A Photovoltaic Power Forecasting Method Based On Da-Rkelm Algorithm,
2020
1. School of Mechanical Engineering, Shenyang University, Shenyang 110041, China; ;
A Photovoltaic Power Forecasting Method Based On Da-Rkelm Algorithm, Mingqi Wei, Tianrui Zhang, Xiuxiu Gao, Shumei Wang
Journal of System Simulation
Abstract: Aiming at the power grid safety problems caused by the fluctuation and randomness of photo-voltaic power generation, a method for predicting photo-voltaic power generation of a regular nuclear limit learning machine based on the optimization of a dragonfly algorithm was proposed. Through correlation analysis, the key factors affecting the photo-voltaic power generation are determined, and the photo-voltaic power prediction model is constructed. Dragonfly algorithm is used to obtain the optimal weight and threshold value of the network, and regularization function and kernel function are introduced based on the standard limit learning machine to avoid the over …
Research On Simulation Optimization Of Intelligent Storage Robot Configuration Under Multiple Constraints,
2020
1. Dalian Neusoft University of Information, Dalian 116023, China; ;
Research On Simulation Optimization Of Intelligent Storage Robot Configuration Under Multiple Constraints, Guo Di, Danlan Xie, Ji Yuan
Journal of System Simulation
Abstract: Aiming at the intelligent warehouse storage robot configuration, a discrete event simulation model based on queuing theory is constructed. Considering the influence of faults and the reliability and service intensity of the system, aiming at minimizing the total cost of distance cost, time cost, idle cost and purchase cost, a based on FlexSim simulation model is proposed. Discrete event simulation optimization method of the platform. By analyzing the system average team length, order average stay time and other indicators, the intuitionistic bottleneck of the system is combined with the actual operation data, and the configuration strategy of minimum system …
Optimization And Simulation Of Offshore Edge Computing Network For E-Pilotage,
2020
1. College of Information Science and Technology, Dalian Maritime University, Dalian 116026, China; ;
Optimization And Simulation Of Offshore Edge Computing Network For E-Pilotage, Bin Lin, Chenchen Song, Yajing Zhang, Jianli Duan
Journal of System Simulation
Abstract: In order to improve the safety of the ship's piloting process, an INA-based offshore edge computing network (IOECN) architecture is proposed to provide navigation assistance information. The Layout Optimization Problem (LOP) of network element nodes in the network is mainly studied. The mathematical model is used to convert the LOP into an Integer Linear Programming (ILP) problem. On condition of the required network coverage and connectivity, aiming to minimize the network cost, being solved by Gurobi and simulated and demonstrated by Matlab, the network optimization on different scales is obtained and the correctness and scalability of …
Period Estimation And Noise In A Neutrally Stable Stochastic Oscillator,
2020
University of North Carolina Asheville
Period Estimation And Noise In A Neutrally Stable Stochastic Oscillator, Kevin R. Sanft, Ben F. M. Intoy
Spora: A Journal of Biomathematics
The periods of the orbits for the well-mixed cyclic three-species Lotka-Volterra model far away from the fixed point are studied. For finite system sizes, a discrete stochastic approach is employed and periods are found via wavelet analysis. As the system size is increased, a hierarchy of approximations ranging from Poisson noise to Gaussian noise to deterministic models are utilized. Based on the deterministic equations, a mathematical relationship between a conserved quantity of the model and the period of the population oscillations is found. Exploiting this property we then study the deterministic conserved quantity and period noise in finite size systems.
Some Generalizations Of Classical Integer Sequences Arising In Combinatorial Representation Theory,
2020
Western Kentucky University
Some Generalizations Of Classical Integer Sequences Arising In Combinatorial Representation Theory, Sasha Verona Malone
Masters Theses & Specialist Projects
There exists a natural correspondence between the bases for a given finite-dimensional representation of a complex semisimple Lie algebra and a certain collection of finite edge-colored ranked posets, laid out by Donnelly, et al. in, for instance, [Don03]. In this correspondence, the Serre relations on the Chevalley generators of the given Lie algebra are realized as conditions on coefficients assigned to poset edges. These conditions are the so-called diamond, crossing, and structure relations (hereinafter DCS relations.) New representation constructions of Lie algebras may thus be obtained by utilizing edge-colored ranked posets. Of particular combinatorial interest are those representations whose corresponding …
We Mind Your Well-Being: Preventing Depression In Uncertain Social Networks By Sequential Interventions,
2020
Singapore Management University
We Mind Your Well-Being: Preventing Depression In Uncertain Social Networks By Sequential Interventions, Aye Phye Phye Aung, Xinrun Wang, Bo An, Xiaoli Li
Research Collection School Of Computing and Information Systems
Mental health has become a major concern according to WHO who estimates that more than 350 million people worldwide are affected by depression. Studies have shown that interventions and social support can reduce stress and depression. However, counselling centers do not have enough resources to provide counselling and social support to all the participants in their interest. This paper helps social support organizations (e.g., university counselling centers) sequentially select the participants for interventions. Unfortunately, previous works do not consider emotion propagation from other neighbours of the influencees and initial uncertainties of mental states and influence. Moreover, they fail to scale …
Co2vec: Embeddings Of Co-Ordered Networks Based On Mutual Reinforcement,
2020
Singapore Management University
Co2vec: Embeddings Of Co-Ordered Networks Based On Mutual Reinforcement, Meng-Fen Chiang, Ee-Peng Lim, Wang-Chien Lee, Philips Kokoh Prasetyo
Research Collection School Of Computing and Information Systems
We study the problem of representation learning for multiple types of entities in a co-ordered network where order relations exist among entities of the same type, and association relations exist across entities of different types. The key challenge in learning co-ordered network embedding is to preserve order relations among entities of the same type while leveraging on the general consistency in order relations between different entity types. In this paper, we propose an embedding model, CO2Vec, that addresses this challenge using mutually reinforced order dependencies. Specifically, CO2Vec explores in-direct order dependencies as supplementary evidence to enhance order representation learning across …
European Floating Strike Lookback Options: Alpha Prediction And Generation Using Unsupervised Learning,
2020
Singapore Management University
European Floating Strike Lookback Options: Alpha Prediction And Generation Using Unsupervised Learning, Tristan Lim, Aldy Gunawan, Chin Sin Ong
Research Collection School Of Computing and Information Systems
This research utilized the intrinsic quality of European floating strike lookback call options, alongside selected return and volatility parameters, in a K-means clustering environment, to recommend an alpha generative trading strategy. The result is an elegant easy-to-use alpha strategy based on the option mechanisms which identifies investment assets with high degree of significance. In an upward trending market, the research had identified European floating strike lookback call option as an evaluative criterion and investable asset, which would both allow investors to predict and profit from alpha opportunities. The findings will be useful for (i) buy-side investors seeking alpha generation and/or …
Deep Reinforcement Learning Approach To Solve Dynamic Vehicle Routing Problem With Stochastic Customers,
2020
Singapore Management University
Deep Reinforcement Learning Approach To Solve Dynamic Vehicle Routing Problem With Stochastic Customers, Waldy Joe, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In real-world urban logistics operations, changes to the routes and tasks occur in response to dynamic events. To ensure customers’ demands are met, planners need to make these changes quickly (sometimes instantaneously). This paper proposes the formulation of a dynamic vehicle routing problem with time windows and both known and stochastic customers as a route-based Markov Decision Process. We propose a solution approach that combines Deep Reinforcement Learning (specifically neural networks-based TemporalDifference learning with experience replay) to approximate the value function and a routing heuristic based on Simulated Annealing, called DRLSA. Our approach enables optimized re-routing decision to be generated …
Efficient Sampling Algorithms For Approximate Temporal Motif Counting,
2020
Hunan University
Efficient Sampling Algorithms For Approximate Temporal Motif Counting, Jingjing Wang, Yanhao Wang, Wenjun Jiang, Yuchen Li, Kian-Lee Tan
Research Collection School Of Computing and Information Systems
A great variety of complex systems ranging from user interactions in communication networks to transactions in financial markets can be modeled as temporal graphs, which consist of a set of vertices and a series of timestamped and directed edges. Temporal motifs in temporal graphs are generalized from subgraph patterns in static graphs which take into account edge orderings and durations in addition to structures. Counting the number of occurrences of temporal motifs is a fundamental problem for temporal network analysis. However, existing methods either cannot support temporal motifs or suffer from performance issues. In this paper, we focus on approximate …
Federated Topic Discovery: A Semantic Consistent Approach,
2020
Singapore Management University
Federated Topic Discovery: A Semantic Consistent Approach, Yexuan Shi, Yongxin Tong, Zhiyang Su, Di Jiang, Zimu Zhou, Wenbin Zhang
Research Collection School Of Computing and Information Systems
General-purpose topic models have widespread industrial applications. Yet high-quality topic modeling is becoming increasingly challenging because accurate models require large amounts of training data typically owned by multiple parties, who are often unwilling to share their sensitive data for collaborative training without guarantees on their data privacy. To enable effective privacy-preserving multiparty topic modeling, we propose a novel federated general-purpose topic model named private and consistent topic discovery (PC-TD). On the one hand, PC-TD seamlessly integrates differential privacy in topic modeling to provide privacy guarantees on sensitive data of different parties. On the other hand, PC-TD exploits multiple sources of …
Eeg Classification Based On Multi-Domain Features And Random Subspace Ensemble,
2020
Key Laboratory of Data Engineering and Visual Computing, College of Computer Science and Technology Chongqing University of Posts and Telecommunications, Chongqing 400065, China;
Eeg Classification Based On Multi-Domain Features And Random Subspace Ensemble, Deng Xin, Can Long, Jianxun Mi, Boxian Zhang, Kaiwei Sun, Wang Jin
Journal of System Simulation
Abstract: Aiming at the preprocessing feature extraction and classification recognition in BCI system, a method for EEG classification of motion imagery based on random subspaces ensemble learning of multi-domain features is proposed. Based on the analysis on the ERD/ERS characteristics of motion imagery (MI) signals, the multi-domain features of best effective time and frequency bands are extracted as the feature vectors, and the scale of the random subspace ensemble with cross-validation is adaptively chosen, and the EEG classification is realized by using linear discriminant analysis (LDA) classifiers ensemble. The test results show that the accuracy of the multi-domain features and …
The Expansion From System Simulation To Domain Simulation,
2020
1. College of Systems Engineering, National University of Defense Technology, Changsha 410073, China; ;2. The PLA's 31002 Unit, Beijing 100094, China;
The Expansion From System Simulation To Domain Simulation, Xiaogang Qiu, Yazhou Chen, Zhang Peng
Journal of System Simulation
Abstract: With the generalization of simulation application and complex system simulation becoming the focus, domain simulation is becoming more and more important. In 1995 United States Department of Defense (DoD) presented the master plan of modeling and simulation, which gives birth to the basic idea of domain simulation. The advances in information technology such as network technology and cloud computing help domain simulation to access to use. Taking the change of simulation research object as the basis, the development of simulation research from the aspects of model researches, simulation tools and simulation applications are summarized. The goal of domain simulation …
Review On Agv Scheduling Optimization,
2020
1. School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China; ;
Review On Agv Scheduling Optimization, Jianlin Fu, Hengzhi Zhang, Zhang Jian, Liangkui Jiang
Journal of System Simulation
Abstract: AGV scheduling plays an important role in improving the efficiency and reducing manufacturing cost, but it is also a very complex combinatorial optimization procedure. AGV scheduling optimization is divided into three types, AGV static scheduling, AGV dynamic scheduling and AGV simultaneous scheduling with other resources scheduling. Various methods are summarized and listed, including traditional analysis method, modeling and simulation method, intelligent optimization algorithm and hybrid optimization method, and the advantages and disadvantages of each method are also analyzed. The deficiencies of AGV scheduling research are pointed out and the research directions for future are presented.
Evaluation On Geo-Registration Accuracy Of Outdoor Augmented Reality,
2020
1. Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China; ;2. 61618 Troops, Beijing 100094, China; ;
Evaluation On Geo-Registration Accuracy Of Outdoor Augmented Reality, Deng Chen, You Xiong, Meixia Zhi
Journal of System Simulation
Abstract: Geo-registration technology is a key technology for the combination of augmented reality and geographic information systems, and its registration accuracy has a significant impact on the availability of ARGIS. Aiming at this application, the basic concepts and principles of augmented reality geo-registration technology are analyzed, and the method for quantitative evaluation of geo-registration accuracy is proposed. Combined with the pre-acquired high-precision geographic information data, a variety of outdoor geo-registration experiments are carried out by using the different hardware devices, and the quantitative accuracy of different geo-registration methods is evaluated. The geo-registration errors and the problems existing in the practical …
Research On Recursive Variable Sampling Period Scheduling Algorithm Based On Two-Parameter Priority,
2020
College of Electrical and Information Engineering Dalian Jiaotong University, Dalian 116028, China;
Research On Recursive Variable Sampling Period Scheduling Algorithm Based On Two-Parameter Priority, Weiguo Shi, Xu Chao, Wang Xun, Xiangtai Wang
Journal of System Simulation
Abstract: A recursive variable sampling periodic dynamic scheduling algorithm based on two-parameter priority is proposed for the resource-constrained network control system. The network demand degree and network urgency double parameter of the control loop are calculated, and the two-parameter weight is established by the two-square root mapping function which is created by the absolute value of the control loop error to realize the scheduling of the sensor priority. The comprehensive analysis of the control loop performance recursively adjusts the sampling period of each control loop, and completes the scheduling adjustment under the premise of ensuring the stability of the …
Finite Element Method Evaluation On Chest Blunt Injury By Rubber Projectile,
2020
College of Equipment Management and Support, Engineering University of People's Armed Police, Xi'an 710086, China;
Finite Element Method Evaluation On Chest Blunt Injury By Rubber Projectile, Wang Song, Renjun Zhan, Xiongyi Duan
Journal of System Simulation
Abstract: In order to reveal the non-lethal injury mechanism of rubber projectile and improve its safety service level, the 18.4 mm rubber projectile finite element model and the improved chest blunt injury assessment model are constructed and verified. The virtual impact test experiments under different loads are carried out, and the stress-time response and deformation-time response data are obtained. The results show that the time to reach the peak stress (less than 0.2 ms) is much shorter than the time to reach the maximum deformation variable (4~5 ms), which means the damage is not caused by the impact itself …
Simulation Analysis On Penetration To Aircraft Carrier Of Image Homing Rocket,
2020
Artillery and Air Defense Academy of PLA, Hefei 230031, China;
Simulation Analysis On Penetration To Aircraft Carrier Of Image Homing Rocket, Shidong Fang, Chen Dong, Quanli Ning, Zhang Jie, Li Yong
Journal of System Simulation
Abstract: The effect of image homing rocket projectile penetrating aircraft carrier is the important basis for its operation. According to the characteristics of projectile and aircraft carrier, the geometric equivalent model and simulation model are established, and the penetration process is simulated by LS-DYNA. Simulation results are verified by the failure form and penetration limit velocity, and show the correctness of the model. Using the established models, the penetration processes are simulated under the different conditions. The overall force on the projectile is analyzed according to the extreme acceleration value of projectile. Based on the analysis of some collected key …
Simulation On Vehicles Mandatory Lane Changing And Merging Process In Case Of Road Bottleneck,
2020
1. China Research Center for Emergency Management, Wuhan University of Technology, Wuhan 430070, China; ;2. School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430070, China;
Simulation On Vehicles Mandatory Lane Changing And Merging Process In Case Of Road Bottleneck, Lü Wei, Feizhou Huo
Journal of System Simulation
Abstract: A microscopic dynamic traffic flow model based on vehicle's mandatory lane changing behavior is established. Under the condition of road bottleneck, three macroscopic traffic flow characteristics of traffic flow, lane speed distribution and space-time diagram, and two microscopic traffic flow characteristics of merging distance and vehicle's travel time are analyzed. The simulation results show that, the total flow of arbitrary cross section of the bottleneck road can represent the overall traffic capacity, and the road bottleneck can reduce the total traffic flow by 10% to 35%, and cause a delay of 17% to 42% to the vehicle travel time …
Operation Loss Reduction Control For Large-Scale Wind Farm Based On Hybrid Modeling Simulation,
2020
Department of control and computer engineering, North China Electric Power University, Beijing 102206, China;
Operation Loss Reduction Control For Large-Scale Wind Farm Based On Hybrid Modeling Simulation, Yunqi Xiao, Wang Yi
Journal of System Simulation
Abstract: Due to the large number of transformers and collection lines in large-scale wind farms, the losses of collecting system is serious in actual operation. A reactive power/voltage control strategy is proposed, which takes wind turbines as the distributed reactive power sources to optimize the power flow in wind farm and reduce the overall losses of collector system. To improve the efficiency of wind farm modeling and multi-scene loss reduction simulation, a hybrid modeling and simulation scheme based on combining object model configuration and control algorithm programming is proposed. The wind farm model consists of module configuration, and can be …
