Android Flight Price Prediction Web-Based Platform: Leveraging Generating AI for Real-Time Airfare Forecasting
Authors:-Mrs. M. Mani Deepika, P. Nasivi Ramya Anjani, V. Sai Jyothika Chowdary, Y. Anitha Chowdary, M. Swarna, K.Vamsika
Abstract-The aviation industry faces significant challenges in accurately and swiftly predicting flight fares due to the sector’s dynamic nature. Factors such as fluctuating demand, fuel prices, and route complexities contribute to this unpredictability. To address these issues, this research introduces a novel approach leveraging generative artificial intelligence (GAI) to forecast airfares in real time with high precision. The proposed framework integrates generative models, deep learning architectures, and historical pricing data to enhance predictive accuracy. Utilizing GAI within an advanced web engineering framework, this method effectively captures intricate patterns and relationships within historical airline data. By employing deep neural networks, the model efficiently processes diverse scenarios, extracting critical insights to improve the understanding of key factors influencing flight costs. Furthermore, the approach prioritizes real-time forecasting, enabling rapid adaptation to market fluctuations and providing valuable insights for dynamic pricing strategies.
