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Operations Research, Systems Engineering and Industrial Engineering Commons™

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2024

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Articles 451 - 480 of 670

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

A Distributed Simulation System For Space Operation Missions, Yunzhao Liu, Mingming Wang, Jintao Li, Chuankai Liu, Jianjun Luo Mar 2024

A Distributed Simulation System For Space Operation Missions, Yunzhao Liu, Mingming Wang, Jintao Li, Chuankai Liu, Jianjun Luo

Journal of System Simulation

Abstract: For the ground verification requirements of complex space operation missions such as noncooperative target capture, on-orbit maintenance, and in-space assembly, a distributed simulation system is developed, which mainly consists of a back-end simulation model, a front-end visual demonstration system, and a front-end main controller. In order to realize the multidisciplinary model coupling and interaction among different modeling tools or programming languages, the functional mock-up interface (FMI) standard is introduced for system integration, improving the modularity, generality, and portability of the system. To fully utilize computing resources and improve the simulation efficiency, simulation subsystems and modules are deployed in a …

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Joint Distribution-Inventory Optimization And Simulation For Cold Chain Logistics Considering Order Substitution, Yuanpeng Wan, Chengji Liang, Sihong Wang, Yu Wang Mar 2024

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 …

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Dynamic Digital Twin Modelling And Semi-Physical Simulation Of Wind Turbine Operation, Yang Hu, Weiran Wang, Fang Fang, Ziqiu Song, Yuhan Xu, Jizhen Liu Mar 2024

Dynamic Digital Twin Modelling And Semi-Physical Simulation Of Wind Turbine Operation, Yang Hu, Weiran Wang, Fang Fang, Ziqiu Song, Yuhan Xu, Jizhen Liu

Journal of System Simulation

Abstract: For the accurate mapping and real-time simulation requirements proposed by digital twin technology, a multi-input multi-output (MIMO) finite difference domain-hybrid semi-mechanical (FDDHSM) digital twin modeling method is proposed, and a semi-physical simulation system of wind turbine digital twin with physical controller is established for the complex nonlinear operation characteristics of large wind turbines. The integrated dynamic MIMO-FDD-HSM model structure is constructed. Finite difference regression vectors are defined to characterize the operating conditions of the wind turbine, and finite difference space tight convex partitioning, parametric model identification, and non-parametric model training are completed under full operating conditions. The wind turbine …

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Construction Of Surrogate Model Driven By Model And Data, Jing An, Guangya Si, Miaoting Zeng Mar 2024

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 …

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Effectiveness Evaluation Of Heterogeneous Uav Swarms Based On A Hybrid Model, Yuanjie Lu, Shanshan Long, Hang Zhao, Guoxu Feng, Xiaojia Zhao Mar 2024

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 …

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Hybrid Features Extraction For The Online Mineral Grades Determination In The Flotation Froth Using Deep Learning, Ahmed Bendaouia, El Hassan Abdelwahed, Sara Qassimi, Abdelmalek Boussetta, Intissar Benzakour, Abderrahmane Benhayoun, Oumkeltoum Amar, François Bourzeix, Karim Baïna, Mouhamed Cherkaoui, Oussama Hasidi Mar 2024

Hybrid Features Extraction For The Online Mineral Grades Determination In The Flotation Froth Using Deep Learning, Ahmed Bendaouia, El Hassan Abdelwahed, Sara Qassimi, Abdelmalek Boussetta, Intissar Benzakour, Abderrahmane Benhayoun, Oumkeltoum Amar, François Bourzeix, Karim Baïna, Mouhamed Cherkaoui, Oussama Hasidi

Manufacturing & Industrial Engineering Faculty Publications

The control of the froth flotation process in the mineral industry is a challenging task due to its multiple impacting parameters. Accurate and convenient examination of the concentrate grade is a crucial step in realizing effective and real-time control of the flotation process. The goal of this study is to employ image processing techniques and CNN-based features extraction combined with machine learning and deep learning to predict the elemental composition of minerals in the flotation froth. A real world dataset has been collected and preprocessed from a differential flotation circuit at the industrial flotation site based in Guemassa, Morocco. …

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T-Pickseer: Visual Analysis Of Taxi Pick-Up Point Selection Behavior, Shuxian Gu, Yemo Dai, Zezheng Feng, Yong Wang, Haipeng Zeng Mar 2024

T-Pickseer: Visual Analysis Of Taxi Pick-Up Point Selection Behavior, Shuxian Gu, Yemo Dai, Zezheng Feng, Yong Wang, Haipeng Zeng

Research Collection School Of Computing and Information Systems

Taxi drivers often take much time to navigate the streets to look for passengers, which leads to high vacancy rates and wasted resources. Empty taxi cruising remains a big concern for taxi companies. Analyzing the pick-up point selection behavior can solve this problem effectively, providing suggestions for taxi management and dispatch. Many studies have been devoted to analyzing and recommending hotspot regions of pick-up points, which can make it easier for drivers to pick-up passengers. However, the selection of pick-up points is complex and affected by multiple factors, such as convenience and traffic management. Most existing approaches cannot produce satisfactory …

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Laboratory Evaluation Of High-Temperature Resistant Lysine-Based Polymer Gel Systems For Leakage Control, Tao Song, Xuyang Tian, Baojun Bai, Yugandhara Eriyagama, Mohamed Ahdaya, Adel Alotibi, Thomas P. Schuman Mar 2024

Laboratory Evaluation Of High-Temperature Resistant Lysine-Based Polymer Gel Systems For Leakage Control, Tao Song, Xuyang Tian, Baojun Bai, Yugandhara Eriyagama, Mohamed Ahdaya, Adel Alotibi, Thomas P. Schuman

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

In-situ crosslinking gel known for its cost-effectiveness, has been employed for decades to plug high-permeability features in subsurface environments. However, some commonly used crosslinkers are being phased out due to the increasingly rigorous environmental regulations. As a newly discovered environmentally friendly crosslinker, lysine can crosslink the partially hydrolyzed polyacrylamide through transamidation reaction. The present work aimed to study the effect of polymer composition and concentration on the gelation behavior of lysine and high molecular weight acrylamide-based polymers. Several commercial high molecular weight polymers with different contents of 2-Acrylamido-2-methyl-1-propane sulfonic acid (AMPS) including AN-105/125, SAV-55/37/28, and SAV-10 were deployed in this …

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Enhancing Port Efficiency And Lead Time Reduction Through Predictive Analysis: A Case Study Of Container Management At Khalifa Bin Salman Port, Abdulaziz A. Aljalahma Mar 2024

Enhancing Port Efficiency And Lead Time Reduction Through Predictive Analysis: A Case Study Of Container Management At Khalifa Bin Salman Port, Abdulaziz A. Aljalahma

Theses and Dissertations

Khalifa bin Salman Port (KBSP), a key pillar in Bahrain's maritime infrastructure, is the focal point of this study, highlighting the significant role of predictive analytics in optimizing port operations. This thesis analyzes container throughput data from 2017 to 2022, provided by Bahrain's Ministry of Transportation database. This data forms the basis for forecasting the 2023 throughput. The study thoroughly compares these predictions with the actual 2023 data, assessing the predictive model's accuracy. The findings underscore the importance of predictive analytics in strategic decision-making for port management, focusing on enhancing operational efficiency and reducing lead times. This research offers a …

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Optimizing Deployment Kit, Introducing Acceptance Threshold, Saleh A. Alshuhri Mar 2024

Optimizing Deployment Kit, Introducing Acceptance Threshold, Saleh A. Alshuhri

Theses and Dissertations

This article addresses the optimization of a specialized deployment kit crucial for air force operations, emphasizing the need for rapid and efficient aircraft deployment. Through a comprehensive analysis of historical data, the study aims to streamline the kit's contents without compromising effectiveness. The research suggests a potential reduction of 7.8%, with an impressive 60.5% decrease if a minimal 5% threshold is deemed acceptable. While the primary focus is on air force deployment, the broader implications extend to military entities, such as armies and navies, highlighting the applicability of the findings in enhancing deployment efficiency across various defense sectors.

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Electric Vehicle Support Equipment Deployment At Military Installations: A Mixed-Integer Linear Programming Approach, Katelyn M. Barton Mar 2024

Electric Vehicle Support Equipment Deployment At Military Installations: A Mixed-Integer Linear Programming Approach, Katelyn M. Barton

Theses and Dissertations

This research provides insights into a mixed integer linear programming model that finds the ideal number and type of Electric Vehicle Support Equipment (EVSE) required to meet U.S. military installations’ electric energy demands. Executive Order No. 14057 (2021) requires federal agencies to transition to electric non-tactical vehicles by 2035. This research determines minimum cost solutions to implement the transition incorporating real-world constraints, including the weekly vehicle mileage demand, EVSE cost, charging time, and EVSE capacity. This study contributes to the broader effort of the U.S. military to combat climate change and enhances the understanding of efficient EVSE deployment strategies in …

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Federated Medical Scoring Systems, Jacob F. Bryant Mar 2024

Federated Medical Scoring Systems, Jacob F. Bryant

Theses and Dissertations

Federated Learning (FL) is a recent framework of machine learning implementation that trains models on a distributed network of clients as opposed to housing and analyzing this data centrally. This has data communication and practical data privacy advantages, the latter of which is particularly attractive to the medical community where patient privacy is closely safeguarded. We apply FL to a family of sparse linear integer models called Medical Scoring Systems (MSSs). We create a novel methodology for creating these MSSs in a simulated federated environment that involves an lo constrained Logistic Regression (LR), loss-surface examination, and rounding procedure. We tested …

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On Intrinsic Dimensionality Of Data Sets And Neural Networks, Ori Chachmo Mar 2024

On Intrinsic Dimensionality Of Data Sets And Neural Networks, Ori Chachmo

Theses and Dissertations

The concept of Intrinsic Dimensionality (ID) is of special interest in the field of Neural Networks (NNs) since it promotes both (a) a deeper understanding of the underlying mechanisms, and (b) embraces parsimonious modeling (that is, building the right-sized model for the task) with associated benefits to processing speed and storage requirements. This thesis explores the concept of ID via two separate, but related, questions. First, we study the potential of NN ID prediction by exploiting easily obtained quantities measured on the data. We then explore NN ID as an independent concept by comparing the results of different methods for …

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Systematic Review Of Supply Chain Control Tower Critical Success Factors And Resilience Effects, Clay H. Chaffin Mar 2024

Systematic Review Of Supply Chain Control Tower Critical Success Factors And Resilience Effects, Clay H. Chaffin

Theses and Dissertations

Supply chain control towers (SCCTs) are emerging as a vital component of modern supply chain management (SCM); however, research on SCCTs is limited and disjointed. This paper aims to uncover the critical success factors (CSFs) necessary for high-performing SCCTs, their relationship to the enablers and phases of supply chain resilience (SCRES), and the underlying theoretical framework of this relationship.

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Evaluation Of Vtol-Capable Cargo Uavs For Dispersible Airfield Logistics In The Usindopacom Aor, Maria C. Chedzoy Mar 2024

Evaluation Of Vtol-Capable Cargo Uavs For Dispersible Airfield Logistics In The Usindopacom Aor, Maria C. Chedzoy

Theses and Dissertations

This research models and analyzes the ability of commercial cargo UAVs to rapidly evacuate logistics from an airfield to proximal, outlying destinations, particularly in the USINDOPACOM AOR. This is a tenet of Agile Combat Employment by the USAF, which seeks to mitigate the effect of kinetic threats by near-peer adversaries. The analysis sets forth a binary linear program to minimize the total time to evacuate a fixed amount of logistics from an airfield. Parameters include the cargo UAV with its performance specifications, number of cargo loading points at the airfield, number of destinations for cargo evacuation, and subset of destinations …

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2033 Digital Modernization At Usmepcom: A Strategic Analysis Of Future Military Applicant Processing, William A. Clay Mar 2024

2033 Digital Modernization At Usmepcom: A Strategic Analysis Of Future Military Applicant Processing, William A. Clay

Theses and Dissertations

This research examines the projected 2033 applicant processing scenario considering the digital modernization efforts of the United States Military Entrance Processing Command (USMEPCOM). The study evaluates the necessary modifications to current processes, with a particular focus on the influence of two key information technology systems, the MEPCOM Integrated Resource System (MIRS) 1.1 and the Military Health System (MHS) Genesis, on manpower at a Military Entrance Processing Station (MEPS). In doing so, the study establishes baseline processing metrics for assessing these impacts. By utilizing discrete event simulation modeling and leveraging current literature, the study proposes strategies for incorporating technological advancements into …

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Reinforcement Learning For Team Based Air Combat Maneuvering Decisions With Directed Energy Weaponry, Joshua D. Combs Mar 2024

Reinforcement Learning For Team Based Air Combat Maneuvering Decisions With Directed Energy Weaponry, Joshua D. Combs

Theses and Dissertations

Leveraging the Advanced Framework for Simulation, Integration, and Modeling (AFSIM) we investigate the use of reinforcement learning (RL) techniques for imbuing AUCAV agents with high-quality behaviors for the within-visual-range air combat maneuvering problem (ACMP). We formulate the 2v2 WVR ACMP as a Markov decision process wherein friendly AUCAVs are equipped with DEW capabilities and operate with 6 degrees of freedom. We utilize the Double Deep Q-Network RL algorithm, which centrally trains two friendly AUCAVs and employ a phased learning approach, initially exposing the AUCAVs to a dense reward environment for early training, followed by a sparse reward environment to encourage …

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Advanced Intermediate Manufacturing (Aim) Supply Chain Concepts Leading To Reduced Lead Times And Improved Responsiveness, Eric S. Draudt Mar 2024

Advanced Intermediate Manufacturing (Aim) Supply Chain Concepts Leading To Reduced Lead Times And Improved Responsiveness, Eric S. Draudt

Theses and Dissertations

This thesis investigates the optimization of the supply chain for key aircraft components, focusing on the implementation of Advanced Intermediate Manufacturing (AIM) production facilities. Utilizing anyLogistix, the study compares the current supply chain model based on Supply Chain Operations Wing (SCOW) data with various AIM production facility configurations: single, dual, quadruple, and three utilization-driven models (high, medium, and low). The findings demonstrate that integrating AIM production facilities significantly reduces lead times, with even a single facility dramatically cutting down the lead time from over 800 days to approximately 104 days. The utilization models further provide insights into operational flexibility under …

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An Integer Programming Model To Optimize Us Army Deployment Cycle And Maximize Unit Availability, Grant R. Engel Mar 2024

An Integer Programming Model To Optimize Us Army Deployment Cycle And Maximize Unit Availability, Grant R. Engel

Theses and Dissertations

The goal of this paper is to determine an optimal cycle length, in months, that minimizes costs and maximizes availability for deploying units in the United States (US) Army. The US Army must be cost efficient while maintaining the flexibility required to adapt to dynamic mission demand. The current practice is to deploy units for a length between the range of 6 to 12 months; however, this varies from unit to unit and the best policy is not clear. We address these issues by forming a mathematical programming model with unique characteristics that distinguish it from others of similar design. …

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Techniques For Addressing Extreme Class Imbalance For Artificial Neural Networks Training, Colin W. Foley Mar 2024

Techniques For Addressing Extreme Class Imbalance For Artificial Neural Networks Training, Colin W. Foley

Theses and Dissertations

This research examined the class imbalance problem while training convolutional neural networks (CNN) by applying different techniques to combat this common issue. This research used a modified CIFAR-10 dataset along with a curated aerial image dataset. Methods covered included undersampling, oversampling, synthetic minority oversampling technique, Edited Nearest Neighbors and combinations of the aforementioned methods. This research found that undersampling methods tended to outperform oversampling methods. While undersampling methods showed a decrease in overall accuracy, the increase in minority class prediction performance was promising enough to warrant further investigation.

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A Multi-Objective Approach To Optimal Deployment Policies For Wireless Sensor Networks Using Drop Points, Noah E. Fox Mar 2024

A Multi-Objective Approach To Optimal Deployment Policies For Wireless Sensor Networks Using Drop Points, Noah E. Fox

Theses and Dissertations

This research addresses the development of deployment policies for aerially dropped sensors in a wireless sensor network (WSN). Multi-objective genetic algorithm (GA) and simulated annealing meta-heuristic techniques, along with Monte Carlo simulation are used to identify policies with the aim of maximizing coverage and minimizing the number of sensors deployed. The policies developed from these techniques are then compared against uniform sensor distribution, as well as initial deployment policies that focus sensors in the center and edge of the region, as well as evenly deployed over the region. A total of 29 non-dominated policies were identified from the GA and …

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An Analysis Of China’S Perceived Geographic Locations Of Interest By Use Of Value Informed Facility Location Models, Layton C. Hedge Mar 2024

An Analysis Of China’S Perceived Geographic Locations Of Interest By Use Of Value Informed Facility Location Models, Layton C. Hedge

Theses and Dissertations

This research examines China and derives insights specific to it and the First Island Chain and the Second Island Chain. In doing so, this research demonstrates a methodology to examine other competitors and their geostrategic interests. In the first phase of analysis, it develops a value hierarchy to depict objectives within subregions of the area of interest and considers four alternative weightings of the value hierarchy. In the second phase of analysis, it applies four location-covering models to assess how the competitor would emplace a range of limited resources to deter and/or control points of interest. Results indicate that land-based …

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Analysis And Visualization Of Military Convoy And Supply Utilization In Support Of State-Specific Freight Plans, Madison E. Hofmann Mar 2024

Analysis And Visualization Of Military Convoy And Supply Utilization In Support Of State-Specific Freight Plans, Madison E. Hofmann

Theses and Dissertations

Researching the United States military’s use of highways and interstates is necessary for the allocation of federal infrastructure spending. As of today, there is no established method, tool, or process routinely utilized by the Surface Deployment and Distribution Command to effectively show a system-wide view of military convoy and supply route usage across CONUS. This research advances this endeavor by providing a by-state characterization of interstates and major highways in 2022, categorized by the volume of military freight they support. Some notable methodologies used to conduct the analyses are the shortest path problem, map matching algorithms, and Global Positioning System …

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Simulating Human-Autonomous Aircraft Teams In An Anti-Access Area Denial (A2ad) Environment, Michael Kaminski Mar 2024

Simulating Human-Autonomous Aircraft Teams In An Anti-Access Area Denial (A2ad) Environment, Michael Kaminski

Theses and Dissertations

The role of autonomy has evolved recently, demanding tighter integration between human and autonomous systems, particularly in highly contested A2AD environments. Near-peer adversaries have modernized their integrated air defense systems (IADS), diminishing the current advantages of the United States Air Force. To regain air dominance, efforts like the Collaborative Combat Aircraft (CCA) program are underway, aiming to deploy unmanned autonomous alongside manned next-generation fighter aircraft. This research assesses various operational concepts, focusing on autonomous tactics post-manned fighter loss, strike timing of independent teams, and weapon configuration observability. Using the Advanced Framework for Simulation, Integration and Modeling (AFSIM), an agent-based model …

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Usmepcom Prescreens: A Value-Focused Thinking Approach, Phillip M. Koenig Mar 2024

Usmepcom Prescreens: A Value-Focused Thinking Approach, Phillip M. Koenig

Theses and Dissertations

As the recruiting crisis continues to impact the United States Armed Forces, the United States Military Entrance Processing Command (USMEPCOM) continues to search for ways to increase its capability to efficiently determine which applicants are suited for military service. Unfortunately, USMEPCOM does not have a way to evaluate newly suggested alternatives. By leveraging Value-Focused Thinking (VFT), this research describes 28 fundamental objectives that can be applied to a variety of current and future decision problems. Further, this research applies these fundamental objectives to analyze a current decision problem: reengineering the prescreen process to decrease the time from prescreen submission to …

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U.S. Army Cadet Command Branch Prediction Model, Daniel M. Krizan Mar 2024

U.S. Army Cadet Command Branch Prediction Model, Daniel M. Krizan

Theses and Dissertations

The current system for providing US Army ROTC cadets their branches leaves significant uncertainty until the final pronouncement of branch assigned. This uncertainty can be alleviated by providing a prediction model for cadets to input personal data and desired branch to identify likelihood of receiving the request. This thesis produces a machine learning model capable of producing branch prediction for cadets.

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The Use Of Deep Learning And Transfer Learning In Complex Problems, Jacob S. Lang Mar 2024

The Use Of Deep Learning And Transfer Learning In Complex Problems, Jacob S. Lang

Theses and Dissertations

Deep neural networks and transfer learning show potential in addressing complex problems such as the Tower of Hanoi and knapsack problems. The primary aim is to examine how the use of deep neural networks and transfer learning can enhance the ability of artificial learning systems to generalize. Transfer learning plays a crucial role in machine learning, particularly in the domain of artificial neural networks, as it helps overcome the challenges associated with limited data, computational efficiency, and generalization. The methodology used in this research involves the creation of data sets for the Tower of Hanoi and knapsack problems. To predict …

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Automated Image Registration For Titanium Aircraft Components Via Resolution-Robust Parallel Neural Networks, Paige T. Luebbering Mar 2024

Automated Image Registration For Titanium Aircraft Components Via Resolution-Robust Parallel Neural Networks, Paige T. Luebbering

Theses and Dissertations

Titanium alloys are vital to the structural integrity of military and commercial aircraft, comprising numerous critical components. These components are composed of microtexture regions (MTRs) that, at a specific size and orientation, can lead to aircraft failure. Existing MTR testing methods, such as Electron Backscatter Diffraction, often fall short in effectively detecting these MTRs without causing damage to the component. Addressing this gap, this thesis develops a Parallel Convolutional Neural Network (CNN) model tailored for multi-resolution image registration of Polarized Light Microscopy (PLM) images to enhance MTR identification in a non-invasive manner. The findings reveal a significant enhancement in the …

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A Reinforcement Learning Self-Play Approach For Informing Wargaming Analysis & Development, Kathleen A. Maclean Mar 2024

A Reinforcement Learning Self-Play Approach For Informing Wargaming Analysis & Development, Kathleen A. Maclean

Theses and Dissertations

The integration of RL into wargames to learn strategic and operational insights is of interest to the United States Air Force. This thesis explores the application of a RL SARSA(λ) algorithm to the wargame Stratagem MIST. The primary objective is to select air and ground combat policies for the Blue Agent to effectively counter various opponent strategies across different terrains. This testing enables a comprehensive evaluation of the Blue Agent’s adaptability and performance under varying combat conditions. The use of basis functions, linear value function approximations, and specific air and ground strategies simplifies the state and action spaces of the …

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Bayesian Augmentation Of Object Detection Algorithms To Enhance Object Classification Stability, Taylor D. Markham Mar 2024

Bayesian Augmentation Of Object Detection Algorithms To Enhance Object Classification Stability, Taylor D. Markham

Theses and Dissertations

Neural networks, despite their prowess in computer vision, often exhibit "flickering". Flickering occurs when networks fail to maintain consistent object representation across frames, leading to inaccurate and inconsistent output. This problem is particularly critical in mission-surety applications where reliable object recognition is crucial. This research presents a novel approach that combines existing object detection and tracking algorithms like YOLO and SORT with a Bayesian backend model. This Bayesian backend incorporates probabilistic reasoning to analyze the network's confidence in its predictions and infer the most likely object identity across multiple frames, effectively reducing flickering and enhancing robustness.

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