leads to complex ReID models that (i) fail to generalize to challenging occlusions of diverse appearance, shape or size, and (ii) become ineffective in handling non-occluded pedestrians. However, real-world ReID applications typically have highly diverse occlusions and involve a hybrid of occluded and non-occluded pedestrians. To address these two …
A Comparative Study On Feature Extraction And Classification/Clustering Of Fake News And Conspiracy Theories From Twitter Data,
2021
Columbus State University
A Comparative Study On Feature Extraction And Classification/Clustering Of Fake News And Conspiracy Theories From Twitter Data, Deb Shana
Theses and Dissertations
Fake news and conspiracy theories have become largely abundant in the expanding world of social media. They predominantly affect the beliefs and thoughts of the public, resulting in chaos. They have always existed throughout the last few decades. They have been linked to prejudice, revolutions and genocide across history. They have also been known to have propelled people to reject mainstream medicines to an extent where some diseases are recurring in some parts of the world. They impose a serious impact since they are capable of spreading very fast Thus, it is very important to find suitable ways to detect …
Deep Learning For Image Super-Resolution: A Survey,
2021
South China University of Technology
Deep Learning For Image Super-Resolution: A Survey, Zhihao Wang, Jian Chen, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Image Super-Resolution (SR) is an important class of image processing techniqueso enhance the resolution of images and videos in computer vision. Recent years have witnessed remarkable progress of image super-resolution using deep learning techniques. This article aims to provide a comprehensive survey on recent advances of image super-resolution using deep learning approaches. In general, we can roughly group the existing studies of SR techniques into three major categories: supervised SR, unsupervised SR, and domain-specific SR. In addition, we also cover some other important issues, such as publicly available benchmark datasets and performance evaluation metrics. Finally, we conclude this survey by …
Online Learning: A Comprehensive Survey,
2021
Singapore Management University
Online Learning: A Comprehensive Survey, Steven C. H. Hoi, Doyen Sahoo, Jing Lu, Peilin Zhao
Research Collection School Of Computing and Information Systems
Online learning represents a family of machine learning methods, where a learner attempts to tackle some predictive (or any type of decision-making) task by learning from a sequence of data instances one by one at each time. The goal of online learning is to maximize the accuracy/correctness for the sequence of predictions/decisions made by the online learner given the knowledge of correct answers to previous prediction/learning tasks and possibly additional information. This is in contrast to traditional batch or offline machine learning methods that are often designed to learn a model from the entire training data set at once. Online …
Themes, Communities And Influencers Of Online Probiotics Chatter: A Retrospective Analysis From 2009-2017,
2021
Northumbria University
Themes, Communities And Influencers Of Online Probiotics Chatter: A Retrospective Analysis From 2009-2017, Santosh Vijaykumar, Aravind Sesagiri Raamkumar, Kristofor Mccarty, Cuthbert Mutumbwa, Jawwad Mustafa, Cyndy Au
Research Collection Lee Kong Chian School Of Business
We build on recent examinations questioning the quality of online information about probiotic products by studying the themes of content, detecting virtual communities and identifying key influencers in social media using data science techniques. We conducted topic modelling (n = 36,715 tweets) and longitudinal social network analysis (n = 17,834 tweets) of probiotic chatter on Twitter from 2009–17. We used Latent Dirichlet Allocation (LDA) to build the topic models and network analysis tool Gephi for building yearly graphs. We identified the top 10 topics of probiotics-related communication on Twitter and a constant rise in communication activity. However the number of …
Bv-Person: A Large-Scale Dataset For Bird-View Person Re-Identification,
2021
Singapore Management University
Bv-Person: A Large-Scale Dataset For Bird-View Person Re-Identification, Cheng Yan, Guansong Pang, Lei Wang, Jile Jiao, Xuetao Feng, Chunhua Shen, Jingjing Li
Research Collection School Of Computing and Information Systems
Person Re-IDentification (ReID) aims at re-identifying persons from non-overlapping cameras. Existing person ReID studies focus on horizontal-view ReID tasks, in which the person images are captured by the cameras from a (nearly) horizontal view. In this work we introduce a new ReID task, bird-view person ReID, which aims at searching for a person in a gallery of horizontal-view images with the query images taken from a bird's-eye view, i.e., an elevated view of an object from above. The task is important because there are a large number of video surveillance cameras capturing persons from such an elevated view at public …
Modeling Research Of Cognition Behavior For Intelligent Wargaming,
2021
College of Joint Operations, National Defence University, Beijing 100091, China;
Modeling Research Of Cognition Behavior For Intelligent Wargaming, Xiaoyuan He, Shengming Guo, Wu Lin, Li Dong, Xu Xiao, Li Li
Journal of System Simulation
Abstract: Aiming at the problem of cognitive behavior modeling in the construction and application of intelligent wargaming system, one modeling framework based on Actor-Operations-Scene (AOS) was proposed for C2 agent in wargaming. Then the realization of cognitive behavior modeling method for C2 agent was explored, including the modeling for the scenario oriented knowledge graph, intelligent situation awareness, operational planning, integrated operational control. It provides a feasible scheme for the construction and application of intelligent wargaming system.
Intelligent Wargaming System: Change Needed By Next Generation Need To Be Changed,
2021
College of Joint Operation, National Defense University, Beijing100091, China;
Intelligent Wargaming System: Change Needed By Next Generation Need To Be Changed, Xiaofeng Hu, Dawei Qi
Journal of System Simulation
Abstract: The future direction of wargaming system is intelligent, and the most significant feature of intelligence is the modeling of cognition. The main problems of wargaming system are summarized, the main difficulties of modeling brought by cognition and the overall framework of intelligent wargaming system design are discussed, the technical ways of transformation and upgrading based on the existing wargaming system are given from four aspects of model construction, system design, wargaming ecology and test inspection. It provides direction and reference to the development and construction of the next generation intelligent wargaming system.
