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Papers tagged with "Series"
ProcureAi: An AI-Driven Procurement Spend Intelligence Platform For Automated Anomaly Detection, Supplier Optimisation And Predictive Expenditure Forecasting
- Enterprises Routinely Lose Between Three And Eight Percent Of Addressable Procurement Spend To Fragmentation, Duplicate Payments, Maverick Buying, Contract Price Leakage, And Unmanaged Tail Spend. This Paper Presents ProcureAI, A Full-sta...
A Comprehensive Review On Machine Learning And Deep Learning Models For Forecasting Stock Market Trends
Machine Learning Is Transforming Stock Market Prediction By Leveraging Vast Datasets, Advanced Algorithms, And Computational Power To Provide More Accurate Forecasts. While Challenges Remain, Continuous Advancements In Artificial Intelligen...
A Deep Learning Approach For Predicting Crypto Currency Prices Trends
Machine Learning And Deep Learning Models Are Being Extensively Used At The Backend Of Forecasting Crypto Prices. Many Factors, Including Changes In Regulation, Public Opinion On Social Media, Investor Actions, And Overall Global Economic T...
A Comprehensive Review On Contemporary Machine Learning And Deep Learning Models For Forecasting Stock Market Trends
Machine Learning Is Transforming Stock Market Prediction By Leveraging Vast Datasets, Advanced Algorithms, And Computational Power To Provide More Accurate Forecasts. While Challenges Remain, Continuous Advancements In Artificial Intelligen...
Design And Development Of A Series Regulated Integrated Starter Generator (ISG) Controller With Diagnostic Features
Modern Automotive Systems Require Efficient Electrical Power Generation And Management Due To Increasing Electrical Loads And Stringent Emission Regulations. Conventional Vehicles Utilize Separate Starter Motors And Alternators For Engine C...
AI-Driven Price Prediction System For Direct Farmer-to- Market Consumer Agricultural Market
Farmers Who Sell Directly To Consumers Through Digital Platforms Often Have No Idea What Price To Charge For Their Produce. They Rely On Heuristic Judgment And Informal Market Signals, Or Whatever Their Neighbor Charged Last Week. This Leav...
A STUDY ON SALE AND DEMAND FORCASTING USING TIME SERIES ANALYSIS IN A TEXTILE MANUFACTURING COMPANY
Accurate Sales And Demand Forecasting Is A Strategic Imperative For Textile Manufacturing Enterprises Operating In Volatile, Seasonally Driven Markets. This Study Applies Time Series Analysis To Historical Sales And Demand Data (2022–2025)...
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...
Live Cryptocurrency Market Dashboard With Machine Learning-Based Price Prediction And RSI Signal Generator
Cryptocurrency Markets Are Highly Volatile And Change Rapidly, Which Makes Price Prediction And Decision- Making Difficult For Investors. This Project Presents A Live Cryptocurrency Market Dashboard That Provides Real-time Market Visualizat...
IoT-Enabled Unified Gas Safety Management System
Gas Leaks Are A Real Threat—one That Puts Lives, Property, And Industries At Constant Risk. Fires, Explosions, Toxic Exposure, Even Simple Kitchen Accidents Trace Back To Leaks That Go Unnoticed For Just A Few Minutes. The Old Ways Of Handl...
ENHANCING STOCK PRICE FORECASTING ACCURACY USING COMPOSITIONAL RNN
Predicting Stock Prices Accurately Is Essential For Making Well-informed Decisions In Erratic Financial Markets. This Paper Introduces A Compositional Deep Learning Framework For Multivariate Time-series Forecasting That Integrates Three RN...
An Intelligent Hybrid GCN-LSTM Model For Energy Stock Price Forecasting With Temporal Dynamics And Inter-Stock Correlation
Energy Sector Stock Price Prediction Is A Critical Yet Challenging Task In Financial Forecasting, Characterized By High Volatility, Non-linearity, And Complex Interdependencies Driven By Geopolitical Events, Regulatory Shifts, And Commodity...
AQI Index Analyzer Using Machine Learning
Air Quality Index AQI Prediction Is A Critical Public Health Task That Involves Leveraging Data-driven Methods To Forecast Pollutant Concentrations And The Resulting AQI Under Dynamic Environmental And Meteorological Conditions1. This R...
SYNETHETIC TIME SERIES GENERATOR FOR ANAMOLY DETECTION
Industries Increasingly Depend On Continuous Monitoring Systems Where Fast And Accurate Anomaly Detection Is Crucial For Preventing Failures And Ensuring Operational Reliability. This Project Proposes A Lightweight Python-based Synthetic Ti...