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Articles 901 - 930 of 13799
Full-Text Articles in Engineering
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 …
End-To-End (E2e) Model-Based Systems Engineering (Mbse) Framework, Joshua Adelabu, Bhushan Lohar
End-To-End (E2e) Model-Based Systems Engineering (Mbse) Framework, Joshua Adelabu, Bhushan Lohar
Shelby Hall Graduate Research Forum Presentations
This presentation explores the latest advancements in systems engineering, with a particular focus on Model-Based Systems Engineering (MBSE). It covers key definitions, benefits, applications, and challenges associated with these methodologies, as well as analyzes current frameworks and research methodologies in the field.
End-To-End (E2e) Mbse Framework, Joshua Adelabu, Bhushan Lohar
End-To-End (E2e) Mbse Framework, Joshua Adelabu, Bhushan Lohar
Shelby Hall Graduate Research Forum Posters
Principles of systems engineering (SE) possess great influence. Frameworks are generated to execute and incorporate such principles. Framework can have various architectural constructs and simultaneously consist of diverse concepts. Concepts like modularity, scalability, integration, and the balance between performance, cost, and risk are guided by SE principles as well as the manufacturability of designed systems due to the migration from mass customization to mass personalization resulting in increased complexity, and as a result need to be guided and gives rise to modularity. However, principles are not enough for effective system design and understanding. There is a need for a framework. …
Operational Energy Education: A Thematic Analysis Of Knowledge Area Needs And Educational Gaps, Nana Hene
Operational Energy Education: A Thematic Analysis Of Knowledge Area Needs And Educational Gaps, Nana Hene
Theses and Dissertations
Operational Energy (OE) education is vital for national security, military readiness, and fuel energy efficiency. This thesis analyzes the current landscape of OE education and identifies key gaps in awareness, energy knowledge, and curriculum structure. Through a reflexive thematic analysis of interviews with Subject Matter Experts (SMEs), the study underscores the necessity of integrating OE concepts into both educational and professional training programs. A framework is proposed to enhance OE education across various levels in the Air Force, aiming to cultivate a more energy-conscious and strategically prepared force. The findings highlight the critical need for targeted training, curriculum enhancements, and …
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 …
Practical Estimation Of Action-Generation Mechanisms In Repeated Games, Vladimer Kellachow Iii
Practical Estimation Of Action-Generation Mechanisms In Repeated Games, Vladimer Kellachow Iii
Theses and Dissertations
The goal of this research is to gain insight into how players of a game learn their strategy during the course of repeated play. The study employs the Experience Weighted Attraction (EWA) model, developed by Dr. Colin F. Camerer and Dr. Teck-Hua Ho, as the foundational behavioral framework. Using historic observed strategy decisions, the parameter values that define an opponent’s learning process are updated using various inference methods.
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 …
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. …
Real-Time Decision-Making During Maritime Chokepoint Disruption Using Digital Twin, Jared M. Orendorff
Real-Time Decision-Making During Maritime Chokepoint Disruption Using Digital Twin, Jared M. Orendorff
Theses and Dissertations
This research develops a digital twin of the global maritime shipping system to model disruptions in major shipping lanes like the Suez and Panama Canals. By incorporating live ship-tracking data, the model simulates closures, forecasts queue lengths, and determines the best rerouting options. Findings show that canal closures cause large traffic backlogs and increased congestion at alternative chokepoints, while rerouted ships may face higher piracy risks in regions like the Gulf of Guinea and the Strait of Malacca. This tool helps decision-makers respond effectively to maritime disruptions.
Utility Of Self-Sensing Damage Technology Through A2/Ad Drone Combat Simulation, Sidhanth Venkatasubramaniam
Utility Of Self-Sensing Damage Technology Through A2/Ad Drone Combat Simulation, Sidhanth Venkatasubramaniam
Theses and Dissertations
Since the introduction of the first unmanned aerial vehicle (UAV), UAVs have consistently improved in capability and versatility. The ability to perform military operations without the risk of losing human life is crucial for the United States military. The trade-off for this versatility is cost, and several ongoing research efforts are being made to improve UAV mission success and the lifespan of UAVs. An area of research that falls under the categories mentioned is self-damage detection. The Air Force Research Laboratories (AFRL) are developing a capability to enable a UAV to assess airframe damage, enabling real-time determination of damage potentially …
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, …
Analysis Of An Army Recruiter Allocation Model (Ram), Erik J. Wittendorf
Analysis Of An Army Recruiter Allocation Model (Ram), Erik J. Wittendorf
Theses and Dissertations
The United States Army Recruiting Command’s mission to recruit America’s best and brightest volunteers that can deploy, fight, and win requires an effective distribution of its recruiting force to serve as local community ambassadors. This research analyzes an Army recruiter allocation model (RAM) and assesses its underlying assumptions, objective function, and constraints. A detailed study of relative market potential and production rates for up to 1,319 Army recruiting stations and 18,789 ZIP codes enables RAM modification recommendations leveraging evolving recruiting concepts and identifies areas of future work to continue improving the Army’s understanding of the recruiting environment.
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.
Performing Requirements Specification And Analysis Through Open Generative Pre-Trained Transformers, Harvey J. Hurst
Performing Requirements Specification And Analysis Through Open Generative Pre-Trained Transformers, Harvey J. Hurst
Theses and Dissertations
Every acquisition program begins with a requirement, and for those programs to succeed, robust requirements engineering (RE) must be implemented. RE encompasses eliciting, analyzing, specifying, and validating requirements—a critical process throughout a program's lifecycle. Despite its importance, RE faces challenges such as scope creep, ambiguity, redundancy, and inadequate automation support, often exacerbated by reliance on historical data. To address these issues, this thesis leverages advancements in Generative Technology, particularly large language models (LLMs) such as Generative Pre-Trained Transformers (GPTs). This research developed two GPT-based tools: the Single Requirement Analysis Tool and the Set of Requirements Analysis Tool. These tools were …
Model-Based Approach To Support Safety Driven Design And Satisfy Mil-Std-882e Requirements With Stpa Coordination: A Case History In Suas Defense Acquisition, Daniel A. Shea
Theses and Dissertations
Increasingly complex defense systems that are routinely overbudget and behind schedule are driving digital engineering initiatives in the defense acquisition industry. MBSE offers a solution to counter this issue but the lack of guidance on how to implement it has led to significant experimentation. One MBSE area of interest is system safety. This research demonstrates how to conduct model-based Systems Theoretic Process Analysis (STPA) to meet the unique system safety process requirements from MIL-STD882E. Based in systems theory, STPA extended for coordination enables a safety-driven design process of complex systems. This research investigated conducting STPA in the SysML-RAAML modeling language …
Symbology Detection And Numerical Recognition For T-38 Heads-Up Display Recordings, Ben T. Hepner
Symbology Detection And Numerical Recognition For T-38 Heads-Up Display Recordings, Ben T. Hepner
Theses and Dissertations
The extraction of symbology and numerical data from the T-38 Heads-Up Display (HUD) enhances post-flight analysis and supports real-time decision-making. This research develops a deep learning pipeline using YOLO-based object detection and Optical Character Recognition (OCR) to analyze HUD video data. Model evaluations showed mAP0.5:0.95 ranging from 0.422 (YOLOv11m, hard test set) to 0.696 (YOLOv8m, medium test set), demonstrating robust symbology detection. Numeric detection performed well (mAP0.5:0.95 = 0.764), but OCR struggled with glare and resolution limitations, achieving a recognition accuracy of 17.35%. These results validate deep learning for HUD data extraction but highlight the need for improved robustness …
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, …
Learning To Dogfight: Proximal Policy Optimization Vs. Double Deep Q Network For 2v2 Air Combat With Directed Energy Weapons In Afsim, Caden W. Wilson
Learning To Dogfight: Proximal Policy Optimization Vs. Double Deep Q Network For 2v2 Air Combat With Directed Energy Weapons In Afsim, Caden W. Wilson
Theses and Dissertations
This research utilizes reinforcement learning (RL) to train two blue agents each imbued with a directed energy weapon (DEW) in a 2v2 within visual range air combat maneuvering problem. A phased solution approach is employed to repeatedly tune and train several RL algorithm implementations: Proximal Policy Optimization (PPO) and Double Deep Q Network (DDQN). Phase I of training includes reward shaping for basic flight elements such as altitude, airspeed, and target proximity. Phase II of training builds off policies developed in Phase I, but rewards emphasize winning the aerial engagement by any means necessary. DDQN significantly outperforms PPO in Phase …
Safety-Driven Concept Development Using System Theoretic Process Analysis Extended For Coordination In A Model Based Environment: A Case Study On Autonomous Satellite Teaming, Taylor L. Matarazzo
Safety-Driven Concept Development Using System Theoretic Process Analysis Extended For Coordination In A Model Based Environment: A Case Study On Autonomous Satellite Teaming, Taylor L. Matarazzo
Theses and Dissertations
Rigorous system safety analysis methods, allow programs to identify potential problems helping to minimize their impact to program schedules and budgets. In the contested, congested, and competitive space environment, coordination within and between systems is critical to mission success. System Theoretic Process Analysis extended for Coordination (STPA-coord) can prescriptively analyze these coordination interactions. STPA-coord shifts the conversation of system safety from elements ofreliability to elements of control, providing insights that holistically analyze the system. As studies suggest, decisions made early in a systems design determine 80-86% of a programs final cost, therefore integrating system safety as early into design can …
Weighed And Measured: Toward An Evaluation Method For Digital Models In Source Selection, Liam N. O'Neill
Weighed And Measured: Toward An Evaluation Method For Digital Models In Source Selection, Liam N. O'Neill
Theses and Dissertations
Inspired by a recent model-based source selection conducted by the Advanced Range Threat System (ARTS) Program Office at Hill AFB, this research effort explored the development of new tools the DoD could use when evaluating models submitted with proposals. Specifically, the effort aimed to incorporate the Multi-Objective Decisions Analysis (MODA) framework into SysML diagrams as a solution for technical evaluations on models submitted with offeror proposals, eventually producing the Model-Based Decision Tool (MBDT). The MBDT is built from a Value Hierarchy based on key system requirements, each weighted by priority and measured by their own Single-Dimensional Value Functions (SDVFs). By …
Advances Towards A Robotic Management Vehicle Suited To Nurse Row Crops To More Efficient Outcomes, Adam Mk Gronewold
Advances Towards A Robotic Management Vehicle Suited To Nurse Row Crops To More Efficient Outcomes, Adam Mk Gronewold
Dartmouth College Ph.D Dissertations
Enhancing agricultural production while reducing input costs remains a central challenge in modern row-crop management. Recent advances in computation, imagery, and sensors are enabling more efficient practices across various agricultural domains, and automation technologies are increasingly available to manage tasks central to perennial crop development. Automation in row-crop agriculture, by contrast, lags behind. This thesis explores utilizing small, unmanned ground vehicles to transform row cropping through the implementation of unconventional, in-season management strategies. The first focus of this work considers improvements to nitrogen fertilization using small, autonomous vehicles. An agronomy experiment in corn assessed the effects of gradually applying nitrogen …
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.