Dynamic pricing has become increasingly common in event ticketing and entertainment, where prices adapt to exogenous signals such as date, demand, and weather. Accurately forecasting prices under user-specified conditions benefits both consumers and operators. We present a web-based price-prediction tool that couples a simple, task-focused user interface with a PHP–Laravel backend. Users provide contextual inputs—date, meteorological conditions, and personal preferences—while the backend orchestrates data access, feature engineering, and a machine-learning model to return a price estimate. The development process encompassed requirements elicitation, data preparation, model training and evaluation, interface design, and full-stack integration. The resulting system enables users to explore “what-if” scenarios and obtain actionable price forecasts, supporting planning and decision-making.
La dynamic pricing è diventata sempre più comune nel settore della biglietteria per eventi e dell'intrattenimento, dove i prezzi si adattano a segnali esogeni come data, domanda e condizioni meteorologiche. Prevedere accuratamente i prezzi in base a condizioni specificate dall’utente apporta benefici sia ai consumatori sia agli operatori. Presentiamo uno strumento web-based di previsione dei prezzi che combina un’interfaccia utente semplice e orientata al compito con un backend PHP–Laravel. Gli utenti forniscono input contestuali—data, condizioni meteorologiche e preferenze personali—mentre il backend gestisce l’accesso ai dati, la feature engineering e un modello di machine learning per restituire una stima del prezzo. Il processo di sviluppo ha coinvolto la raccolta dei requisiti, la preparazione dei dati, l’addestramento e la valutazione del modello, la progettazione dell’interfaccia e l’integrazione full-stack. Il sistema risultante consente agli utenti di esplorare scenari ipotetici (“what-if”) e ottenere previsioni di prezzo utili, supportando la pianificazione e il processo decisionale.
Web Application for Price Prediction
NAZIRI ALHASHEM, SEYEDEH SARA
2024/2025
Abstract
Dynamic pricing has become increasingly common in event ticketing and entertainment, where prices adapt to exogenous signals such as date, demand, and weather. Accurately forecasting prices under user-specified conditions benefits both consumers and operators. We present a web-based price-prediction tool that couples a simple, task-focused user interface with a PHP–Laravel backend. Users provide contextual inputs—date, meteorological conditions, and personal preferences—while the backend orchestrates data access, feature engineering, and a machine-learning model to return a price estimate. The development process encompassed requirements elicitation, data preparation, model training and evaluation, interface design, and full-stack integration. The resulting system enables users to explore “what-if” scenarios and obtain actionable price forecasts, supporting planning and decision-making.| File | Dimensione | Formato | |
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NaziriAlhashem_SeyedehSara.pdf
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https://hdl.handle.net/20.500.12608/99597