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Articles 511 - 540 of 674
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Proximal Policy Optimization Applied To The Beyond Visual Range Air Combat Maneuvering Problem, Daniel B. Joseph
Proximal Policy Optimization Applied To The Beyond Visual Range Air Combat Maneuvering Problem, Daniel B. Joseph
Theses and Dissertations
Artificial intelligence (AI) grows ever-more important in warfighting. Emerging technologies allow for the use of AI to control aircraft and weapons systems. This research investigates the application of reinforcement learning (RL) through the Proximal Policy Optimization (PPO) algorithm to a two-versus-two (2v2) beyond-visual-range (BVR) air combat maneuvering problem (ACMP). Implemented in the Advanced Framework for Simulation, Integration, and Modeling (AFSIM), the methodology frames the engagement as a Markov decision process, wherein an autonomous RL agent learns continuous control decisions—throttle, pitch, roll, and yaw—under a cooperative communication scheme. A multi-phase curriculum-learning approach facilitates the progressive acquisition of flight stability, weapon deployment, …
A Case Study N Modeling The Human Behavior Of Basic Fighter Maneuvers Using Mbse, Josiah J. Franklin
A Case Study N Modeling The Human Behavior Of Basic Fighter Maneuvers Using Mbse, Josiah J. Franklin
Theses and Dissertations
As fighter aircraft become more complex and technology, such as autonomy, is introduced, it is essential to anticipate the critical tasks and information pilots need to accomplish their mission with these new systems. Fighter pilots operate in highly demanding situations where the consequences of failure are severe and require their systems to provide the right information for the task. Traditionally, these designs are informed through Critical Task Analyses of existing systems. This research produced a method for modeling critical task analysis and information requirements using model-based systems engineering. The scenario was a fighter aircraft conducting basic fighter maneuvers in a …
Spatiotemporal Prediction Of Atmospheric Events Through Recurrent Deep Learning Model, Brian W. F. Popick
Spatiotemporal Prediction Of Atmospheric Events Through Recurrent Deep Learning Model, Brian W. F. Popick
Theses and Dissertations
The main contributions of this research is to add to the growing library of literature on the use of deep learning algorithms for the spatiotemporal prediction of dangerous atmospheric and hydrologic phenomena. Specifically, we develop novel attention-based and non-attention-based recurrent neural network frameworks to produce short-range sequential forecasts for lightning and tornado occurrences. Additionally, we introduce methods that account for and include error in the model tuning process to generate more reliable models. Furthermore, we have created a lightweight spatiotemporal tornadic prediction dataset that we plan to make publicly available. The first component of this research develops three novel spatiotemporal …
The Application Of Decision Analysis Theory For Space Allocation At The Air Force Institute Of Technology, Damian N. Soriano
The Application Of Decision Analysis Theory For Space Allocation At The Air Force Institute Of Technology, Damian N. Soriano
Theses and Dissertations
This thesis investigates the application of Decision Analysis Theory to optimize space allocation at the Air Force Institute of Technology (AFIT). Through a Multi-Objective Decision Analysis (MODA) framework, this study addresses existing methodologies for space allocation in military, academic, and office settings; the rules, limitations, and factors influencing space utilization at AFIT; and approaches to improve office and lab allocations for institutional efficiency and fairness. This research incorporates qualitative and quantitative metrics, including faculty and student data, research outputs, and historical space usage. These findings highlight significant complexities in space allocation, particularly in reconciling administrative and research requirements with structural …
Reinforcement Learning For Aeromedical Evacuation In Nonstationary Combat Environments, Micah J. Kartchner
Reinforcement Learning For Aeromedical Evacuation In Nonstationary Combat Environments, Micah J. Kartchner
Theses and Dissertations
This research formulates the medical evacuation (MEDEVAC) dispatching problem as a sequential decision process and investigates the application of reinforcement learning under nonstationary conditions. We model the dynamic arrival rate of MEDEVAC requests using a nonstationary Hawkes process and design a Double Deep Q-Network algorithm that incorporates belief states to anticipate future requests. Through computational experimentation, we analyze the impact of belief formulation on decision quality and system performance. Results indicate that policies incorporating belief states significantly outperform myopic dispatching policies, reducing urgent casualty wait times by up to 49.68% and increasing on-time evacuations by up to 21.91%.
Military Entrance Processing Station Location And Capacity Optimization, Micah A. Hurst
Military Entrance Processing Station Location And Capacity Optimization, Micah A. Hurst
Theses and Dissertations
This research optimizes the number, placement, and capacity of Military Entrance Processing Stations (MEPS) to minimize applicant and recruiter travel and improve recruitment efficiency. Using mixed-integer programming, it develops capacitated facility location (CFLP) and maximal covering location (MCLP) models, considering facility capacity, budget, and geographic coverage. Computational testing and scenario evaluations highlight opportunities to reduce travel and balance capacity. For example, the CFLP model adds three new MEPS, reducing annual applicant travel by 1.2 million miles in Florida and Texas and 1.0 million in California, while increasing accessibility within 60 miles of a MEPS. This data-driven approach provides USMEPCOM with …
Simulating The Impact Of Self-Sensing Materials On Aircraft Sortie Generation, Harmoni J. Blackstock
Simulating The Impact Of Self-Sensing Materials On Aircraft Sortie Generation, Harmoni J. Blackstock
Theses and Dissertations
In conjunction with the Air Force Research Laboratory Materials Lab(AFRL-RX), this study evaluates the potential military value of the prototype material sensing composites on Unmanned Aerial Vehicle (UAV) operations in intelligence, surveillance, reconnaissance (ISR), and close air support (CAS) missions within a contested Indo-Pacific theater. Using a Simio based simulation,UAV performance was assessed under varying combat conditions, focusing on Remote Sensing, deployment strategies, initial lay-downs, and varying loss rates. Re-sults show that UAVs equipped with Remote Sensing technology significantly improved sortie generation and logistical efficiency. Scenario 17 achieved the highest sortie rate(965.5 sorties), outperforming the next-best scenario by 25 sorties. …
Improving Zero Shot Learning By Linking Multi-Label Cnns With Llms, Michael A. Wegner
Improving Zero Shot Learning By Linking Multi-Label Cnns With Llms, Michael A. Wegner
Theses and Dissertations
Classifying previously unseen objects poses a significant challenge for traditional computer vision algorithms, which rely on extensive labeled training data. Zero-shot reasoning offers a way to overcome this limitation. This research explores a novel method for image recognition using the Animals with Attributes 2 (AWA2) dataset as a proof of concept. A multi-label ResNet50 model predicts core attributes like color, ear shape, or number of limbs. Those attributes then feed into ChatGPT which leverages its extensive knowledge base to classify the animal based on the provided attributes. This novel approach skips the need to train on every possible class. Instead, …
An Analysis Of Development Phase Nre/Rec Costs In Dod Acquisition Efforts, Jason Aristizabal
An Analysis Of Development Phase Nre/Rec Costs In Dod Acquisition Efforts, Jason Aristizabal
Theses and Dissertations
Estimating Nonrecurring Engineering (NRE) and Recurring Engineering (REC) costs in defense acquisition programs remains challenging, especially in development. While production costs are studied, NRE/REC ratios in development receive little attention. This study analyzes NRE/REC ratios across WBS elements, commodity types, and time periods using defense program data. Results show significant variability, challenging the assumed 1:1 ratio. System Level, PME, and ST&E elements follow distinct trends, highlighting shifting cost structures. These findings stress the need for adaptive methodologies, enabling cost analysts to refine estimates based on historical trends and program-specific factors for improved resource planning.
An Agent-Based Modeling Framework For Evaluating The Linkage Between Disaster Facility Damage And Mental Health, Emily S. Reeves
An Agent-Based Modeling Framework For Evaluating The Linkage Between Disaster Facility Damage And Mental Health, Emily S. Reeves
Theses and Dissertations
This research establishes a novel agent-based modeling framework to establish the linkage between disaster-induced facility damage and mental health outcomes and the evaluation of treatment methods within the civilian and USAF mental health spheres. The study models the degradation and recovery of agent mental health using simulated data and evaluates the efficacy of three distinct treatment approaches through statistical methods. The methodology integrate agent-based modeling with resilient engineering concepts to simulate mental health resilience curves based on vulnerability, exposure, and facility damage. Agents’ mental health indices were tracked through phases of degradation, stagnation, and recovery based on the three treatments …
An Analysis Of Hardware Modification Cost: A Test Of A 1:1 Ratio Heuristic, Oluwasegun Faleye
An Analysis Of Hardware Modification Cost: A Test Of A 1:1 Ratio Heuristic, Oluwasegun Faleye
Theses and Dissertations
Accurate cost estimation for Department of Defense (DoD) hardware modification programs remains a critical challenge due to the complexity of Group A and Group B modifications and their associated installation costs. This study evaluates the validity of a 1:1 ratio heuristic, which suggests that Group A modification kits combined with installation costs should equate to the costs of Group B modification kits. This study analyzes cost relationships across system types and modification categories using a dataset of 255 modification programs from the Air Force Life Cycle Management Center (AFLCMC). Statistical methods, including means tables and regression modeling, evaluate the validity …
Using Mbse To Facilitate Integration And Stakeholder Support For Autonomous Aerial Refueling Flight Test, Kevin G. Keth
Using Mbse To Facilitate Integration And Stakeholder Support For Autonomous Aerial Refueling Flight Test, Kevin G. Keth
Theses and Dissertations
he Department of Defense has pushed to implement Digital Material Management, to include Engineering (DE) and Model-Based Systems Engineering (MBSE) into acquisition processes, publishing various supporting documents such as the Systems Engineering Guidebook, DoDI 5000.97 Digital Engineering, and DoD Reference Architecture Description. DE and MBSE aims to establish a digital authoritative source of truth accessible to all stakeholders responsible for system architecture. However, within multidisciplinary teams, individuals often come from diverse professional backgrounds unrelated to DE and systems engineering, making it challenging to fully leverage the benefits of the digital model. This paper describes an MBSE model that adopts a …
Methodology Of Automated Control Of Situations In Structurally Complex Systems With Recycled Flows, Khusan Zokirovich Igamberdiev Academician, Madina Mirxalilovma Fozilova
Methodology Of Automated Control Of Situations In Structurally Complex Systems With Recycled Flows, Khusan Zokirovich Igamberdiev Academician, Madina Mirxalilovma Fozilova
Chemical Technology, Control and Management
This article discusses the methodology of automated management of situations in structurally complex systems with recycled flows. The need to develop a correct model for effectively controlling such systems based on scientific principles of analysis and decision-making is substantiated. Particular attention is paid to modeling, optimizing, and using digital technologies, including artificial intelligence, to improve the accuracy and efficiency of management decisions. The principles of decomposition, multi-criteria optimization, and linguistic models of fuzzy correspondence are described, which can be used in conditions of uncertainty and complexity of industrial facilities.
Joint Estimation Of The State And Parameters Of Dynamic Control Objects Based On The Maine Estimator, Yulduz Abdurakhmanova
Joint Estimation Of The State And Parameters Of Dynamic Control Objects Based On The Maine Estimator, Yulduz Abdurakhmanova
Chemical Technology, Control and Management
The issues of constructing an adaptive joint estimation of the state and parameters of dynamic control objects using the Maine estimator are considered. There are various variants of the extended filter, and a variant based on iterations between parameter and state estimates was used in the work. In this version of the extended Kalman filter, the problem of joint parameter and state estimation is solved in such a way that parameter estimation is performed before state estimation. Then, the parameter values are used to assess the state. In this case, further iterations between the state vector estimation and the parameter …
Determination Of Chemical And X-Ray Phase Analysis Of Carbon-Containing Material, Sh.T. Juraev, B.F. Muxiddinov, U.T. Tailakov
Determination Of Chemical And X-Ray Phase Analysis Of Carbon-Containing Material, Sh.T. Juraev, B.F. Muxiddinov, U.T. Tailakov
Chemical Technology, Control and Management
This paper presents a chemical and X-ray diffraction study of the solid fraction obtained from the thermal-oxidative pyrolysis of waste tires. The study covers the analysis of the composition of rubber products before and after pyrolysis at a temperature of 750-850 °C. A chemical analysis of the gaseous, liquid and solid phases of pyrolysis products was also carried out. The ignition temperatures of gaseous products, their percentage content, as well as the optimal boiling temperatures of the resulting condensates were determined. X-ray analysis showed that the solid carbon residue consists of calcite (7.50%), amorphous carbon (87.24%), ankerite (Ca(Mg, Fe)[CO3 …
Dеvеlоpmеnt Аnd Simulаtiоn Оf Аutоmаtiс Tеmpеrаturе Соntrоl Sуstеms Fоr Sоlаr Drуеrs, Sarvar Rejabov, Botir Shukurillayevich Usmonov, Komil Usmanov
Dеvеlоpmеnt Аnd Simulаtiоn Оf Аutоmаtiс Tеmpеrаturе Соntrоl Sуstеms Fоr Sоlаr Drуеrs, Sarvar Rejabov, Botir Shukurillayevich Usmonov, Komil Usmanov
Chemical Technology, Control and Management
Thе utilizаtiоn оf sоlаr еnеrgу in thе drуing оf аgriсulturаl prоduсts is соnsidеrеd signifiсаnt duе tо its еnеrgу еffiсiеnсу аnd еnvirоnmеntаl friеndlinеss. Hоwеvеr, trаditiоnаl drуing mеthоds fасе сhаllеngеs in mаintаining stаblе tеmpеrаturе аnd humiditу lеvеls, whiсh саn lеаd tо rеduсеd prоduсt quаlitу аnd dесrеаsеd prосеss еffiсiеnсу. Tо аddrеss thеsе issuеs, thе implеmеntаtiоn оf аutоmаtiс соntrоl sуstеms is еssеntiаl. In dеvеlоping аn аutоmаtiс tеmpеrаturе соntrоl sуstеm fоr sоlаr drуеrs, thе hеаt аnd mаss trаnsfеr prосеssеs wеrе prесisеlу mоdеlеd. Thе primаrу pаrаmеtеrs оf thе drуing prосеss, suсh аs prоduсt tеmpеrаturе аnd mоisturе соntеnt dуnаmiсs, wеrе еxprеssеd thrоugh mаthеmаtiсаl еquаtiоns. PID аnd Fuzzу …
Modeling Of Analog-To-Digital Converter In Signal Processing, Ravshan Aliev, A.U. Djalilov
Modeling Of Analog-To-Digital Converter In Signal Processing, Ravshan Aliev, A.U. Djalilov
Chemical Technology, Control and Management
This article is devoted to the study of the modeling process of analog-to-digital converters (ADCs) that process signals, one of the main parts of control system elements and devices. As we know, ADCs are an important part of modern control systems. During the research, the main stages of analog signal conversion were analyzed, i.e. discretization, quantization, coding. A classification of analog-to-digital conversion methods was made and the advantages and disadvantages of each were identified. Also, the characteristics and parameters of ADC were studied, their impact on ADCs performance was evaluated, and it was determined that certain characteristics should be taken …
Principles And Models Of Construction Of Linear Motion Actuators With Holonomic Structure For Intelligent Robot Movement, Matyokubov Nurbek Rustamovich, Temurbek Omonboevich Rakhimov, Yusupov Bekmurod Bayotovich
Principles And Models Of Construction Of Linear Motion Actuators With Holonomic Structure For Intelligent Robot Movement, Matyokubov Nurbek Rustamovich, Temurbek Omonboevich Rakhimov, Yusupov Bekmurod Bayotovich
Chemical Technology, Control and Management
This article is devoted to the principles and models of building linear motion actuators with holonomic structure for the movement of intelligent robots. Also, the classification of the elements of the linear movement performance according to their interconnections and technical characteristics, taking into account their physical characteristics, was seen. A morphological matrix of the construction of holonomic structured linear motion performance elements based on the classification according to the considered technical specifications is presented. The given morphological matrix of linear motion actuators serves to develop new actuators for intelligent mechatronic and robotic systems. Based on the morphological matrix of the …
Application Of An Adaptive Neuro-Fuzzy Inference System To Control The Wastewater Treatment Process, Jaloliddin Abdurazzakovich Eshbobaev, Bakhodir Tajiddinovich Khamidov, Marcos Torices Fallanza
Application Of An Adaptive Neuro-Fuzzy Inference System To Control The Wastewater Treatment Process, Jaloliddin Abdurazzakovich Eshbobaev, Bakhodir Tajiddinovich Khamidov, Marcos Torices Fallanza
Chemical Technology, Control and Management
This study explores the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for controlling wastewater treatment processes using ion-exchange resins. It addresses the critical challenges of water scarcity and pollution by enhancing the regulation of water hardness (H) and Total Dissolved Solids (TDS). Using a pilot laboratory device and experimental data from the mixed wastewater of the Kungrad Soda Plant in Uzbekistan, an ANFIS model was developed in MATLAB to automate process control. The model leverages water hardness and TDS as input parameters to regulate the water flow rate by servo valve opening degree, ensuring precise and efficient treatment. Compared …
Sustainability In Forex Trading: A Review In Search Of The Sarsa-Fis Hybrid Method As A Novelty, Joni Fat, Parwadi Moengin, Pudji Astuti, Sally Cahyati
Sustainability In Forex Trading: A Review In Search Of The Sarsa-Fis Hybrid Method As A Novelty, Joni Fat, Parwadi Moengin, Pudji Astuti, Sally Cahyati
Bulletin of Monetary Economics and Banking
This study employs meta-analysis, rich pictures, timeline analysis, and causal loop diagram to explore the sustainability impacts of the SARSA-FIS hybrid method in forex trading robots. It reviews 56 references (2018-2023), using rich pictures to map AI-driven interactions. Timeline analysis traces AI’s evolution in forex, while causal loop diagram clarifies its role in market dynamics. Responsible algorithms and SRI principles mitigate risks, promoting ethical trading. SARSA-FIS enhances strategies, leveraging AI for sustainable forex practices amidst global uncertainties. The research identifies gaps and positions SARSA-FIS as a novel approach, providing a foundation for advancing AI applications in finance, particularly in forex …
Comparative Evaluation Of Linear Regression, Cross Validation And Regularization Approaches In Multivariate Data Analysis, Ransford Owusu, Felix Yeboah, Francis Effah Boateng
Comparative Evaluation Of Linear Regression, Cross Validation And Regularization Approaches In Multivariate Data Analysis, Ransford Owusu, Felix Yeboah, Francis Effah Boateng
Data Science and Data Mining
This study evaluates linear regression and its enhanced variants incorporating cross-validation and regularization techniques for high-dimensional, multivariate datasets. We address challenges such as multicollinearity and overfitting. Methods including Ridge, LASSO, and Elastic Net are compared against ordinary least squares regression. Empirical analysis using an automobile dataset for fuel efficiency prediction shows that while OLS regression captures basic relationships, its limitations are mitigated through regularization and cross-validation, resulting in improved model interpretability. The findings provide a comprehensive framework for predictive modeling in complex data environments and offer insights into statistical methodology and practical applications in the automobile industry.
Additive Manufacturing Applications In Mission-Critical Operations: A Review, Arup Dey, Olusanmi Adeniran, Monsuru Ramoni
Additive Manufacturing Applications In Mission-Critical Operations: A Review, Arup Dey, Olusanmi Adeniran, Monsuru Ramoni
Manufacturing & Industrial Engineering Faculty Publications
Additive manufacturing (AM) is used to fabricate complex components from a wide variety of materials in an additive manner. AM brings several benefits, such as reduced lead times, on-demand production, creation of complex customized designs without tooling requirements, and remote design sharing. However, the use of AM for critical components is limited in large missions due to quality and reliability concerns, as is the case with many manufacturing technologies. Enhancing the acceptance of AM-built parts for mission-critical components can be achieved by producing highly reliable parts, establishing robust quality standards, and continually improving part properties. This review article comprehensively explores …
Utilizing Ai For Improved Credit Risk Assessment, Emel Baglarbasi
Utilizing Ai For Improved Credit Risk Assessment, Emel Baglarbasi
Harrisburg University Dissertations and Theses
As the finance sector continues to evolve, traditional risk assessment methods struggle to calculate default risk and identify nonlinear relationships accurately. This research examines an alternative risk assessment model designed to estimate credit risk more accurately and efficiently in the credit processes of individual customers, which are one of the primary sources of income for the banking sector. It presents the theoretical design of an AI-based model. The use of this AI model can reduce human error in processes, improve risk assessment accuracy, and expedite procedures. The study adopts a postpositivist worldview and employs a quantitative research design. Algorithms including …
Incorporating Sustainability In Facility Layout Planning Algorithms And Assessing Hybridization Techniques On An Egyptian Case Study, Islam Atia
Theses and Dissertations
Due to the growing consequences faced as a result of global warming and climate change; humanity has come together to take an inclusive stance to combat this serious phenomena and work towards a more sustainable future. Large amounts of carbon dioxide emissions are a major contributor to global warming, and a vast proportion of this emission come from industrial and commercial facilities. Hence, if industrial facilities are built with a larger focus on carbon footprint, it will yield a significant reduction in global emissions throughout the lifetime of the facility and will constitute a huge milestone in the journey to …
Research On Task Planning Methods For Space Robot Assisted Operation, Guoqiang Fang, Haitao Chang, Xing Liu, Zhengxiong Liu, Panfeng Huang
Research On Task Planning Methods For Space Robot Assisted Operation, Guoqiang Fang, Haitao Chang, Xing Liu, Zhengxiong Liu, Panfeng Huang
Journal of System Simulation
Abstract: In view of the difficulties caused by the complicated task process and numerous task constraints during the space robot assisted operation, a task planning method combining fast forward search algorithm and hierarchical network algorithm is proposed, in which the task planning process is divided into task planning and replanning. Based on the fast forward search task planning method of operation cost, the execution sequence of actions with minimum operation cost is obtained. The task adaptive replanning method based on hierarchical network corrects and compensates the problems according to the priority of compensation for the movement, grab and release actions. …
Intelligent Service Migration Towards Mec-Based Iov Systems, Sijin Huang, Jia Wen, Zheyi Chen
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 …
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
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% …
A Hybrid Heuristic Algorithm For Solving The Green Vrp With Priority Delivery, Huanhuan Cui, Lihe Guan
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 …
Improved Target Detection Algorithm For Aerial Images Based On Yolov5, Yecai Guo, Jingdong Sun, Saha Amitave
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, …
An Empirical Analysis Of New Perspectives For Strategy Solving In Intelligent Game-Theoretic Decision-Making, Jiongming Su, Junren Luo, Shaofei Chen
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 …