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Papers tagged with "Forecasting"
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 Survey On Machine Learning And Deep Learning Models For Predicting Traffic Transit Time
The Transition Towards Intelligent Traffic Systems (ITS) Is Inevitable In Future. Accurate Travel Time Estimation Is Vital For The Effectiveness Of Modern Public Transportation Systems. It Plays A Central Role In Applications Such As Real-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...
BUSINESS INTELLIGENCE: A WEB-BASED BUSINESS INTELLIGENCE SYSTEM FOR REAL-TIME RETAIL ANALYTICS, DEMAND FORECASTING, AND RISK MANAGEMENT
Small And Medium Retail Businesses Frequently Face Operational Difficulties Related To Inventory Management, Stock Monitoring, Demand Estimation, And Financial Reporting. Most Shop Owners Rely On Manual Records Or Entry-level Billing Softwa...
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...
Multi-Feature Search–Based Purchasing Tendency Community Classification For Densely Distributed Clients In E-commerce
Purchasing Tendency Is Defined As Customer Prefer-ences For Products And Brands, Interested In Price And Frequency Of Purchase, And Is Determined By Demographic, Transactional And Behavioral Attributes. In Today’s E-commerce, These Insights...
CONSEQUENCE INTELLIGENCE ENGINE FOR PREDICTING DECISION IMPACT IN COMPLEX SYSTEMS
Strategic Decision-making In Complex Organizational Environments Is Inherently Associated With Risk And Uncertainty. Despite Widespread Adoption Of Decision Support Systems, Most Existing Tools Focus On Structuring Decisions Rather Than Pre...
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...
AI-BASED ENERGY MANAGEMENT SYSTEM
The Rapid Growth Of Energy Demand, Increasing Electricity Costs, And The Need For Sustainable Power Utilization Present Significant Challenges To Traditional Energy Management Practices. This Paper Presents An AI-Based Smart Energy Manageme...
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...
Street Level Travel Time Estimation Employing WBPST-SVR Model Using GTFS Feature
Accurate Estimation Of Street-level Travel Time Is A Fundamental Requirement For Intelligent Transportation Systems (ITS), Enabling Effective Traffic Management, Route Optimization, And Real-time Traveler Information Services. With The Incr...
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...