Multi-Agent Path Planning With Obstacle Penalty Factor,
2024
Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
Multi-Agent Path Planning With Obstacle Penalty Factor, Xingyu Yan, Dayan Li, Niya Wang, Kaixiang Zhang, Jianlin Mao
Journal of System Simulation
Abstract: In light load environments, complex obstacle areas will exacerbate local conflicts between agents, leading to a decrease in path solving efficiency. This paper proposes a multi-agent path planning (MAPF) method with obstacle penalty factors in light load environments. First, in the low-level single machine planning process based on the conflict-based search (CBS) algorithm framework, by judging the distribution type of surrounding obstacles that are about to expand the agent's position, corresponding obstacle penalty factors are assigned to them; then, the penalty factors in the path planning process are accumulated and used as the heuristic value of single machine planning …
Research On Optimization Design Method Of Waverider Forebody/Bump Profile Of Aircraft,
2024
School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621000, China
Research On Optimization Design Method Of Waverider Forebody/Bump Profile Of Aircraft, Jialin Qiu, Jun Huang, Peng Shu, Qingfeng Wang, Zhiqin Liu, Wenyou Qiao
Journal of System Simulation
Abstract: The waverider forebody and Bump profile of aircraft are two classic cases reflecting the waverider idea in aircraft component design. They can effectively improve the overall aerodynamic performance of aircraft and have become the core technology of aircraft overall design. In order to seek the optimal design of the waverider forebody and Bump profile to improve the efficiency of aircraft design, an optimization design method for the waverider forebody and Bump profile is proposed in this paper. The initial waverider forebody and Bump profile are generated by the osculating cone theory and conical flow field, and the aerodynamic performance …
Research On Hybrid Solution Algorithm For Layout Problem Of Rectangular Parts With Multiple Constraints,
2024
School of Mechanical Engineering, Jiangnan University, Wuxi 214122, China
Research On Hybrid Solution Algorithm For Layout Problem Of Rectangular Parts With Multiple Constraints, Ye Liu, Weixi Ji, Xuan Su, Hongxuan Zhao
Journal of System Simulation
Abstract: A hybrid algorithm based on a cutting and matching algorithm and an improved ant colony algorithm was proposed to solve the layout problem of rectangular parts in the process of wood and glass blanking. A layout optimization model was established to maximize the mean square utilization and the remaining processing time; the ant colony algorithm was used as the layout sequence algorithm to determine the layout sequence of some parts and meet the processing time constraint. In order to improve the search efficiency of the ant colony algorithm, an adaptive pheromone updating strategy was proposed, and a hybrid mutation …
Human Action Recognition Based On Skeleton Edge Information Under Projection Subspace,
2024
School of Computer and Information, Anqing Normal University, Anqing 246133, China; School of Mathematics and Computer,Tongling University, Tongling 244061, China
Human Action Recognition Based On Skeleton Edge Information Under Projection Subspace, Benyue Su, Peng Zhang, Bangguo Zhu, Mengjuan Guo, Min Sheng
Journal of System Simulation
Abstract: In recent years, human action recognition based on skeleton data has received a lot of attention in the fields of computer vision and human-computer interaction. Most of the existing methods focus on modeling the skeleton points in the original 3D coordinate space. However, skeleton points ignore the physical chain structure of the human body itself, which makes it difficult to portray the local correlation of human motion. In addition, due to the diversity of camera views, it is difficult to explore the comprehensive representation of actions in different views under the original point-based 3D space. In view of this, …
Joint Distribution-Inventory Optimization And Simulation For Cold Chain Logistics Considering Order Substitution,
2024
Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China
Joint Distribution-Inventory Optimization And Simulation For Cold Chain Logistics Considering Order Substitution, Yuanpeng Wan, Chengji Liang, Sihong Wang, Yu Wang
Journal of System Simulation
Abstract: The most important purpose of cold chain logistics is to ensure product freshness, and how to reduce the cost of order distribution on this basis is an urgent problem for cold chain companies. For consumers, product quality and food safety are their main needs. Therefore, by taking the distribution center as the research object, the products were divided into different grades according to the initial freshness of the products before distribution, and the overall freshness of the products was improved by adopting the grade upward substitution mode for orders that do not meet the delivery requirements so that customers …
Three-Dimensional Path Planning Of Uav Based On All Particles Driving Wild Horse Optimizer Algorithm,
2024
College of Mechatronics Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210000, China
Three-Dimensional Path Planning Of Uav Based On All Particles Driving Wild Horse Optimizer Algorithm, Gaoyang Li, Xiangfeng Li, Kang Zhao, Yuchao Jin, Zhidong Yi, Dunwen Zuo
Journal of System Simulation
Abstract: In view of large calculation amounts and difficult convergence in the unmanned aerial vehicle (UAV) path planning, a path planning method based on all particles driving wild horse optimizier (APDWHO) was proposed. A three-dimensional environment model and path cost model were established, by which the path planning problem was transformed into a multi-dimensional function optimization problem. An adaptive neighborhood search strategy (ANSS) was adopted to improve the exploitation ability of the algorithm. The Gaussian random walk strategy was used to search the historical optimal position of the individual to improve the exploration ability of the algorithm. Since the ANSS …
3d Streamline Visualization Method Based On Clustering Fusion,
2024
Department of Computer Science, North China Electric Power University, Baoding 071003, China; Engineering Research Center of Intelligent Computing for Complex Energy Systems, Baoding 071003, China
3d Streamline Visualization Method Based On Clustering Fusion, Xuqiang Shao, Ya Cheng, Yizhong Jin
Journal of System Simulation
Abstract: In order to solve the problems of incomplete feature extraction, continuity destruction of flow field by visual results, and poor representation of streamline caused by unstable clustering division when the clustering method is used to realize 3D streamline visualization. A 3D streamline visualization method based on clustering fusion is proposed. It consists of a distance measurement method between features and a clustering fusion method, which takes the inter-feature distance and spatial distance as the similarity between streamlines for clustering and then performs weighted merging and subdivision of the obtained clustering result. The method has been tested on data sets …
Planning Modeling And Optimization Algorithm For 5g Indoor Distribution System,
2024
School of Mathematics and Statistics, Guangdong University of Technology, Guangzhou 510520, China
Planning Modeling And Optimization Algorithm For 5g Indoor Distribution System, Shaoda Zeng, Hailin Liu
Journal of System Simulation
Abstract: Most of the new services in 5G mobile communication technologies, including smart homes, smart factories, and virtual reality, take place in indoor scenes. Therefore, how to quickly plan and build a 5G indoor distribution system with low construction cost and low power loss is of great significance for telecom operators. This paper establishes a mathematical planning model of a 5G indoor distribution system, which is closer to the actual scenario. The model aims to minimize the deployment cost and the maximum output signal power deviation between antennas, and the constraint is to meet the expected output signal power of …
Simulation And Optimization Of Permanent Magnet Linear Machine Based On Deep Neural Network,
2024
Engineering Technology Center, Southwest University of Science and Technology, Mianyang 621010, China
Simulation And Optimization Of Permanent Magnet Linear Machine Based On Deep Neural Network, Yan Shiliang, Yinling Wang, Dandan Lu, Xiaoqin Pan
Journal of System Simulation
Abstract: The finite element model (FEM) of permanent magnet linear synchronous machines (PMLSMs) takes a long computing time and cannot directly display the relationship between structural parameters and output thrust, thus failing to guide the structural parameter optimization of the machine. An improved simulation model of PMLSMs based on the subdomain analytical method and deep neural network (DNN) algorithm is proposed. The magnetic flux density, no-load counter electromotive force (EMF), and other data are obtained according to Maxwell's equations. The nonlinear relationship between the structural parameters of the machine and output thrust is fitted by the DNN algorithm. Based on …
Formation Strategy Of Hybrid Obstacle Avoidance Algorithm For Multiple Mobile Robots,
2024
College of Software, Shenyang University of Technology, Shenyang 110870, China; Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
Formation Strategy Of Hybrid Obstacle Avoidance Algorithm For Multiple Mobile Robots, Fulin Liu, Qingxin Li
Journal of System Simulation
Abstract: For the obstacle avoidance problem of multiple mobile robots in the unknown static obstacle environment, this paper proposed a formation strategy of a hybrid obstacle avoidance algorithm for multiple mobile robots, ensuring that multiple mobile robots do not collide during operation, can maintain the formation to the maximum extent in the unknown static obstacle environment for effective obstacle avoidance, and can reach the designated target point in a short time. Based on the leaderfollower method and artificial potential field (APF) method, the formation strategy divided the robots in the system into the leader robot and the follower robot. According …
Research On Hybrid Experimental Scheme Design For Combat Simulation,
2024
School of Software Engineering, South China University of Technology, Guangzhou 510006, China
Research On Hybrid Experimental Scheme Design For Combat Simulation, Fei Liu, Peng Lai, Yingbo Lu, Min Wang, Zhifeng Lu
Journal of System Simulation
Abstract: Combat simulation experimental design refers to sampling the values of experimental factors based on baseline combat scenarios using various experimental design methods and then generating a set of experimental schemes for the sequential simulation. The complexity of combat simulation, such as numerous experimental factors and distinct factor types, including continuous and discrete numeric types, poses several challenges and requires efficient hybrid experimental design methods. To address these issues, this paper conducts a study on the hybrid experimental scheme design for combat simulation. This paper gives a brief classification and review of experimental design methods and presents three hybrid experimental …
Intelligent Optimization Of Coal Terminal Unloading Scheduling Based On Improved D3qn Algorithm,
2024
Guoneng (Tianjin) Port Co. , Ltd, Tianjin 300450, China
Intelligent Optimization Of Coal Terminal Unloading Scheduling Based On Improved D3qn Algorithm, Baoxin Qin, Yuxiao Zhang, Sirui Wu, Weichong Cao, Zhan Li
Journal of System Simulation
Abstract: Intelligent decision scheduling can improve the operation efficiency of large ports, which is one of the important research directions for the implementation of artificial intelligence technology in the smart port scenario. This article studies the intelligent unloading scheduling tasks of coal terminals and abstracts them as a Markov sequence decision problem. A deep reinforcement learning model for this problem is established, and an improved D3QN algorithm is proposed to realize intelligent optimization of unloading scheduling decisions by considering the characteristics of high action space dimension and sparse feasible action in the model. The simulation results show that for the …
Path Planning For Improvement Of A* Algorithm And Artificial Potential Field Method,
2024
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Path Planning For Improvement Of A* Algorithm And Artificial Potential Field Method, Xiang Yu, Chen Jiang, Sirui Duan, Qianrui Deng
Journal of System Simulation
Abstract: A* algorithm has the problem of too many polyline paths and search nodes, while the artificial potential field (APF) method has the problems of local optimality and unattainability. These problems are investigated in this paper. A new hybrid heuristic function is proposed based on the Euclidean distance and projection distance, based on which the A* algorithm process is improved accordingly. The search nodes of the A* algorithm are reduced, and the search efficiency is improved. The optimal node generated by the new A* algorithm is used as the local target point of the APF algorithm to assist in getting …
Effectiveness Evaluation Of Heterogeneous Uav Swarms Based On A Hybrid Model,
2024
Shenyang Aircraft Design Institute, AVIC, Shenyang 110035, China
Effectiveness Evaluation Of Heterogeneous Uav Swarms Based On A Hybrid Model, Yuanjie Lu, Shanshan Long, Hang Zhao, Guoxu Feng, Xiaojia Zhao
Journal of System Simulation
Abstract: This paper presents a hybrid model based on availability dependability capability (ADC) system performance evaluation and back propagation (BP) neural network prediction to realize a rapid performance evaluation of UAV swarms and cope with the diversity of UAV swarm configuration and state and the complexity of performance calculation. By analyzing the components of swarm performance, a capability index system including the general platform capability, system-level capability, and task execution capability of UAVs is established. By using the ADC method, a swarm combat performance sample set is generated, and the BP neural network is used to construct a comprehensive combat …
Construction Of Surrogate Model Driven By Model And Data,
2024
Joint Logistics College, National Defense University, Beijing 100858, China; Graduate School, National Defense University, Beijing 100091, China; Joint Operations College, National Defense University, Beijing 100091, China
Construction Of Surrogate Model Driven By Model And Data, Jing An, Guangya Si, Miaoting Zeng
Journal of System Simulation
Abstract: By taking the three-dimensional projection action in a certain combat style as the research object, a surrogate model construction method driven by model and data is proposed to support the operational action research, so as to solve the problem that the calculation factors are too much during simulated deduction; the calculation resource cost is too large, and the calculation accuracy of the general analytical model is insufficient. Firstly, an analytical model group of three-dimensional projections with coefficients to be optimized is constructed based on military theory, including weapons and equipment, forces, etc. In addition, the composition and parameter setting …
Spectralomics – Towards A Holistic Adaptation Of Label Free Spectroscopy,
2024
Technological University Dublin
Spectralomics – Towards A Holistic Adaptation Of Label Free Spectroscopy, Hugh Byrne
Articles
Vibrational spectroscopy, largely based on infrared absorption and Raman scattering techniques, is much vaunted as a label free approach, delivering a high content, holistic characterisation of a sample, with demonstrable applications in a broad range of fields, from process analytical technologies and preclinical drug screening, to disease diagnostics, therapeutics, prognostics and personalised medicine. However, in the analysis of such complex systems, a trend has emerged in which spectral analysis is reduced to the identification of individual peaks, based on reference tables of assignments derived from literature, which are then interpreted as biomarkers. More sophisticated analysis attempts to unmix the spectrum …
Weakly Supervised Attention-Based Recognition Under Spectral, Turbulence, And Resource Variations,
2024
University of Nebraska-Lincoln
Weakly Supervised Attention-Based Recognition Under Spectral, Turbulence, And Resource Variations, Kshitij Naresh Nikhal
Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–
While supervised optimization paradigms are ubiquitous across diverse recognition systems, the risk of over-fitting and increasing bias have limited their applicability.
This dissertation focuses on unsupervised learning—learning without precisely curated data—and argues that unsupervised learning methods can enable both discriminability and generalizability. Through the use of attention-based machine learning and advanced clustering, unsupervised methods are able to focus on fine-grained information in images without any explicit supervision. The dissertation introduces a domain-bridging framework for tasks like cross-spectrum matching and long-range recognition, utilizing intra-domain clustering and inter-domain matching to generate pseudo-labels. Additionally, a hash-based network is proposed to accelerate the search …
Math Word Problem Generation Via Disentangled Memory Retrieval,
2024
Singapore Management University
Math Word Problem Generation Via Disentangled Memory Retrieval, Wei Qin, Xiaowei Wang, Zhenzhen Hu, Lei Wang, Yunshi Lan, Richang Hong
Research Collection Lee Kong Chian School Of Business
The task of math word problem (MWP) generation, which generates an MWP given an equation and relevant topic words, has increasingly attracted researchers’ attention. In this work, we introduce a simple memory retrieval module to search related training MWPs, which are used to augment the generation. To retrieve more relevant training data, we also propose a disentangled memory retrieval module based on the simple memory retrieval module. To this end, we first disentangle the training MWPs into logical description and scenario description and then record them in respective memory modules. Later, we use the given equation and topic words as …
Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach,
2024
Baylor University
Understanding The Impact Of Trade Policy Effect Uncertainty On Firm-Level Innovation Investment: A Deep Learning Approach, Daniel Chang, Nan Hu, Peng Liang, Morgan Swink
Research Collection School Of Computing and Information Systems
Integrating the real options perspective and resource dependence theory, this study examines how firms adjust their innovation investments to trade policy effect uncertainty (TPEU), a less studied type of firm specific, perceived environmental uncertainty in which managers have difficulty predicting how potential policy changes will affect business operations. To develop a text-based, context-dependent, time-varying measure of firm-level perceived TPEU, we apply Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art deep learning approach. We apply BERT to analyze the texts of mandatory Management Discussion and Analysis (MD&A) sections of annual reports for a sample of 22,669 firm-year observations from 3,181 unique …
Improvement Of Flow Coefficient Estimation With Limited Well Test Data For Real-Time Condition Analytics Of Choke Valve,
2024
Singapore Management University
Improvement Of Flow Coefficient Estimation With Limited Well Test Data For Real-Time Condition Analytics Of Choke Valve, T. Visawameteekul, Tin Seong Kam, P. Thamvechvitee
Research Collection School Of Computing and Information Systems
The study discusses a method for monitoring the internal condition of choke valves to predict sand erosion using flow coefficient (Cv). The method calculates the Cv of the choke valve by utilizing eight parameters and compares it to the newly manufactured value to generate warnings. However, the availability of spot-check well test data can significantly impact the model's efficiency if tests are performed infrequently. To address this issue, the Extended Cv monitoring method is proposed in this paper. The main purpose of this study is to develop a model for estimating Cv value in the absence of well test data. …
