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Papers tagged with "Predict"
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...
Enhancing The Recommendation Model For Disease Prediction Based On User Symptoms Using Machine Learning
Healthcare Is One Of The Most Important Research Fields With The Rapid Improvement Of Technology And Increase In Data. It Is Difficult To Handle Huge Amounts Of Patient Data. Big Data Analytics Can Be Used To Handle Such Data. There Are A L...
Customer Sales Predication Using Artifical Intelligence
Customer Churn Prediction Is An Important Research Problem In Business Analytics That Helps Organizations Identify Customers Who Are Likely To Discontinue Their Services. This Paper Proposes A Machine Learning-based Churn Prediction Framewo...
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,...
AI Based Cyber Threat Prediction
The AI-Based Cyber Threat Prediction System Improves Cybersecurity Using Artificial Intelligence, Machine Learning, And Deep Learning Techniques. The System Continuously Monitors Network Traffic, System Logs, And User Activities To Identify...
BlueFactory Copilot: An Autonomous Multi Agent AI System For Real-Time AGV Swarm Orchestration
Traditional Automated Guided Vehicle (AGV) Systems Rely On Centralized Controllers And Rigid Programming, Causing Collisions, Torque Overloads, And Operational Downtime When Factory Conditions Change. Nobody Checks If An AGV Mission Is Phys...
A HYBRID STOCK PRICE FORECASTING SYSTEM USING ARIMA, LSTM, AND SENTIMENT ANALYSIS
The Accurate Forecasting Of Stock Prices Remains One Of The Most Persistent And Challenging Problems In Quantitative Finance, Owing To The Inherently Noisy, Nonstationary, And Nonlinear Nature Of Financial Time Series. Traditional Foreca...
Intelligence Agent For Network Service And Resource Management
Silent Performance Degradation In Network Systems Is A Critical Operational Challenge Where Servers Gradually Lose Efficiency Without Explicit Failures Or Alarms, Leading To Reduced Reliability, Increased Downtime Risk, And Higher Maintenan...
AI-BIOSENTRY: A DECENTRALIZED IOT-BASED MULTI-MODAL SYSTEM FOR REAL-TIME RIPENESS MONITORING
Agricultural Sustainability Is Challenged By Nearly 40% Post-harvest Losses Due To Inefficient Manual And Destructive Ripeness Testing. Bio-Sentry Is An Advanced, Non-destructive Automated System Designed To Bridge This Gap Through A Multi-...
Digital Twin Driven Hybrid LSTM And Isolation Forest Framework For Predictive Failure Detection And Autonomous Self Healing In Servers
Cloud Server Infrastructures Form The Foundation For Technical Services, Where The Services Will Be Highly Available, Critical For Business Continuity And User Satisfaction. Traditional Systems Notify The User After The Failures Had Occurre...
AI-Powered Inventory Management System- Ezze Buy
This Paper Presents The Design, Architecture, And Full-stack Implementation Of EzzeBuy, A Web-based AI-powered Inventory Management And Sales Prediction Platform. The System Integrates A Long Short-Term Memory (LSTM) Neural Network Backend...
Inductive Based Industrial Automation
Unanticipated Machinery Failures In Industrial Environments, Arising From Overheating, Excessive Vibration, Electrical Faults, Or Fire, Can Result In Severe Equipment Damage, Operational Downtime, And Safety Hazards. This Study Presents A N...
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...
Smart AI – Powered Health Care System
- This Paper Presents A Smart AI-Based Healthcare System Designed To Enhance Disease Prediction And Support Clinical Decision-making Using Machine Learning Techniques. The System Analyzes Patient Data Such As Symptoms, Medical History, And...