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Articles 301 - 330 of 57778
Full-Text Articles in Physical Sciences and Mathematics
Unveiling The Dynamics Of Ai Applications: A Review Of Reviews Using Scientometrics And Bertopic Modeling, Raghu Raman, Debidutta Pattnaik, Laurie Hughes, Prema Nedungadi
Unveiling The Dynamics Of Ai Applications: A Review Of Reviews Using Scientometrics And Bertopic Modeling, Raghu Raman, Debidutta Pattnaik, Laurie Hughes, Prema Nedungadi
Research outputs 2022 to 2026
In a world that has rapidly transformed through the advent of artificial intelligence (AI), our systematic review, guided by the PRISMA protocol, investigates a decade of AI research, revealing insights into its evolution and impact. Our study, examining 3,767 articles, has drawn considerable attention, as evidenced by an impressive 63,577 citations, underscoring the scholarly community's profound engagement. Our study reveals a collaborative landscape with 18,189 contributing authors, reflecting a robust network of researchers advancing AI and machine learning applications. Review categories focus on systematic reviews and bibliometric analyses, indicating an increasing emphasis on comprehensive literature synthesis and quantitative analysis. The …
Water Body Satellite Images Segmentation Using Maxwell Boltzmann Distribution, Lama Affara, Ali El-Zaart, Rabih Damaj
Water Body Satellite Images Segmentation Using Maxwell Boltzmann Distribution, Lama Affara, Ali El-Zaart, Rabih Damaj
BAU Journal - Science and Technology
Images can exhibit diverse attributes and characteristics, because of variations in both the quantity of each intensity level and their respective positions, histograms display varying distributions. Some images feature symmetric histograms, while others exhibit asymmetry. In image segmentation tasks, traditional mean-based thresholding methods work well with symmetric histograms, relying on Gaussian distribution definitions. However, situations arise where asymmetric distributions must be considered. Threshold-based segmentation entails the partitioning of intensity levels into separate regions determined by the threshold value. Within this category of thresholding methods, Minimum Cross Entropy Thresholding (MCET) stands out as a mean-based thresholding technique with a unique self-contained …
Containerization On A Self-Supervised Active Foveated Approach To Computer Vision, Dario Dematties, Silvio Rizzi, George K. Thiruvathukal
Containerization On A Self-Supervised Active Foveated Approach To Computer Vision, Dario Dematties, Silvio Rizzi, George K. Thiruvathukal
Computer Science: Faculty Publications and Other Works
Scaling complexity and appropriate data sets availability for training current Computer Vision (CV) applications poses major challenges. We tackle these challenges finding inspiration in biology and introducing a Self-supervised (SS) active foveated approach for CV. In this paper we present our solution to achieve portability and reproducibility by means of containerization utilizing Singularity. We also show the parallelization scheme used to run our models on ThetaGPU–an Argonne Leadership Computing Facility (ALCF) machine of 24 NVIDIA DGX A100 nodes. We describe how to use mpi4py to provide DistributedDataParallel (DDP) with all the needed information about world size as well as global …
Enhancing Tumor Classification Through Machine Learning Algorithms For Breast Cancer Diagnosis, Lawrence Agbota, Edmund Agyemang, Priscilla Kissi-Appiah, Lateef Moshood, Akua Osei- Nkwantabisa, Vincent Agbenyeavu, Abraham Nsiah, Augustina Adjei
Enhancing Tumor Classification Through Machine Learning Algorithms For Breast Cancer Diagnosis, Lawrence Agbota, Edmund Agyemang, Priscilla Kissi-Appiah, Lateef Moshood, Akua Osei- Nkwantabisa, Vincent Agbenyeavu, Abraham Nsiah, Augustina Adjei
School of Mathematical and Statistical Sciences Faculty Publications and Presentations
In cancer diagnosis, machine learning helps improve cancer detection by providing doctors with a second perspective and allowing for faster and more accurate determination and decisions. Numerous studies have used both classic machine learning approaches and deep learning to address cancer classification. In this study, we examine the efficacy of five commonly used machine learning algorithms; both traditional and deep learning models namely, Logistic Regression, Support Vector Machines (SVM), Random Forest (RF), Decision Tree and Deep Neural Networks (DNN). We analyze their ability to properly classify tumors as Benign or Malignant using the Wisconsin breast cancer dataset (WBCD). Random Forest …
Ai Literacy Innovations: Chatgpt's Integration Into A First-Year Information Literacy Program, Taylor J. Greene, Douglas R. Dechow
Ai Literacy Innovations: Chatgpt's Integration Into A First-Year Information Literacy Program, Taylor J. Greene, Douglas R. Dechow
Library Presentations, Posters, and Audiovisual Materials
In the dynamic field of information technology, integration of Artificial Intelligence (AI) literacy into information literacy instruction is now essential to ensure the ethical and productive use of generative AI by our students. This poster demonstrates our innovative approach to embedding AI literacy within the first-year information literacy program at an R2 research university. We used a two-pronged strategy: an “AI Literacy” section in Canvas and practical demonstrations of applying ChatGPT in live library sessions. The Canvas module section equips students with foundational knowledge and critical thinking about using generative AI for research and learning activities. It covers AI fundamentals, …
Hierarchical Quantized Autoencoders: Using Hierarchical Models For Data Compression Across Multiple Domains, Armani Lorenzo Rodriguez
Hierarchical Quantized Autoencoders: Using Hierarchical Models For Data Compression Across Multiple Domains, Armani Lorenzo Rodriguez
Theses and Dissertations
In the era of vast data processing and transmission, sending data over a channel for downstream operations is a very common occurrence. The bandwidth of this data channel acts as a limiting factor in this operation, capping the amount of data that can be sent over a time period. Therefore, in addition to pursuing advancements in networking technology, there exists a need for more efficient means of data compression. Learned compression is the application of machine learning models to the data compression problem, and in this study, we leverage the ability of neural networks to learn the underlying structure of …
Hyper-Dimensional Computing And Its Applications In Tinyml, Ellis A. Weglewski
Hyper-Dimensional Computing And Its Applications In Tinyml, Ellis A. Weglewski
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
As computing systems enter the realm of nano form levels, new fields of computational development have spawned, each posing their own set of challenges. Amongst these fields is Tiny Machine Learning (tinyML), which aims to install machine learning on tiny embedded systems. The restrictions imposed upon algorithms by the limited hardware of nano-scale tiny systems make contemporary approaches to machine learning non-contenders. Hyperdimensional computing is an approach to representing data as high-dimensional vectors which allows for one-pass encoding and quick all-encompassing comparison operations via an associative memory. This approach is power-efficient, robust, and can be done in-memory, all of which …
Enhancing Evolutionary Computation Through Phylogenetic Analysis, Chenfei Peng
Enhancing Evolutionary Computation Through Phylogenetic Analysis, Chenfei Peng
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
In this paper, we will provide an overview of the paper “Phylogeny-informed fitness estimation for test-based parent selection” by Lalejini, et al. [7] Phylogenies, or ancestry trees, provide a detailed look into the evolutionary journey of a population. In evolutionary computation, a phylogeny can represent the progress of an evolutionary algorithm through a search space. Although phylogenetic analysis is mainly used to deepen the understanding of evolutionary algorithms after they have been run, this study explores its potential use in real-time to enhance parent selection during evolutionary searches. The research by Lalejini, et al. introduces the concept of phylogeny-informed fitness …
Research On Operational Protection Area Of Ils Glide Slope, Qingdong Li, Jiaquan Ye, Jian Xu
Research On Operational Protection Area Of Ils Glide Slope, Qingdong Li, Jiaquan Ye, Jian Xu
Journal of System Simulation
Abstract: The scientific protection for the operational protection area of the instrument landing system glide slope is of great significance to ensure the quality of civil aviation navigation space signals, the safety of aircraft approach operations, and the efficiency of airport operations. Combined with the concept evolution of the glide slope operational protection area, a comparative analysis of the delineation of the glide slope operational protection area required by the national civil aviation standards, industry standards, and Annex 10 Volume I of the Convention on International Civil Aviation is carried out. Taking the extra-large aircraft (A380-800) as an example, the …
Thinking Of Aerospace Equipment Systematization Simulation Technology Development, Weimin Bao, Zhenqiang Qi
Thinking Of Aerospace Equipment Systematization Simulation Technology Development, Weimin Bao, Zhenqiang Qi
Journal of System Simulation
Abstract: The aerospace field is flourishing in the new era. Aerospace equipment presents new characteristics such as systematization, new quality, high efficiency and intelligence. Simulation technology plays a more important role in the digital aerospace era as a means of enhancing efficiency and empowerment covering all stages of the entire lifecycle, including project demonstration, research and development, testing, manufacturing, training, and maintenance. The conception of aerospace equipment systematization simulation technology is introduced, the current development status and practices at home and abroad are elaborated, and the future development trends and challenges of aerospace equipment systematization simulation technology are evaluated. Focusing …
Air Defense Missile Weapon Target Assignment Based On Multi-Objective Evolutionary Algorithm, Xin Sun, Lining Xing, Rui Wang, Ling Wang, Jianmai Shi, Tianyu Luo
Air Defense Missile Weapon Target Assignment Based On Multi-Objective Evolutionary Algorithm, Xin Sun, Lining Xing, Rui Wang, Ling Wang, Jianmai Shi, Tianyu Luo
Journal of System Simulation
Abstract: An effective weapon target assignment method can reduce the combat losses and improve the defense effect. A reasonable mathematical model is established for the allocation of air defense resources, aiming at the optimization objectives of maximizing target destruction effectiveness and minimizing radar resource consumption, considering multiple constraints such as the upper limit of radar channels, on the basis of multiobjective evolutionary algorithm based on decomposition (MOEA/D), the probability of crossover and mutation is adaptively adjusted to improve the quality of individuals in the process of population evolution, and a set of optimal solution sets for decision makers is obtained. …
Arterial Coordination Optimization Method Based On Vehicle Speed Guidance And Inductive Control, Mingjun Deng, Xinxia Hu, Xiang Li, Liping Xu
Arterial Coordination Optimization Method Based On Vehicle Speed Guidance And Inductive Control, Mingjun Deng, Xinxia Hu, Xiang Li, Liping Xu
Journal of System Simulation
Abstract: Arterial signal coordination is usually based on fixed belt speeds and time-of-day statistical flows. Actually, vehicle speeds and traffic flows are fluctuating, which causes to the mismatch between the signal scheme and the actual optimal belt speeds and traffic flow demands, and affects the intersection's traffic efficiency. Based on the vehicle infrastructure cooperation, by applying Maxband model and the maximum green wave bandwidth, the minimum number of arterial vehicle delays, arterial stops and the minor direction delays being the optimization objectives, a multi-objective optimization model for arterial signal coordination is established. Through using an improved multi-objective particle swarm algorithm …
Simulation Of Rice Disease Recognition Based On Improved Attention Mechanism Embedded In Pr-Net Model, Yang Lu, Pengfei Liu, Siyuan Xu, Qiwang Liu, Fuqian Gu, Peng Wang
Simulation Of Rice Disease Recognition Based On Improved Attention Mechanism Embedded In Pr-Net Model, Yang Lu, Pengfei Liu, Siyuan Xu, Qiwang Liu, Fuqian Gu, Peng Wang
Journal of System Simulation
Abstract: Aiming at the low accuracy of existing CNN models in identifying rice leaf diseases, a hybrid convolutional neural network model PRC-Net (parallel residual with coordinate attention network) combining parallel structure and residual structure is proposed. A parallel structure is introduced to improve the receptive field of convolution, and the residual structure is combined to achieve the complete and continuous transmission of feature information. An improved spatial attention mechanism is embedded into the backbone model PR-Net to enhance the degree of aggregation of lesion feature information at different scales. In order to further improve the accuracy of disease identification and …
Unsupervised Complex Condition Recognition Based On Stochastic Neighborhood Embedding, Lin Huang, Shanjun Liu, Wei Wang, Li Gong
Unsupervised Complex Condition Recognition Based On Stochastic Neighborhood Embedding, Lin Huang, Shanjun Liu, Wei Wang, Li Gong
Journal of System Simulation
Abstract: Modern industrial production equipment usually has a complex structure and runs alternately in different working conditions. Accurate working conditions identification based on monitoring data is the basis of health monitoring of the system, but the monitoring data of the system usually has a high dimension and a large data volume. To identify the complex equipment operating conditions, an unsupervised operating condition identification method based on stochastic neighborhood embedding is proposed. The stochastic neighborhood embedding algorithm can simultaneously preserve the local and global structural characteristics of the data, and also calculate the probability similarity of data points in high-dimensional and …
Hybrid Flow Shop Scheduling With Limited Buffers Considering Energy Consumption And Transportation, Tingxin Wen, Tingyu Guan
Hybrid Flow Shop Scheduling With Limited Buffers Considering Energy Consumption And Transportation, Tingxin Wen, Tingyu Guan
Journal of System Simulation
Abstract: Aiming at the untimely production scheduling and excessive energy consumption during processing, a limited buffer hybrid flow shop scheduling optimization model is constructed. To minimize the makespan and total energy consumption of the workshop, the transport time, generalized energy consumption and buffer capacity being the constraints, and the on/off energy saving strategy applied to reduce the standby energy consumption, the feasibility of the optimization model are verified. A lion swarm optimization algorithm is designed, in which a population initialization method combining random generation and greedy selection is used to improve the initial solution quality and solution efficiency, the lion …
Application Of Driving Simulation Technology In Calibration Of Traffic Simulation Parameters, Shikun Liu, Yi Tang, Yonghong Liu
Application Of Driving Simulation Technology In Calibration Of Traffic Simulation Parameters, Shikun Liu, Yi Tang, Yonghong Liu
Journal of System Simulation
Abstract: To address the insufficient accuracy in traffic simulation modeling due to the lack of in-depth consideration of complex driving behaviors, a calibration method for traffic simulation parameters based on driving simulation technology is proposed. The reconstruction and expansion project of Shenzhen Bao'an International Airport Expressway is selected as the case. Using VISSIM simulation software, a comprehensive traffic simulation model of the entire route is constructed, and UC-winRoad software is employed to create the highly realistic driving simulation scenarios. Driving simulation experiments are conducted to extract the typical driving behavior characteristics in complex scenarios. Calibration functions for simulation parameters are …
Optimal Trajectory Of Full-Duplex Uav Relaying Over Hybrid Probability Channels, Tao Wang, Ji Xiaodong
Optimal Trajectory Of Full-Duplex Uav Relaying Over Hybrid Probability Channels, Tao Wang, Ji Xiaodong
Journal of System Simulation
Abstract: A fixed-wing UAV being the full-duplex moving relay, and a hybrid probability channel being the source to send data to the destination, through the flight optimal trajectory design. On the basis of ensuring the total data amount of source-destination communication, the energy consumption of the system is minimized. Two optimization problems of runway shape and mixed trajectory are established, which are non-convex and are difficult to get the closed-form solution. The hybrid probability channels gains are replaced by the average channel gains, and the lower bounds of the received data at the UAV and the destination are calculated by …
Classification Cooperative Scheduling Of U-Automated Container Terminal Based On Container Markers, Fei Wang, Daofang Chang, Furong Wen
Classification Cooperative Scheduling Of U-Automated Container Terminal Based On Container Markers, Fei Wang, Daofang Chang, Furong Wen
Journal of System Simulation
Abstract: To improve the confusing scheduling of U-shaped yard operations due to improper classification of containers, the classification cooperative scheduling process is proposed, in which the classification cooperative scheduling model is established with the constraints of coordinated operation and efficient independent operation. The container classification principle and the container multiple stacking principle are proposed, the stacking point is selected by the weighted calculation based on the container operation mark to design the penalty mechanism, and the classification cooperative heuristic algorithm solution model is designed. Comparative experiments show that the strategy used in the algorithm is superior,which can reduce the equipment …
Simulation Of Robotic Peg-In-Hole Assembly Strategy Based On Drl, Zilu Zhu, Yongkui Liu, Lin Zhang, Lihui Wang, Tingyu Lin
Simulation Of Robotic Peg-In-Hole Assembly Strategy Based On Drl, Zilu Zhu, Yongkui Liu, Lin Zhang, Lihui Wang, Tingyu Lin
Journal of System Simulation
Abstract: Aiming at the existing peg-in-hole assembly method problems of dependence on accurate contact state models, difficulties in data acquisition, low sampling efficiency, and poor security, a simulation research method for robot peg-in-hole assembly strategy based on DRL is proposed. A simulation environment of robot peg-in-hole assembly based on ROS-Gazebo is built, and a method of gravity compensation for force/torque sensor based on a least square method is proposed. The reinforcement learning paradigm is employed to model the robot peg-in-hole assembly, and a method based on soft actor-critic(SAC) algorithm is proposed. The communication mechanism between the simulation environment and the …
Adaptive Pid Control Algorithm Based On Ppo, Zhiyong Zhou, Fei Mo, Kai Zhao, Yunbo Hao, Yufeng Qian
Adaptive Pid Control Algorithm Based On Ppo, Zhiyong Zhou, Fei Mo, Kai Zhao, Yunbo Hao, Yufeng Qian
Journal of System Simulation
Abstract: A six-axis robotic arm is built and simulated in a complex control environment with disturbances by using MATLAB physics engine and Python, which provides a trial-and-error environment for the robotic arm training that could not be provided in reality. Proximal policy optimization(PPO) algorithm in reinforcement learning is proposed to improve the traditional PID control algorithm. By introducing the multi-agent idea and on the basis of the different effects of the three parameters of PID on control system and the characteristics of the six-axis robotic arm, the three parameters are separately trained as different intelligent individuals to achieve a new …
Fusing Rotation Angle Coding In Spherical Space For Human Action Recognition, Benyue Su, Bangguo Zhu, Mengjuan Guo, Min Sheng
Fusing Rotation Angle Coding In Spherical Space For Human Action Recognition, Benyue Su, Bangguo Zhu, Mengjuan Guo, Min Sheng
Journal of System Simulation
Abstract: The existing human action recognition methods focus more on the translation information such as the coordinates and displacements of skeleton structure, and pay less attention to the motion trend of skeleton structure and the rotation information representing the motion direction of joints and bones. A spatio-temporal convolutional neural network method combining the rotation angle coding in spherical space is introduced. The angle information with scale invariance is obtained by mapping the human action in three-dimensional spherical space, and the dynamic angular velocity information is extracted as the angle code to represent the rotation information of joints and bones in …
Development And Application Of Simulation Platform For Aquatic Movement Of An Amphibious Armored Vehicle, Mingzhe Chen, Yunzheng Song, Pei Wang, Lei Zhang
Development And Application Of Simulation Platform For Aquatic Movement Of An Amphibious Armored Vehicle, Mingzhe Chen, Yunzheng Song, Pei Wang, Lei Zhang
Journal of System Simulation
Abstract: In order to design and verify the fire control system(FCS) algorithm of amphibious assault vehicle under heavy wind and wave conditions, a real-time simulation platform is developed. The traditional single rigid body dynamic model can't describe the body-turret-barrel dynamic coupling relationship and it is not suitable for FCS simulation with high dynamic characteristics. Twist-wrench method is used to establish the multiple rigid body dynamic model of vehicle, the buoyancy and the hydrodynamic calculation is carried out according to the body and the moving relationship between visual generated waves, and the hydrodynamic coefficient is obtained by the computational fluid dynamic …
Curriculum Learning-Based Simulation Of Uav Air Combat Under Sparse Rewards, Jingyu Zhu, Hongli Zhang, Minchi Kuang, Heng Shi, Jihong Zhu, Zhi Qiao, Wenqing Zhou
Curriculum Learning-Based Simulation Of Uav Air Combat Under Sparse Rewards, Jingyu Zhu, Hongli Zhang, Minchi Kuang, Heng Shi, Jihong Zhu, Zhi Qiao, Wenqing Zhou
Journal of System Simulation
Abstract: To address the limited exploration capabilities and sparse rewards of conventional reinforcement learning methods in air combat environment, a curriculum learning distributed proximal policy optimization (CLDPPO) reinforcement learning algorithm is proposed. A reward function informed by professional empirical knowledge is integrated, a discrete action space is developed, and a global observation and local value and decision network featuring separated global and local observations is established. A methodology for unmanned aerial vehicles UAVs is presented to acquire combat expertise through a sequence of fundamental courses that progressively intensify in their offensive, defensive, and comprehensive content. The experimental results show that …
Design Of Real-Time Simulation & Test Software Based On Windows/Rtx, Yongbo Li, Runmei Tian, Hui Zhang, Shanpeng Guo, Qi Li
Design Of Real-Time Simulation & Test Software Based On Windows/Rtx, Yongbo Li, Runmei Tian, Hui Zhang, Shanpeng Guo, Qi Li
Journal of System Simulation
Abstract: Aiming at the limited real-time performance of traditional test software and the low generality of traditional simulation interface software, a real-time simulation software based on Windows/RTX is designed to meet the requirements of unit testing and control system simulation verification of semiphysical simulation software. Through modular design, GUI layer human-computer interface and RTX layer real-time operation program are developed. To ensure the real-time, the lock-free cyclic buffer plus dual-threading technology is used to solve the timeout problem of serial data transmission and reception when the simulation step size is 1 ms under RTX environment. A timeout detection algorithm is …
Cooperative Ant Colony Algorithm Combining Evaluation Reward And Punishment Mechanism And Neighborhood Dynamic Degradation, Yujie Wang, Xiaoming You, Sheng Liu
Cooperative Ant Colony Algorithm Combining Evaluation Reward And Punishment Mechanism And Neighborhood Dynamic Degradation, Yujie Wang, Xiaoming You, Sheng Liu
Journal of System Simulation
Abstract: To address the slow convergence and the tendency to fall into local optimality in solving TSP, a cooperative ant colony algorithm combining evaluation reward and punishment mechanism and neighborhood dynamic degradation (ENCACO) is proposed. The paths are classified into active and abandon paths according to the path evaluation value, and with the path evaluation value as the weight, the different pheromone reward and punishment strategies are adopted for the two types of paths to accelerate the convergence speed of the algorithm. Through the neighborhood dynamic degradation strategy, and the neighborhood radius is used to divide the set of cities …
Construction Of A Virtual Interactive System For Orchards Based On Digital Twin, Hongjun Wang, Junqiang Lin, Xiangjun Zou, Po Zhang, Mingxuan Zhou, Weirui Zou, Yunchao Tang, Lufeng Luo
Construction Of A Virtual Interactive System For Orchards Based On Digital Twin, Hongjun Wang, Junqiang Lin, Xiangjun Zou, Po Zhang, Mingxuan Zhou, Weirui Zou, Yunchao Tang, Lufeng Luo
Journal of System Simulation
Abstract: Aiming at the low visibility, poor real-time, weak adaptability and single interaction mode in orchard planting management system, a six-dimensional model of orchard digital twin system for planting management process is proposed. The system model construction theory and technology system is discussed from four aspects, entity modeling of management elements, dynamic modeling of management process, simulation modeling of management system and optimization modeling of management strategy. Based on the six-dimensional model, supported by the theory and technology system, the virtual interactive system architecture of the orchard based on the digital twin is designed, and the key technologies of the …
Dynamic Air Defense Resource Allocation Optimization Based On Improved Differential Evolution Algorithm, Tianyu Luo, Lining Xing, Rui Wang, Ling Wang, Jianmai Shi, Xin Sun
Dynamic Air Defense Resource Allocation Optimization Based On Improved Differential Evolution Algorithm, Tianyu Luo, Lining Xing, Rui Wang, Ling Wang, Jianmai Shi, Xin Sun
Journal of System Simulation
Abstract: Based on the integrated performance of weapon equipments such as radars, launchers and missiles, a mixed-integer decision model that minimizes the total target intercept value and the probability of survival based on Target-Set, Resource-Set is developed. A new improved differential evolutionary algorithm has been introduced to solve the problem, and the initial solutions is generated by using the reverse learning strategies to ensure the quality of the initial populations. An inspiration rule for the fast repair and reconstruction is designed to work at multi-stage to improve the search capability of the algorithm. The simulation experiment results show the algorithm's …
Just-In-Time Learning Energy Consumption Predictive Modeling Method In Multi-Condition Production Process, Sheng Wei, Yan Wang, Zhicheng Ji
Just-In-Time Learning Energy Consumption Predictive Modeling Method In Multi-Condition Production Process, Sheng Wei, Yan Wang, Zhicheng Ji
Journal of System Simulation
Abstract: Aiming at the problem that the global energy consumption prediction model is only suitable for part of the prediction sample and the model is computationally intensive, the idea of just-in-time learning is introduced, and the local weighted partial least squares method combined with the energy consumption model is used to establish a temporary local energy consumption prediction model. The inertia weights of the particle swarm algorithm are improved, considering the effects of particle fitness, number of iterations and population size on the convergence speed and convergence accuracy of the particle swarm algorithm, a nonlinear change adaptive inertia weight strategy …
Completion Time Simulation Prediction Method For Aircraft Assembly Process With Batch And Sortie, Changjian Jiang, Hu Fan, Tao Luo, Wen Yuan, Zehao He
Completion Time Simulation Prediction Method For Aircraft Assembly Process With Batch And Sortie, Changjian Jiang, Hu Fan, Tao Luo, Wen Yuan, Zehao He
Journal of System Simulation
Abstract: Aiming at the product differentiation analysis limitation of traditional discrete event simulation method, a simulation prediction method for aircraft assembly process with batch and sortie is proposed. Around the aircraft sortie number, the formal definition of various basic elements and interactions in the assembly process with batch and sortie is studied, and the construction of station and whole line simulation model is carried out. The simulation promotion framework and execution mechanism supporting the product differentiation analysis are studied. Based on the simulation results, a method for predicting the completion time of sorties based on interval estimation method is proposed. …