Computer Sciences Commons^™

An Empirical Analysis Of New Perspectives For Strategy Solving In Intelligent Game-Theoretic Decision-Making, Jiongming Su, Junren Luo, Shaofei Chen

Journal of System Simulation

Abstract: With the development of artificial intelligence technology, especially the promotion of largescale pre-training model theory, some new perspectives of strategy solving for intelligent game-theoretic decision-making have gradually been widely concerned and discussed. This paper combines the development of artificial intelligence technology and the transformation of strategy solving paradigm for intelligent game-theoretic decision-making, takes Chess (two-player zero-sum perfect information game), diplomacy (multi-player general-sum imperfect information game), and StarCraft Multi-Agent Challenge (multi-agent Markov game) as the research object for empirical analysis on sequential decision-making, the new paradigm and new way of strategy solving are analyzed according to the new perspective of …

Intelligent Service Migration Towards Mec-Based Iov Systems, Sijin Huang, Jia Wen, Zheyi Chen

Journal of System Simulation

Abstract: To address the problem of QoS degradation during the vehicle movement, a novel service migration via convex-optimization-enabled deep reinforcement learning (SeMiR) method is proposed. The optimization problem is decomposed into two sub-problems and solved separately. For the service migration sub-problem, an improved deep reinforcement learning based service migration method is designed to explore the optimal migration policy. For the resource allocation sub-problem, a convex optimization based resource allocation method is developed to derive the optimal resource allocation for each MEC server under the given migration decisions, thereby improving the performance of service migration. Experimental results show that the SeMiR …

Intensity-Based Feature Filtering For Lidar-Based Slam, Weigang Li, Shaofeng Zou, Yongqiang Wang, Chuxiang Yu

Journal of System Simulation

Abstract: In order to solve the problem that an excessive influx of feature points into the point cloud registration phase can potentially lead to diminished algorithmic accuracy and suboptimal mapping outcomes, a novel laser SLAM algorithm predicated on the filtering of feature points through the utilization of intensity information is proposed. The intensity distribution near the feature points in the local map is calculated based on the point cloud intensity information, and each feature point within the local map is attributed an intensity distribution index. Through the application of an intensity threshold, feature points that exhibit substantial variations in intensity …

A Hybrid Heuristic Algorithm For Solving The Green Vrp With Priority Delivery, Huanhuan Cui, Lihe Guan

Journal of System Simulation

Abstract: This paper considers the problem that some customers' goods cannot be mixed in logistics distribution. Based on the traditional green vehicle routing problem with simultaneous pickup and delivery, customers are divided into three types: priority delivery, non-priority only pickup without delivery, and non-priority pickup with delivery. A single objective nonlinear optimization model is established to minimize the total cost. A hybrid heuristic method based on simulated annealing and adaptive large neighborhood search algorithm is designed. An improved saving algorithm is used to construct the initial solution. And 5 kinds of destruction operators and 2 kinds of repair operators are …

Point Cloud Registration Method Based On Improved Grey Wolf Algorithm And Adaptive Splitting Kd-Tree, Yuanhao Du, Xiuli Geng, Chengzhi Xu, Yinhua Liu

Journal of System Simulation

Abstract: Traditional GWO algorithms suffer from limitations such as insufficient search efficiency and susceptibility to local optima. A novel method for the registration of point clouds of complex industrial components is proposed based on an improved GWO algorithm and ICP. To address the problem of uneven population distribution caused by random initialization in GWO, chaotic mapping is employed to initialize the gray wolf population, ensuring a more uniform distribution of individuals within the search space. A non-linear control parameter strategy is introduced to strike a balance between the algorithm's local search and global search capabilities. Elite reverse learning is integrated …

Gaussian Chaotic Fire Hawk Optimization Algorithm For Solving Dynamic Optimization Problems, Yongzhang Chen, Yuanbin Mo

Journal of System Simulation

Abstract: There are many important chemical processes in the chemical industry rely on dynamic optimization with factors such as nonlinearity and discontinuity. In order to find a more efficient solution algorithm, Gaussian Chaotic fire hawk optimization algorithm is proposed based on the fire hawk optimization algorithm, which is used to solve such problems after parameterizing the control variables. The original way of initializing the populations is replaced using tent chaotic mapping in order to make more sense of the initial distribution of the algorithm; a more targeted update method has been proposed in the analysis of fire hawk location updates …

Coordinated And Optimal Dispatching For Wind-Photovoltaic-Storage Systems Based On Multi-Strategy Multi-Objective Differential Evolution Algorithm, Xuyang Ren, Xuhui Bu, Yanling Yin, Jinghua Liu

Journal of System Simulation

Abstract: The introduction of new energy generation units makes the power system structure more and more complex, and the existing economic dispatching methods face many challenges. A coordinated and optimal dispatching for wind-photovoltaic-storage systems is constructed and a constraint handling method is given, a competitive mechanism-based multi-strategy multi-objective differential evolutionary (CMMODE) algorithm is proposed. The CMMODE algorithm utilizes a competitive mechanism to partition the population and constructs multiple differential variance operators based on the partitioning results, thus generating a multi-strategy scheme, employs an elite self-exploration mechanism to make the population have the ability to jump out of the local optimum …

Research On Rule-Based Energy Management Strategy Of Hybrid Mining Dump Truck, Jiangong Liu, Yuanhui Zhang, Fei Wei, Yiying Wang, Xiaoling Li, Peiqing Liu, Fengmiao Si

Journal of System Simulation

Abstract: A distributed hybrid powertrain system structure and a rule-based energy management strategy are proposed to address the problems of insufficient power and poor fuel economy in conventional dieselpowered mining dump trucks. By analyzing the operational characteristics of mining dump trucks, a distributed hybrid powertrain system structure and vehicle driving conditions are established, relevant mode-switching rules are formulated. The results demonstrate that the proposed distributed hybrid powertrain system structure enhances the climbing capability of the vehicle by 27% when using the third gear for uphill driving. In addition, the adoption of the rule-based energy management strategy results in an 19% …

Construction Of A Digital Twin-Based Ship Manufacturing Workshop Monitoring System, Tianxiang Hu, Hui Ye, Xiaofei Yang

Journal of System Simulation

Abstract: In order to address issues of opacity in production information and difficulties in collecting equipment data in shipbuilding workshops, a digital twin ship manufacturing workshop monitoring system is designed based on the Unity physics platform. The essential steps in building a virtual reality platform are outlined, encompassing the creation of a virtual ship workshop, the development of data transmission methods for multi-source heterogeneous data acquisition, implementation of data-driven methods for achieving virtual-real synchronization, and enhancement of data visualization capabilities. By practically designing a real-time monitoring system for the welding assembly line production process in shipbuilding, the 3D scene reproduction …

Improved Target Detection Algorithm For Aerial Images Based On Yolov5, Yecai Guo, Jingdong Sun, Saha Amitave

Journal of System Simulation

Abstract: In order to improve the existing small target detection methods, which suffer from low detection accuracy, high false detection rate and high leakage rate, the FSD-YOLOv5 algorithm is proposed, which has three improvements based on the YOLOv5 algorithm. The Focal EIoU is used instead of the original CIoU to improve the model convergence speed and regression accuracy. To cope with the deficiencies in CNN architecture, we adopt a new CNN building block called SPD-Conv is adopted. To address the problem of the reduced or lost information of small objects in feature maps caused by downsampling in convolutional neural networks, …

Integrating Neural Networks For Predictive Torque Control And Obstacle Avoidance In Autonomous Robot, Viswanath Kodali, Harsha Vardhan Borra, Kiran P

Northeast Journal of Complex Systems (NEJCS)

In the field of robotics, precise motion control and accurate computation of joint forces are critical for ensuring optimal performance. Traditional methods, such as using the Jacobian matrix for joint angle determination and Euler-Lagrange equations for torque computation, are reliable but computationally intensive, making them less suitable for real-time applications. This paper presents an advanced approach to improving the productivity and efficiency of a 3-Degree of Freedom (DOF) robotic arm by utilizing Artificial Neural Network (ANN). The proposed system dynamically predicts joint angles and torque, enabling faster and more efficient motion control.

To address the challenge of obstacle avoidance in …

Multimodal Search On A Line, Jared Coleman, Dmitry Ivanov, Evangelos Kranakis, Danny Krizanc, Oscar Morales Ponce

Computer Science Faculty Works

Inspired by the diverse set of technologies used in underground object detection and imaging, we introduce a novel multimodal linear search problem whereby a single searcher starts at the origin and must find a target that can only be detected when the searcher moves through its location using the correct of p possible search modes. The target’s location, its distance d from the origin, and the correct search mode are all initially unknown to the searcher. We prove tight upper and lower bounds on the competitive ratio for this problem. Specifically, we show that when p is odd, the optimal …

Rapid Prediction Of Coastal Flooding With Deep Neural Networks, Ali Shahabi, Navid Tahvildari

Graduate Student Government Association Research Conference

With the increasing impact of climate change and relative sea level rise, low-lying coastal communities face growing risks from extreme storm tides and recurrent nuisance flooding. Thus, timely and reliable predictions of coastal water levels are critical to resilience in vulnerable coastal areas. Over the past decade, enormous efforts have been made to utilize machine learning (ML) based data-driven models for the emulation and prediction of storm tides. However, flood advisory systems still rely on running computationally demanding real-time hydrodynamic models. because developing highly reliable ML-based models suitable for real-time forecasting and capable of capturing any surge levels is challenging. …

Why Are Fairness Concerns So Important? Lessons From A Last-Mile Transportation System, Yiwei Chen, Hai Wang

Research Collection School Of Computing and Information Systems

The Last-Mile Problem refers to the provision of travel service for passengers from the nearest public transportation node to the final destination. The Last-Mile Transportation System (LMTS), which has recently emerged, provides on-demand last-mile transportation service for passengers. We consider an LMTS that consists of two types of passengers, regular-type passengers and special-type passengers (e.g., seniors, disabled people). The valuation of the last-mile service for special-type passengers is statistically higher than the one for regular-type passengers. Passengers incur disutility from waiting for the last-mile service. In this paper, we explore two fairness constraints on special-type passengers: (1) the fare for …

Pilot Study: Initial Investigation Suggests Differences In Emt-Associated Gene Expression In Breast Tumor Regions, Kylie L. King, Hamed Abdollahi, Zoe Dinkel, Alannah Akins, Homayoun Valafar, Heather Dunn

Faculty Publications

Triple negative breast cancer (TNBC) is the most aggressive subtype and disproportionately affects African American women. The development of breast cancer is highly associated with interactions between tumor cells and the extracellular matrix (ECM), and recent research suggests that cellular components of the ECM vary between racial groups. This pilot study aimed to evaluate gene expression in TNBC samples from patients who identified as African American and Caucasian using traditional statistical methods and emerging Machine Learning (ML) approaches. ML enables the analysis of complex datasets and the extraction of useful information from small datasets. We selected four regions of interest …

In Memoriam - Nora Sabelli: Master Orchestrator Of Grant Programs And Mentor For Advancing The Interdisciplinary Learning Sciences Field, Eric Hamilton, Jeremy Roschelle, Roy Pea, Barbara Means, Louis Gomez, Kim Gomez, Nancy Butler Songer

Education Division Scholarship

On Friday, September 6, 2024, the learning sciences field lost a giant in Dr. Nora Sabelli, 87 years old, a personal mentor to many researchers and an inspiration to so many learning scientists and STEM leaders. Nora’s first professional career was as a computational chemist, and later she became a passionate leader in research for improving STEM education. Nora’s time as a senior program officer at the National Science Foundation’s (NSF) Education and Human Resources (EHR) directorate was legendary; she was a force of nature who reshaped funding priorities for stronger science and a stronger connection of science to education …

Sequential Convex Programming Using Safe Flight Corridor For Trajectory Planning Of Uavs, Zhu Wang, Zhenpeng Zhang, Mengtong Zhang, Guangtong Xu

Journal of System Simulation

Abstract: To address the issues of sensitivity to initial values and weak convergence of sequential convex programming(SCP) based time-optimal trajectory planning for UAVs, a SCP method using safety flight corridor, denoted as SFC-SCP(safe flight corridor-sequential convex programming) is proposed. According to the obstacle avoidance path obtained from the front-end path planning, a safe flight corridor is constructed by forming a convex polygon safe flight area without obstacles for each trajectory point. The non-convex obstacle avoidance constraint is converted into linear inequality constraints to improve convergence ability. The rear-end SCP method is used to transform the nonlinear trajectory optimization problem under …

Task Reallocation Method For Unmanned Swarm Under Adversarial Conditions, Lun Zhang, Mei Yang, Tuo Zhao, Shuiku Zhang, Jian Huang

Journal of System Simulation

Abstract: Heterogeneous unmanned swarms have important potential applications in future wars. However, during the high-intensity confrontation in the battlefield, how to efficiently and quickly redistribute the tasks carried by the damaged agents so that the swarms could successfully complete the mission is a difficult problem that must be addressed in the combat application of unmanned swarms. This paper proposes a task reallocation method named improved CNP-HA (contract net protocol-Hungarian algorithm). Through the allocation mechanism and the bidding mechanism, the method realizes the task reallocation of damaged agents with lower communication cost and faster speed comparing with baseline methods. In the …

Moving Target Velocity Measurement Method Based On Multi-View Observation Optimization Of Uav Image, Yuxin Wu, Zhilong Zhang, Aoxu Liu, Jiangwei Zou, Chuwei Li

Journal of System Simulation

Abstract: Measuring the position and velocity of moving targets is an important requirement for drone video analysis. In this paper, a moving target localization and velocity estimation algorithm based on least square optimization of UAV multi-view observation images is proposed: the video and corresponding pose parameters obtained by the airborne optoelectronic system are used to establish a line-of-sight model at multiple observation times, it is unified to the WGS-84 coordinate system by coordinate transformation, the position and velocity of the moving target are estimated based on the least squares algorithm. This algorithm does not require laser ranging information between the …

A Visual Servo Precision Assembly Method For Riveting Parts Based On Adaptive Extended Kalman Filtering, Zonggang Li, Yanbo Li, Jianjun Jiao, Yajiang Du

Journal of System Simulation

Abstract: Aiming at the problems of multiple peg-in-hole riveting parts in industrial production due to the large number of rivets, small gap between rivets and rivet holes, and irregular rivet distribution, resulting in complex assembly process constraints, high assembly accuracy requirements, and difficulty in realizing intelligent riveting process to improve assembly efficiency, a visual servo accurate assembly method of riveting parts based on adaptive extended Kalman filter is proposed. In order to realize the high-precision positioning of riveted parts assembly, on the basis of the traditional extended Kalman filtering, an adaptive noise estimator is introduced to eliminate the influence of …

Research And Realization Of Immersive Skeleton Simulation System, Zining Wang, Shijiang Luo, Weiya Chen, Hanbin Luo

Journal of System Simulation

Abstract: Skeleton, as one of the sliding sports in Winter Olympic Games, has the characteristics of high speed, complexity and danger. In order to reduce the risk of accidents during sliding, a series of immersive skeleton simulation system is constructed utilizing virtual reality. Based on the point cloud data obtained by laser scanning, the existing track is modeled to build a virtual track stadium and skeleton sliding model in Unreal Engine 4. The data collected by motion capture devices is employed to estimate the centroid of the person and enable glide control input. The simulated skeleton posture is captured and …

Global Selection And Local Differentiation Fusion For Vehicle Re-Identification, Shengjun Xu, Mengqian Zhang, Bohan Zhan, Guanghui Liu, Yuebo Meng

Journal of System Simulation

Abstract: To address the interference issues of different perspectives, complex backgrounds, and lighting intensity in vehicle re-identification caused by cross lens multi view differences, a vehicle reidentification network integrating global selection and local differentiation is proposed. Based on Resnet50 backbone network, a three-branch complementary network integrating global and local features is designed. The global branch is used to learn overall appearance information of the vehicle, while the local branch captures differential details of the vehicle. Based on attention mechanism, a context feature selection module (CFSM) is proposed to effectively separate vehicle information from complex background information, and a detail feature …

Vehicle Routing Problem With Drones Considering Zoned Distribution Of Epidemic Prevention Materials, Huawei Ma, Boying Yan

Journal of System Simulation

Abstract: To address the shortcomings of current contactless delivery methods in the collaborative distribution of epidemic prevention supplies, we introduce a specialized model called the vehicle routing problem with drones considering zoned distribution (VRPD-ZD). In order to solve the problem, a linear programming model is established with the shortest delivery time as the optimization objective, and a two-stage heuristic algorithm is proposed. The initial solution is generated by greedy algorithm in the first stage. In the second stage, we develop a Tabu search algorithm with genetic algorithm (TSGA) hybrid. This enhanced algorithm integrates a taboo list and employs advanced chromosome …

Research On Modeling And Simulation Of Collective Mechanical Props Performance Behavior, Lian He, Kexiang Huang, Dapeng Yan, Ruida Tang, Gangyi Ding

Journal of System Simulation

Abstract: In stage performances, the increasing number of mechanical props poses significant challenges to their control and design. Each creative modification requires a complete rehearsal, resulting in low efficiency and sensitivity to creative changes. To address these issues, a model for the collective performance behavior of mechanical props is proposed. It utilizes centroid growth and 3D linear interpolation to generate spatial states and optimizes them in the temporal dimension using gradient descent. Through the construction of 3D simulation experiments, the planning and optimization of collective mechanical prop performance behavior in the model are analyzed. Similarity evaluation is used to compare …

Novel Multi-Gait Strategy For Stable And Efficient Quadruped Robot Locomotion, Daoxun Zhang, Xieyuanli Chen, Zhengyu Zhong, Ming Xu, Zhiqiang Zheng, Huimin Lu

Journal of System Simulation

Abstract: Inspired by the natural gait transition mechanism of quadruped animals, a multi-gait motion strategy is proposed to realize the stable and efficient motion of quadruped robots on different terrains in response to the trade-off between motion energy efficiency and motion stability. The gait is defined based on the duty cycle parameters and phase bias to form the switching basis. Secondly, the affine transformation of gait parameters and the finite state machine are introduced to establish the switching sequence, which realizes the timely gait switching. The speed-gait mapping is designed based on the cost of transport (CoT) and the stability …

Design Of Robust Behavior Tree Control Architecture For Agents In Dynamic Task Environment, Qiwei Wang, Qi Zhang, Shuo Yang, Yong Peng

Journal of System Simulation

Abstract: In recent years, the environment in which agents perform tasks has become more open and dynamic, which puts forward higher requirements for the robustness of task planning and behavior scheduling of agents. As a classic behavior control architecture, behavior tree has the characteristics of modularity, behavior parameterization, and structure of both plan representation and reaction, which can effectively support the behavior representation, decision making and scheduling of agents. Based on the hybrid behavior strategy , this paper proposes a robust behavior tree control architecture for dynamic task environment to realize the prudent decision-making and reactive control of agents. The …

Decision Modeling And Solution Based On Game Adversarial Complex Systems, Jiachen Jiang, Zhengxuan Jia, Zhao Xu, Tingyu Lin, Pengpeng Zhao, Yiming Ou

Journal of System Simulation

Abstract: In view of the complex situation of the current game which will be large-scale, high-intensity, not omniscient, and strong confrontation, and in response to the lack of flexibility and long iteration cycles in traditional game decision-making, the model of the unmanned complex game system is built according to the background of the unmanned red and blue game. Based on deep reinforcement learning technology, intelligent decision-making algorithms are studied in the background of unmanned red and blue games. With the help of deep neural networks and Bellman's optimal principle, the search of the huge solution space is more efficient, and …

Cooperative Control Method Of Mixed Traffic At Signalized Intersection, Qiushi Huang, Yanyang Wang, Changliang Wu, Junfu Huang, Shenggen Zhang, Haoxuan Luo

Journal of System Simulation

Abstract: A hierarchical decoupling cooperative control method for signal light mixed traffic platoon is designed with the goal of improving the traffic environment at signalized intersections. In the research of upper layer signal control, a calculation model for vehicle delay time at intersections is selected, with the goal of minimizing the average delay time of vehicles. A genetic algorithm based upper layer control strategy for intersection signal lights is proposed and verified; in the research of lower layer mixed platoon control, a "1+N" form is used to establish a dynamic model of the mixed platoon. A vehicle energy consumption model …

Driverless Vehicles Distribution Problem In Communities In Cooperation Of Storage Points, Xiaolong Diao

Journal of System Simulation

Abstract: With the development of smart communities, the distribution of driverless vehicles in communities has become a focus of government, operators and researchers. The joint cooperation of storage points in communities is designed to balance the the distribution of each storage point and avoid the high input cost of driverless vehicles, which means that driverless vehicles can travel between different storage points. The driverless vehicle distribution problem proposed in this paper includes the unloading subproblem and the driverless vehicle scheduling subproblem. For the unloading subproblem, the unloading scheme of vehicles at storage points is optimized with the aim of minimizing …

Multi-Uav Deployment And Collaborative Offloading For Large-Scale Iot Systems, Zhiqin Huang, Tianying Lu, Zheyi Chen

Journal of System Simulation

Abstract: In large-scale internet-of-things (IoT) systems, unmanned aerial vehicles (UAV) enabled mobile edge computing (MEC) can alleviate the performance constraints on end IoT devices. However, due to the uneven distribution of IoT devices and inefficient problem-solving, how to efficiently perform computation offloading in large-scale IoT systems is a major challenge. Existing solutions generally cannot fit into dynamic multi-UAV scenarios, causing inefficient resource utilization and excessive response delay. To address these important challenges, this paper proposes a novel multi-UAV deployment and collaborative offloading (MUCO) method for large-scale IoT systems. A UAV deployment scheme based on constrained K-Means clustering is designed to …