Numerical Analysis and Scientific Computing Commons^™

Technology Evolution Network Model And Simulation Based On Patent Citation Network, You Ge, Guo Hao, Liu Xiang

Journal of System Simulation

Abstract: On the basis of on the patent citation network and complex networks, a technology evolution network model is constrcucted, which revealed the topology structure, evolution rules and dynamics of the technology evolution network. By introducing time and fitness preferential attachments mechanism, the effect of time factor and selection law of “survival of the fittest” on evolution of network structure during the technology evolution is studied. The results showed that the technology evolution network had the characteristic of scale-free, which is the result of global selection of “survival of the fittest” in the process of technology accumulation; The effect of …

Simulation Of Benefit Distribution In Platform Delivery Mode, Zheng Wen, Chenxi Dou, Zhe Zhang

Journal of System Simulation

Abstract: Aiming at the benefit distribution relationship of platform delivery mode(PDM), the multi-agents-based model is applied to construct the benefit distribution of PDM. The Swarm simulation platform is used to explore the trading status changes of the participants under different scales; Considering the cost-profit condition, the sense of relative deprivation is introduced as the index to express the individual perception in exploring the emergency of the co-effective relationship of the individual perception and the benefit distribution in systematic and emergence points. The model and its results can reveal the benefit distribution states of the existing PDM structure and the collective …

Network Traffic Anomaly Detection Method For Imbalanced Data, Shuqin Dong, Bin Zhang

Journal of System Simulation

Abstract: Aiming at the poor detection performances caused by the low feature extraction accuracy of rare traffic attacks from scarce samples, a network traffic anomaly detection method for imbalanced data is proposed. A traffic anomaly detection model is designed, in which the traffic features in different feature spaces are learned by alternating activation functions, architectures, corrupted rates and dropout rates of stacked denoising autoencoder (SDA), and the low accuracy in extracting features of rare traffic attacks in a single space is solved. A batch normalization algorithm is designed, and the Adam algorithm is adopted to train parameters of …

Research On Generation Technology Of Computer Generated Force In Lvc Training System, Gao Ang, Zhiming Dong, Guohui Zhang, Liang Tao, Qisheng Guo

Journal of System Simulation

Abstract: LVC training system of the combat equipment under the condition of confrontation is an effective means of training, aiming at the problem that in LVC training system, computer generated forces are difficult to meet the demand of training problems. The concept of LVC training and LVC training system is clarified, according to the relationship between model and system structure, the corresponding modeling technology requirements of three different hierarchical models, namely logical range entity configuration, command entity and combat entity, are expounded. According to the specific requirements, four computer-generated force generation methods are proposed, namely, logical target range virtual and …

Quantum Simulation Of Schrödinger's Equation, Mohamed Eltohfa

Capstone and Graduation Projects

Quantum computing is one of the promising active areas in physics research. This is because of the potential of quantum algorithms to outperform their classical counterparts. Grover’s search algorithm has a quadratic speed-up compared to the classical linear search. The quantum simulation of Schrödinger’s equation has an exponential memory save-up compared to the classical simulation. In this thesis, the ideas and tools of quantum computing are reviewed. Grover’s algorithm is studied and simulated as an example. Using the Qiskit quantum computing library, a code to simulate Schrödinger’s equation for a particle in one dimension is developed, simulated locally, and run …

Structurally Enriched Entity Mention Embedding From Semi-Structured Textual Content, Lee Hsun Hsieh, Yang Yin Lee, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

In this research, we propose a novel and effective entity mention embedding framework that learns from semi-structured text corpus with annotated entity mentions without the aid of well-constructed knowledge graph or external semantic information other than the corpus itself. Based on the co-occurrence of words and entity mentions, we enrich the co-occurrence matrix with entity-entity, entity-word, and word-entity relationships as well as the simple structures within the documents. Experimentally, we show that our proposed entity mention embedding benefits from the structural information in link prediction task measured by mean reciprocal rank (MRR) and mean precision@K (MP@K) on two datasets for …

Singapore Airlines: Profit Recovery And Aircraft Allocation Models During The Covid-19 Pandemic, Michelle L. F. Cheong, Ulysses M. Z. Chong, Anne N. T. A. Nguyen, Su Yiin Ang, Gabriella P. Djojosaputro, Gordy Adiprasetyo, Kendra L. B. Gadong

Research Collection School Of Computing and Information Systems

COVID-19 has severely impacted the global aviation industry, causing many airlines to downsize or exit the industry. For airlines which attempt to sustain their operations, they will need to respond to the increase in passenger and cargo demand, as countries recover slowly from the crisis due to the availability of vaccines. We built a series of spreadsheet models to first project the COVID-19 recovery rates by countries from 2021 to 2025, then forecast the passenger and cargo demand, using historical data as base figures. Using the financial and operation data, the revenue, expense, and profit can be projected, then an …

Waste Collection Routing Problem: A Mini-Review Of Recent Heuristic Approaches And Applications, Yun-Chia Liang, Vanny Minanda, Aldy Gunawan

Research Collection School Of Computing and Information Systems

The waste collection routing problem (WCRP) can be defined as a problem of designing a route to serve all of the customers (represented as nodes) with the least total traveling time or distance, served by the least number of vehicles under specific constraints, such as vehicle capacity. The relevance of WCRP is rising due to its increased waste generation and all the challenges involved in its efficient disposal. This research provides a mini-review of the latest approaches and its application in the collection and routing of waste. Several metaheuristic algorithms are reviewed, such as ant colony optimization, simulated annealing, genetic …

Privacy-Preserving Federated Deep Learning With Irregular Users, Guowen Xu, Hongwei Li, Yun Zhang, Shengmin Xu, Jianting Ning, Robert H. Deng

Research Collection School Of Computing and Information Systems

Federated deep learning has been widely used in various fields. To protect data privacy, many privacy-preserving approaches have also been designed and implemented in various scenarios. However, existing works rarely consider a fundamental issue that the data shared by certain users (called irregular users) may be of low quality. Obviously, in a federated training process, data shared by many irregular users may impair the training accuracy, or worse, lead to the uselessness of the final model. In this paper, we propose PPFDL, a Privacy-Preserving Federated Deep Learning framework with irregular users. In specific, we design a novel solution to reduce …

Efficient Algorithms For Trajectory-Aware Mobile Crowdsourcing, Chung-Kyun Han

Dissertations and Theses Collection (Open Access)

Mobile crowdsourcing, a subclass of crowdsourcing dealing with location-specific tasks, is prevalent in our daily life. From sensing urban environment such as noise, air pollution to package delivery, various location-specific tasks are posted on mobile crowdsourcing platforms to tap on the pool of crowdsourced workers. Many digital platforms compete with each other to expand and retain their pool of crowdsourced workers. Comparing with the traditional workforce, crowdsourced workers do not dedicate their time to do tasks fully and have strong spatiotemporal preferences. The ignorance of crowdsourced workers’ mobility patterns and the lack of personalization would lead to crowdsourced workers’ exodus, …

All The Wiser: Fake News Intervention Using User Reading Preferences, Kuan Chieh Lo, Shih Chieh Dai, Aiping Xiong, Jing Jiang, Lun Wei Ku

Research Collection School Of Computing and Information Systems

To address the increasingly significant issue of fake news, we develop a news reading platform in which we propose an implicit approach to reduce people's belief in fake news. Specifically, we leverage reinforcement learning to learn an intervention module on top of a recommender system (RS) such that the module is activated to replace RS to recommend news toward the verification once users touch the fake news. To examine the effect of the proposed method, we conduct a comprehensive evaluation with 89 human subjects and check the effective rate of change in belief but without their other limitations. Moreover, 84% …

A High-Precision Machine Learning Algorithm To Classify Left And Right Outflow Tract Ventricular Tachycardia, Jianwei Zhang, Guohua Fu, Islam Abudayyeh, Magdi Yacoub, Anthony Chang, William Feaster, Louis Ehwerhemuepha, Hesham El-Askary, Xianfeng Du, Bin He, Mingjun Feng, Yibo Yu, Binhao Wang, Jing Liu, Hai Yao, Hulmin Chu, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Introduction: Multiple algorithms based on 12-lead ECG measurements have been proposed to identify the right ventricular outflow tract (RVOT) and left ventricular outflow tract (LVOT) locations from which ventricular tachycardia (VT) and frequent premature ventricular complex (PVC) originate. However, a clinical-grade machine learning algorithm that automatically analyzes characteristics of 12-lead ECGs and predicts RVOT or LVOT origins of VT and PVC is not currently available. The effective ablation sites of RVOT and LVOT, confirmed by a successful ablation procedure, provide evidence to create RVOT and LVOT labels for the machine learning model.

Methods: We randomly sampled training, validation, and testing …

An Improved Firefly Algorithm And Its Application In Washout Optimization, Wang Hui, Xingshun Lü

Journal of System Simulation

Abstract: To improve the accuracy of the firefly algorithm (FA) and solve the problem of fixed iteration step of the algorithm and easy to fall into local optimum, an improved firefly algorithm is proposed, i.e., EOFA. The EOFA algorithm combines the strong local search ability of extremal optimization algorithm with the strong search ability of firefly algorithm, and adopts the iterative step size of inverted s-type function to improve the optimization ability of the firefly algorithm. The simulation results of function optimization test shows that the improved EOFA algorithm has better optimization performance than firefly algorithm and particle swarm optimization …

Spatio-Temporal Memory Models In Spatial Cognitive Behavioral Modeling, Hu Yue, Xu Kai, Qin Long, Quanjun Yin, Yabing Zha

Journal of System Simulation

Abstract: It is crucial for military simulation systems to model the layouts of spatial environments and the temporal logic of entity activities. To improve the human-likeness of Computer Generated Forces (CGFs) and the runtime efficiency of the systems, building spatio-temporal memory representations and reasoning mechanisms that accord to mankind cognition is required. The neuro cognition science background of spatio-temporal memory is presented, and the related work on modeling the memory in deep learning and computational intelligence communities is summarized. Following the OODA (Observe-Orient-Decide-Act) loop, a general framework of spatial cognitive behavioral modeling is designed and the application of spatio-temporal memory …

Research On Cgf-Oriented Virtual Human Perceptual Attention Model, Weilong Yang, Xu Kai, Xie Xu, Sun Lin

Journal of System Simulation

Abstract: Perception model is an important research field of CGF behavior modeling. As the input of the reasoning module, the information obtained from the perception model has an important influence on the fidelity of the simulation. The CGF perception model is researched, and the attention mechanism, effective time of attention model is analyzed, compared with the traditional model of perception. By modeling the knowledge base and information feedback, a virtual human perception framework based on attention mechanism is proposed, and the experiment is carried out in the simulation environment.

Modeling Of Adversarial Behavior On Road Network Based On Non-Cooperative Game, Xiangyu Wei, Zhang Qi

Journal of System Simulation

Abstract: The modeling of adversarial behavior is the key to the study of various military-like confrontation problems. Existing research mainly focus on the target domain, but in reality, many confrontation problems occur on the road network. Combined with the network flow representation of adversarial behavior, a network adversarial game modeling framework based on non-cooperative games is proposed, and a novel road network confrontation problem—network evasion interdiction game is given based on the framework. Simulation experiments show that the new double oracle algorithm performs better than the original linear solution algorithm. Data experiments based on real road networks further verify …

Preliminary Research On Verification And Validation For Cgf Behavioral Modeling, Jianbing Tang, Zhang Qi, Jiao Peng, Yabing Zha

Journal of System Simulation

Abstract: Building computer generated force model is a very important job in combat simulation. Its core content is modeling of complicated human behavior, including cognition behavioral modeling and physical behavioral modeling. The credibility is vital for behavioral model. Verification and validation (V&V) in all life circle of behavioral modeling can insure the credibility of behavioral model. On the basis of explaining V&V of behavioral modeling and other conceptions, the process model of behavioral modeling is proposed. The V&V process of CGF behavioral modeling is studied emphasizly. Many effective V&V methods for CGF behavioral modeling are explored.

Review On The Construction And Application Of Digital Twins In Transportation Scenes, Zhaohui Wu, Zhenzheng Liu, Shi Ke, Wang Liang, Xiaojie Liang

Journal of System Simulation

Abstract: Digital twins connect the physical world and the information world, and provide new ideas for the analysis and solution of complex traffic problems. The research and application status of digital twins in transportation scenes are reviewed on the basis of sorting out the basic concepts, development history and key technologies of digital twins. The key technologies for the construction of digital twins in transportation scenes that need to be breakthrough are analyzed from the four aspects of "people-vehicle-road-environment" combined with the characteristics of the elements of traffic operation. The prospect of digital twin transportation applications in the development of …

Refined Alignment Method For Single-Axis Rotary Inertial Navigation Based On Fuzzy Adaptive Filtering, Hu Jie, Xiaozhu Shi

Journal of System Simulation

Abstract: In order to restrain the influence of saw tooth velocity error caused by the inertial measurement unit (IMU) rotation on the initial alignment accuracy of single-axis rotary strapdown inertial navigation system (SINS), a refined alignment method based on fuzzy adaptive Kalman filtering is proposed. After calculating the ratio of actual covariance to theoretical covariance of the innovation sequence, the method adaptively adjusts the measurement noise covariance matrix by using the fuzzy inference system (FIS), so that it can adapt to the changes of measurement noise caused by IMU rotation. The initial alignment validation experiments under the swing environment …

An Intrusion Detection Algorithm Based On Ifoa And Welm, Jianwu Dang, Tan Ling

Journal of System Simulation

Abstract: An intrusion detection algorithm of WELM optimized by IFOA is proposed. The advantages of short training time and good generalization performance of WELM are used, and the weight of minority attacks is increased, so that the recall rate of minority attacks in network attacks is greatly improved.The FOA with adaptive adjustment of the iterative step size is used, so the input weights and bias of the hidden layer in the WELM are globally optimized to avoid the algorithm falling into local optimal solution and realize the classification of the NSL-KDD intrusion detection data set. The experimental results show …