✈️ KOU Airlines - Dynamic Pricing Backend

KOU Airlines Backend is a reservation system for an airline company. It is built with Spring Boot and PostgreSQL.

The most important feature of this project is the Dynamic Pricing Engine. It uses Fuzzy Logic (Artificial Intelligence) to calculate ticket prices automatically based on real-time data.

---

🚀 Key Features

🧠 1. Smart Dynamic Pricing

Standard systems use simple rules (if-else). This project uses Fuzzy Logic (.fcl files) to make smarter decisions, like a human manager.

• It analyzes: How many days are left, how full the plane is, and the time of the flight.
• It decides:
  • If the plane is full or it is a busy day (like Monday morning), the price goes UP.
  • If it is a night flight (03:00 AM) and empty, the price goes DOWN.

🛠 2. Flight & Booking Management

• Management: You can create and edit flights, airports, and routes.
• Soft Delete: When we cancel a flight or ticket, we do not delete it from the database permanently. We mark it as "passive" to keep the data safe for reports.
• Seat Safety: The system prevents two people from buying the same seat at the same time.

📅 3. Special Days & Seasons

• The system knows holidays, festivals, and special days.
• It automatically increases prices for specific dates or countries during these times.

🔔 4. Notifications & Security

• Email: When a user buys or cancels a ticket, the system sends an automatic email with flight details.
• Security: Sensitive data (like ID numbers) is hashed and saved securely in the database.

---

🏗 Tech Stack

Technology	Usage
Java 17+	Main Programming Language
Spring Boot 4	Backend Framework (Web, Data JPA)
PostgreSQL	Database
jFuzzyLogic	Library for Fuzzy Logic calculations
Hibernate / JPA	Database connection and management
Lombok	To write less code (cleaner code)

---

🧩 How the Pricing Logic Works

The system uses a logic file (DynamicPricing.fcl) to calculate the price. Here is the process:

1. Inputs (Fuzzification):

   • daysToDeparture: Is the flight soon? (Short term vs Long term)
   • occupancyRate: Is the plane empty or full?
   • dayScore: Is it a popular day? (Friday is popular, Tuesday is not)
   • timeScore: Is it a popular hour? (09:00 AM is popular, 03:00 AM is not)
   • specialDays: The system knows holidays, festivals, and special days.

2. Rules (Inference):

   • Example: IF the flight is very soon AND the plane is full, THEN increase the price significantly.
   • Example: IF it is late night AND the plane is empty, THEN give a discount.

3. Result (Defuzzification):

   • The system calculates a Multiplier (e.g., 1.2 or 0.8).
   • Final Price = Base Price * Multiplier.

---

📞 Contact

Developer: Murat Ertik

Email: dmuratertik1@gmail.com

LinkedIn: www.linkedin.com/in/murat-ertik

This project was developed as a Senior Design Project at Kocaeli University (KOÜ).