Artificial Intelligence and Robotics Commons^™

Teachers’ Engagement And Self-Efficacy In A Pk–12 Computer Science Teacher Virtual Community Of Practice, Robert Schwarzhaupt, Feng Liu, Joseph Wilson, Fanny Lee, Melissa Rasberry

Journal of Computer Science Integration

Prekindergarten to 12th-grade teachers of computer science (CS) face many challenges, including isolation, limited CS professional development resources, and low levels of CS teaching self-efficacy that could be mitigated through communities of practice (CoPs). This study used survey data from 420 PK–12 CS teacher members of a virtual CoP, CS for All Teachers, to examine the needs of these teachers and how CS teaching self-efficacy, community engagement, and sharing behaviors vary by teachers’ instructional experiences and school levels taught. Results show that CS teachers primarily join the CoP to gain high-quality pedagogical, assessment, and instructional resources. The study also found …

Reinforcement Learning Algorithms: An Overview And Classification, Fadi Almahamid, Katarina Grolinger

Electrical and Computer Engineering Publications

The desire to make applications and machines more intelligent and the aspiration to enable their operation without human interaction have been driving innovations in neural networks, deep learning, and other machine learning techniques. Although reinforcement learning has been primarily used in video games, recent advancements and the development of diverse and powerful reinforcement algorithms have enabled the reinforcement learning community to move from playing video games to solving complex real-life problems in autonomous systems such as self-driving cars, delivery drones, and automated robotics. Understanding the environment of an application and the algorithms’ limitations plays a vital role in selecting the …

A Learning And Optimization Framework For Collaborative Urban Delivery Problems With Alliances, Jingfeng Yang, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The emergence of e-Commerce imposes a tremendous strain on urban logistics which in turn raises concerns on environmental sustainability if not performed efficiently. While large logistics service providers (LSPs) can perform fulfillment sustainably as they operate extensive logistic networks, last-mile logistics are typically performed by small LSPs who need to form alliances to reduce delivery costs and improve efficiency, and to compete with large players. In this paper, we consider a multi-alliance multi-depot pickup and delivery problem with time windows (MAD-PDPTW) and formulate it as a mixed-integer programming (MIP) model. To cope with large-scale problem instances, we propose a two-stage …

Gradient Free Sign Activation Zero One Loss Neural Networks For Adversarially Robust Classification, Yunzhe Xue

Dissertations

The zero-one loss function is less sensitive to outliers than convex surrogate losses such as hinge and cross-entropy. However, as a non-convex function, it has a large number of local minima, andits undifferentiable attribute makes it impossible to use backpropagation, a method widely used in training current state-of-the-art neural networks. When zero-one loss is applied to deep neural networks, the entire training process becomes challenging. On the other hand, a massive non-unique solution probably also brings different decision boundaries when optimizing zero-one loss, making it possible to fight against transferable adversarial examples, which is a common weakness in deep learning …

Towards Adversarial Robustness With 01 Lossmodels, And Novel Convolutional Neural Netsystems For Ultrasound Images, Meiyan Xie

Dissertations

This dissertation investigates adversarial robustness with 01 loss models and a novel convolutional neural net systems for vascular ultrasound images.

In the first part, the dissertation presents stochastic coordinate descent for 01 loss and its sensitivity to adversarial attacks. The study here suggests that 01 loss may be more resilient to adversarial attacks than the hinge loss and further work is required.

In the second part, this dissertation proposes sign activation network with a novel gradient-free stochastic coordinate descent algorithm and its ensembling model. The study here finds that the ensembling model gives a high minimum distortion (as measured by …

Data-Driven Learning For Robot Physical Intelligence, Leidi Zhao

Dissertations

The physical intelligence, which emphasizes physical capabilities such as dexterous manipulation and dynamic mobility, is essential for robots to physically coexist with humans. Much research on robot physical intelligence has achieved success on hyper robot motor capabilities, but mostly through heavily case-specific engineering. Meanwhile, in terms of robot acquiring skills in a ubiquitous manner, robot learning from human demonstration (LfD) has achieved great progress, but still has limitations handling dynamic skills and compound actions. In this dissertation, a composite learning scheme which goes beyond LfD and integrates robot learning from human definition, demonstration, and evaluation is proposed. This method tackles …

Laser Surface Treatment And Laser Powder Bed Fusion Additive Manufacturing Study Using Custom Designed 3d Printer And The Application Of Machine Learning In Materials Science, Hao Wen

LSU Doctoral Dissertations

Selective Laser Melting (SLM) is a laser powder bed fusion (L-PBF) based additive manufacturing (AM) method, which uses a laser beam to melt the selected areas of the metal powder bed. A customized SLM 3D printer that can handle a small quantity of metal powders was built in the lab to achieve versatile research purposes. The hardware design, electrical diagrams, and software functions are introduced in Chapter 2. Several laser surface engineering and SLM experiments were conducted using this customized machine which showed the functionality of the machine and some prospective fields that this machine can be utilized. Chapter 3 …

Research On Hybrid Deployment Strategy And Model For Key Position Air-Defense Based On Multi-Weapon Platforms, Jiaqing Wan, Pengfei Wang, Junlin Tang, Zhang Dong, Xinguo Li

Journal of System Simulation

Abstract: Multi-platform cooperative air-defense is the development direction of air-defense and antimissile warfare, and the hybrid deployment strategy and model are the important research content. Based on the background of key position air-defense research, the deployment strategy, principle and form of multi-platform cooperative air-defense are studied. The operational scenario and operational process of typical air defense are established. The principles, influencing factors and deployment methods of hybrid deployment are studied. A typical hybrid deployment strategy is proposed and a mathematical model is established. It provides support for the multi platform cooperative air defense and key position defense deployment.

Co-Simulation Of Parallel Computing Of Disc Temperature Distributed Parameter System Cooling Rate Control, Shengdong Gao, Yu Xin

Journal of System Simulation

Abstract: Aiming at the problem of large number of grids and long computation time in numerical simulation of complex engineering problems, combining the User-defined Function (UDF) parallel computing principle with UDP (User Datagram Protocol) communication in Fluent, the data transfer of the parallel calculation between Fluent and the visual simulation tool (Simulink) is completed by embedding UDF and S function in UDP communication. And the parallel calculation and simulation platform of the disk and billet gas impingement jet quenching is built. The serial and parallel calculation of the same model are carried out, and the comparative analysis of the numerical …

Research On Integrated Optimization Approach For Car-Sharing Systems, Tang Jie, Jinxin Cao

Journal of System Simulation

Abstract: Effective scheduling and routing of employees and vehicles determines the efficiency of car-sharing systems. Aiming at the scheduling of shared cars within one day, with the objective of minimizing the total system costs and personnel costs, a bi-level optimization model for multiple traveling salesman problem with time windows is established. A genetic algorithm with multi-chromosome coding and the optimized complex mutation operator are developed for the problem solution. From the comprehensive computational experiments, it can be concluded that the total numbers of vehicles and employees with the joint routing plans satisfying the order constraints can be obtained in …

The Allocation Of Jamming Resources Based On Double Q-Learning Algorithm, Xingyuan Huang, Yanyi Li

Journal of System Simulation

Abstract: In modern warfare, the multifunctional trend of radars, even multiple radars detecting targets together, enhances the anti-jamming capability of radars. However, the traditional jamming system still follows a fixed jamming strategy, and the real-time performance of decision-making facing large numbers of radars is poor. And the cognitive jamming study is urgent. The concept of reinforcement learning is explained and the difference between Q learning algorithm and double Q learning algorithm is compared. The reinforcement learning algorithm is used to establish a model based on cognitive electronic warfare to realize the allocation of radar jamming strategies. The simulation of the …

Relationship Between Suspension Damping And Stability Of Vehicle Hunting Motion, Yan Yong, Zeng Jing, Kun Xu, Feiyan Zhao

Journal of System Simulation

Abstract: In order to avoid or restrain the primary hunting stability of rail vehicles, correlation between the primary hunting stability and suspension damping parameters under the damping ratio of 0 and 5% is calculated based on the analysis of suspension parameters on the vehicle modal frequency. The method to improve the stability of vehicle hunting motion by optimizing suspension parameters is obtained. The results show that when selecting different damping ratios to calculate the critical stability, the range of damping parameters varies greatly. The lateral damping parameter in a certain range or a larger vertical damping is beneficial to keep …

A Signal Decomposition Method Based On Multi-Layer Iteration Structured Singular Spectrum Analysis, Yumiao Wei, Zhili Zhang, Hongguang Li, Shuqing Li

Journal of System Simulation

Abstract: To process the complex signals with concentrated frequency distribution, an adaptive decomposition method based on singular spectrum analysis with multi-layer iteration structure is researched. The traditional singular spectrum analysis is improved by frequency band subdivision and iterative filtering approach. A high-precision decomposition algorithm base on recursive structure is therefore designed, solving the problems such as insufficient adaptive capability and unsatisfied decomposition. Simulation results show that adaptive decomposition capability of the proposed method is effectively enhanced. For the multi-mode vibration signal with 0.2% ratio of spitting frequency to center frequency, the components are all accurately extracted, and consistent well …

Obstacle Avoidance Path Planning Of Bridge Crane Based On Improved Rrt Algorithm, Zhimei Chen, Li Min, Xuejuan Shao, Zhicheng Zhao

Journal of System Simulation

Abstract: In view of the problem that the reasonable path can not be obtained quickly for bridge crane planning in complex environment, a rapidly exploring random tree (RRT) algorithm combined with particle swarm algorithm is proposed. According to the characteristics of the bridge crane operation, the RRT algorithm is improved. The two-way RRT algorithm is used to make the tree grow in the direction of the target according to the probability. When the path is generated, the particle swarm optimization algorithm is used to smooth the path to get a more suitable path for the operation of the bridge crane. …

Short-Term Power Load Forecasting Based On Lstm Neural Network Optimized By Improved Pso, Tengfei Wei, Tinglong Pan

Journal of System Simulation

Abstract: To improve the accuracy of short-term power load forecasting, a short-term power load forecasting model (ACMPSO-LSTM) based on long-short memory neural network (LSTM) optimized by adaptive Cauchy mutation particle swarm optimization (ACMPSO) is proposed. For the problem of difficult selection of LSTM model parameters, ACMPSO is used to optimize model parameters, and non-linear changing inertia weights are adopted to improve the global optimization ability and convergence speed of PSO algorithm. In the optimization process, a mutation operation based on genetic algorithm is added to reduce the risk of particles falling into local optimal solutions. The simulation results show that …

Mpc Algorithm Design Based On Improved Macroscopic Traffic Flow Model, Hongguang Pan, Gao Lei, Wenyu Mi

Journal of System Simulation

Abstract: In order to obtain stable and orderly traffic flow, a model predictive control method based on improved macroscopic traffic flow model is proposed for highway system. Considering the uncertainty caused by the inflow and outflow of ramp, the method takes the traffic density and velocity of each section as the control target. Based on the traditional macroscopic traffic flow model, a macroscopic traffic flow state space model is improved. Aiming at the problem of multiple variables and control constraints, a traffic flow density and velocity controller based on model predictive control is designed to ensure better control effect. The …

Method Of Battlefield Frequency Allocation Based On Chaotic Perturbation Mechanism Particle Swarm Optimization Algorithm, Niu Kan, Li Bing, Fu Qiang

Journal of System Simulation

Abstract: In order to carry out the frequency allocation in the electromagnetic environment of battlefield and reduce the frequency equipment interference of various forces, a frequency allocation method based on chaotic perturbation mechanism particle swarm optimization algorithm is proposed. Which transforms battlefield frequency allocation into the optimal spectrum resource search and solution problem with constraints. The frequency allocation model with the lowest interference cost is built and the frequency allocation through the improved particle swarm optimization algorithm is carries out. The chaotic perturbation mechanism is introduced to improve the population diversity and the global optimization ability of the …

Sar Imaging Seeker Interference Modeling & Evaluation And Simulation System Design, Xueping Luo, Yunhe Cao, Hu Qi, Shutao Chen, Shijie Yan, Cai Xi

Journal of System Simulation

Abstract: For the simulation, evaluation and verification of SAR imaging seeker interference, the modeling and evaluation of SAR imaging seeker interference and design of simulation system are discussed. The simulation system can be used to model and simulate the target environment, jamming and seeker at the signal level. The signal environment simulation, echo signal acquisition, signal processing and other processes can be simulated under the environment of multiple interference signals, and the interference effect can be evaluated at the same time. The validity and practicability of the simulation system are verified with simulation test. The design of this simulation system …

Game Analysis Of Government Procurement Contract Financing Based On Blockchain Technology, Haitao Huang, Qinming Liu, Chunming Ye, Chen Xiang

Journal of System Simulation

Abstract: Abstract: In view of the financing difficulties of small and medium-sized enterprise and the existing credit problems of financial supply chain, the block chain technology is applied to the financing mode of government procurement contract of the Ministry of Finance. From the supply chain business aspect, the tripartite game model of government procurement departments, small and medium-sized enterprises and banks is built, and the decision of the main body is analyzed. From the block chain technology, the evolutionary game model is built and the selection of chain node is analyzed. By MATLAB, the simulation experiments are carried out to …

Residential Demand Response Scheduling Optimization And Simulation Based On An Improved Pso Algorithm, Huazhen Li, Youquan Liu, Jiawei Zhu, Liao Qiang

Journal of System Simulation

Abstract: Aiming at the problems of low utilization rate of household load energy and the potential damage to the power grid caused by the lack of systematic and efficient management of household power consumption, the power consumption characteristics of controllable equipment and the energy storage characteristics of electric vehicles are modeled respectively, and the scheduling optimization objective function of household equipment under time of use price is established, and the improved particle swarm optimization algorithm is used to solve the problem. Through the example simulation, the residential power dispatching under various scenarios is analyzed. The experimental results show that the …

Self-Learning-Based Multiple Spacecraft Evasion Decision Making Simulation Under Sparse Reward Condition, Zhao Yu, Jifeng Guo, Yan Peng, Chengchao Bai

Journal of System Simulation

Abstract: In order to improve the ability of spacecraft formation to evade multiple interceptors, aiming at the low success rate of traditional procedural maneuver evasion, a multi-agent cooperative autonomous decision-making algorithm, which is based on deep reinforcement learning method, is proposed. Based on the actor-critic architecture, a multi-agent reinforcement learning algorithm is designed, in which a weighted linear fitting method is proposed to solve the reliability allocation problem of the self-learning system. To solve the sparse reward problem in task scenario, a sparse reward reinforcement learning method based on inverse value method is proposed. According to the task scenario, …

Hybrid System Simulation Method Based On Quantized State, Zhihua Li, Jiang De, Hanwu Shen, Zhihua Fan

Journal of System Simulation

Abstract: Hybrid system simulation and discontinuity processing have always been the difficulties of the time-discretized integration methods, while Quantized State System (QSS) is a new numerical integration method based on state variable discretization. Aiming at the hybrid systems simulation, a method of QSS+DEVS is proposed. The discrete part of hybrid system is represented as DEVS model, and the continuous part of hybrid system is discretized by QSS, which can also be represented as DEVS model. The simulation model of the whole hybrid system is obtained by coupling the two DEVS models. The accuracy, efficiency and simplicity of the QSS+DEVS method …

Modeling On Anti-Uav System-Of-Systems Combat Ooda Loop Based On Netlogo, Zhao Zhu, Wang Yi, Ruifeng Fan, Liya Li, Qi Meng

Journal of System Simulation

Abstract: Aiming at the threats from unmanned aerial vehicle (UAV) or swarm, as well as the difficult problems of systems confrontation modeling, overall process design, and operational effectiveness evaluation in anti-UAV system-of-systems, the structure and operational process both of the UAV and anti-UAV systems are analyzed respectively, and the anti-UAV Observe-Orient-Decide-Act (OODA) system-of-systems combat model which based on multi-agent modeling platform NetLogo is proposed. Utilizing the emergence of agent role in this simulation model, the influence exerted by OODA on anti-UAV is studied by the multi-agent simulation. The results show that the OODA loop is one …

Application Of Trust Driven Adaptive Cooperative Control Algorithm, Xindong Gui, Hongjiang Ji, Lingling Fan, Shida Liu

Journal of System Simulation

Abstract: When a multi-manipulator performs cooperative task, it's end position is difficult to accurately track the target and ensure the consistency influenced by the nonlinear factors such as working environment, assembly condition and system disturbances, resulting in large errors during collaborative work. To solve multi-manipulators position coordinated control problem, a multi-agent based adaptive position coordination control algorithm is proposed by researching on the novel trust mechanism, including adaptive update mechanism of trust value (self-trust and mutual-trust) and Fisher information weighted (covariance) update mechanism. In automated collaborative assembly tasks, the precise consensus positioning of end-effector is achieved with improvements in the …

Simulation Analysis Of Assessment Method For Missile Accuracy, Shuqing Li, Zhili Zhang, Yumiao Wei, Haitao Wang

Journal of System Simulation

Abstract: The missile accuracy of the falling points is one of the important performance indexes of missile systems, so the assessment method is very important. An improved algorithm for missile accuracy assessment is proposed. Accuracy assessment problem is simplified as a hypothesis check for probability circle, and the accuracy difference coefficients are defined to describe the accuracy difference between the real falling points and the expected situation. Based on the probability circle method, an improved risk assessment method is put forward to balance and minimize producer's risk and consumer's risk. According to sequential check method, this risk assessment …

Cloud Model Pid Control Of Pmsm Based On Svm Inverse System, Li Hui, Yun Hao, Hongli Yue

Journal of System Simulation

Abstract: Aiming at the problem of multivariable, nonlinearity and strong coupling of the permanent magnet synchronous motor(PMSM), a strategy of inverse system identification which is independent of precise mathematical model and parameters based on support vector machines(SVM) is proposed. The dynamic decoupling control of PMSM is researched based on multivariable nonlinear control inverse system theory. To deal with direct inverse control open-loop system with poor robustness and inverse modeling error of SVM, a parameter self-tuning PID(Proportional Integral Differential) closed-loop controller based on cloud model rule inference is designed. The simulation results confirm that the cloud model PID control based on …

Combination Weighting-Based Comprehensive Evaluation For Discrete Workshop Production Plan, Zhangzhen Luo, Haifan Jiang, Jianlin Fu, Guofu Ding

Journal of System Simulation

Abstract: Aiming at the lack of a general evaluation index system and a comprehensive evaluation method combining qualitative and quantitative for discrete workshop production planning, an evaluation index system is constructed from the economy, timeliness and adaptability and a combination weighting-based comprehensive evaluation method is proposed. A combination weight of subjective and objective significance is obtained by combining the extension of analytic hierarchy process, entropy value method and improved CRITIC (Criteria Importance Through Intercriteria Correlation) method, which improves the scientific evaluation of discrete workshop production planning. The verification results of examples show that the method is more sensitive to the …

Actuator Fault Status Evaluation Based On Two-Class Nmf Network, Yinsong Wang, Tianshu Sun

Journal of System Simulation

Abstract: In the feedback control loop, the adjustment ability of controller covers up the performance degradation of the actuator to some degree. A fault state evaluation algorithm based on a two-class non-negative matrix network is proposed to implement online fault state monitoring of the actuator, including fault classification and degradation assessment. The local static features of the samples are extracted, and a classifier model is established to form a network. The similarity is introduced to describe the dynamic characteristics between samples. To fulfill the actuator fault status assessment, the static distance and dynamic changes of the network output are merged …

Small-Data Driven Modeling And Simulation Of High-Speed Train Running Time Under Limited Speeds, Xu Peng, Guoqi Feng, Xuewu Dai, Dongliang Cui, Qilong Wei, Baoxu Li, Jianming Li

Journal of System Simulation

Abstract: In order to provide data support and evaluate the feasibility of high-speed train group scheduling optimization algorithm, a method of combining the mechanism model with the small-data drive is proposed. The train segment fitting model under speed limit is constructed and parameterized to reduce the number of parameters to be identified: In order to avoid the improper fitting, a parameter fitting algorithm based on the particle swarm optimization and the least square is proposed. “Location-Time-Speed” model for temporary speed limits together are proposed. The model is demonstrated on the simulation platform, and the train running time is simulated accurately …

Research And Application Of Simulation Support Platform For System-Of-Systems Combat, Xiaodong Huang, Kongshu Xie, Li Ni, Xuefeng Yan, Yali Zhao

Journal of System Simulation

Abstract: Based on the requirement of developing high-precision, high-reliability, and high-fidelity SoS (System-of-Systems) combat simulation system efficiently, the overall structure of SoS combat simulation platform is designed with the implementation process of the SoS simulation development as the starting point. The key methods such as the parameterized & serviced SoS simulation framework, SoS combat oriented multi-view collaborative modeling, extensible high-performance distributed parallel simulation, and intelligent simulation evaluation based on large data & deep learning are emphatically put forward and implemented. A simulation platform is developed to support the weapon equipment SoS combat simulation deduction and evaluation in complex environment. Applications …