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A Comprehensive Study Of Machine Learning (ML) Algorithms And Performance Evaluation: Enhancing The Credit Card Fraud Detection
Credit Card Companies Must Be Able To Identify Fraudulent Credit Card Transactions So That Clients Are Not Charged For Items They Did Not Purchase. Previously, Many Machine Learning Approaches And Classifiers Were Used To Detect Fraudulent...
AgroNGO: A Machine Learning–Enabled Platform For Farm-to-Consumer Commerce And Sustainable Food Redistribution
A Major Challenge That The Agriculture Supply Chain Is Facing In India Is The Lack Of Technology. Fragmented With Large Losses In Food Post Harvest, Lowering Farmers' Income, Poor Food Availability For Low-income Groups. This Paper Outlines...
Intelligent Learning Outcome Prediction Using Machine Learning Techniques
Student Performance Prediction Is An Important Application Of Educational Data Mining That Helps Institutions Identify Students Who May Require Academic Support At An Early Stage. This Study Proposes A Classification-based Approach To Predi...
Hybrid Machine Learning Model For Multi-Diseases Diagnosis
Co-occurring Chronic Conditions And Complex Multi-disease Pathologies Represent An Escalating Global Public Health And Socioeconomic Crisis. In Rapidly Growing Urban Patient Populations, Overlaps Between Metabolic, Cardiovascular, And Neuro...
BIKE PRICE PREDICTION SYSTEM USING MACHINE LEARNING
The Valuation Of Used Consumer Assets, Particularly Pre-owned Two-wheeled Vehicles, Remains A Major Secondary-market And Socioeconomic Challenge. In Rapidly Developing Urban Transport Ecosystems, Frequent Fluctuations In Marketplace Deman...
AI-Powered Diagnosis Of Vision-Threatening Ocular Conditions Using Clinical Data Analytics
Vision-threatening Ocular Diseases Such As Diabetic Retinopathy, Glaucoma, Cataract, Age-related Macular Degeneration (AMD), Hypertensive Retinopathy And Pathological Myopia Are Leading Causes Of Preventable Blindness Worldwide. Conventiona...
Predictive Power Machine Learning Models For Machine Failure Status
Predictive Maintenance Has Emerged As A Cornerstone For Maximizing Operational Efficiency And Minimizing Unexpected Machine Breakdowns In Industrial Environments. This Paper Presents An Integrated End-to-end Machine Learning Framework For F...
AI-Powered Intelligent Framework For Detection And Prevention Of Cybersecurity Attacks Using Machine Learning Algorithms
The Rapid Growth Of Digital Technologies Has Substantially Increased Exposure To Cybersecurity Threats Including Malware, Phishing, Ransomware, And Unauthorized Network Intrusions. Traditional Signature-based Security Systems Are Inherently...
AI-BASED PREDICTIVE MODELING FOR CLASSIFICATION OF FETAL HEALTH CONDITIONS
Fetal Health Assessment Is A Critical Component Of Prenatal Care, Directly Influencing The Safety And Outcomes Of Both Mother And Fetus During Pregnancy. Conventional Diagnostic Approaches, Which Rely Heavily On Manual Interpretation Of Car...
SMART USED VEHICLE PRICE PREDICTION AND MARKET SYSTEM
The Used Vehicle Market Has Experi- Enced Significant Growth In Recent Years, Making It Challenging For Buyers And Sellers To Determine Accurate Vehicle Prices. Traditional Pricing Meth- Ods Often Rely On Personal Judgment, Which May Lead T...
REAL –TIME AI INTRUSION DETECTION SYSTEM USING MACHINE LEARNING
The Relentless Escalation Of Cyber Threats In Contemporary Network Environments Has Necessitated A Fundamental Rethinking Of Intrusion Detection Methodologies. Traditional Signature-based Systems, While Once Sufficient, Have Proven Structur...
Explainable Ensemble Machine Learning Framework For Heart Disease Prediction
Heart Disease Is One Of The Leading Causes Of Death Worldwide, And Early Prediction Plays An Important Role In Reducing Severe Health Risks. Traditional Diagnostic Methods Such As ECG, Blood Tests, And Imaging Require Expert Interpretation,...
Hybrid Adaptive Sampling With Risk-Based Credit Card Fraud Detection (HAS-RFD)
Credit Card Fraud Has Become A Significant Challenge In The Digital Economy, Resulting In Substantial Financial Losses And Reduced Trust In Online Transactions. This Paper Presents A Hybrid Adaptive Sampling With Risk-Based Fraud Detection...
RANDOM FOREST REGRESSION APPROACH FOR CROP YIELD ESTIMATION USING SENTINEL- 1 SAR, LULC, CLIMATE DATA
Crop Yield Estimation Plays A Major Role In Agricultural Planning And Food Security. Traditional Methods Of Crop Yield Estimation Are Time-consuming And Require Extensive Field Surveys. This Study Focuses On Estimating Rice Crop Yield Using...
AI-Based Supply Chain Risk Prediction System Using Machine Learning
Supply Chain Systems Are Highly Vulnerable To Disruptions Caused By Factors Such As Transportation Delays, Traffic Congestion, Weather Conditions, And Inventory Fluctuations. Traditional Risk Assessment Methods Are Largely Manual, Time-cons...