With the acceleration of globalization and human activities, marine ecosystems are facing unprecedented pressure. To address this ecological crisis and promote the conservation and sustainable development of marine biodiversity, we have developed a Marine Species Population Dynamics Prediction Platform based on relational database technology. This platform aims to provide researchers, policymakers, and the public with a comprehensive service that integrates data filtering, querying, evaluation, and prediction.

• Data Collection & Input: Supports diverse data sources, including biological records, measurements, datasets, accepted species, and sequences. Administrators can input and update key ecological data.
• Data Maintenance & Cleaning: Regular updates and validation ensure data accuracy and timeliness.
• Data Access Control: Role-based access management ensures secure data storage and access.

• Data Filtering & Search: Researchers can filter and search data based on various criteria.
• Trend Analysis: Utilize statistical and deep learning techniques to analyze changes in marine species populations.
• Data Visualization: Use AMap (Gaode) API for visual representation of species' geographical locations.

• Query Interface: Users can query specific species information.
• User Feedback: Users can evaluate and rate marine species, enhancing platform interactivity and educational value.
• Education & Awareness: Publish news on endangered species and extreme marine environments to raise public awareness.

• Research Prediction: Scientists can input parameters for time-series predictions using an LSTM model, and view results as charts for further research and publication.

• Permission Management: Administrators can manage user accounts, including enabling/disabling accounts and upgrading/downgrading roles.
• Content Management: Admins can review, edit, or delete posts and manage marine data.

• Frontend: Vue.js, Element UI
• Backend: Flask, MySQL
• Data Visualization: AMap (Gaode) API
• Tools: PyCharm, HBuilder X, Navicat Premium

• Node.js
• Python 3.8
• MySQL 8.0

1. Clone the repository:

   git clone /~https://github.com/your-repo/marine-prediction-platform.git
   cd marine-prediction-platform

2. Backend Setup:

   • Navigate to the backend directory:

     cd backend

   • Install dependencies:

     pip install -r requirements.txt

   • Set up the database:

     mysql -u root -p < sea.sql

   • Run the backend server:

     python app.py

3. Frontend Setup:

   • Navigate to the frontend directory:

     cd ../frontend

   • Install dependencies:

     npm install

   • Run the frontend server:

     npm run serve

4. Access the Platform: Open your browser and go to http://localhost:10001/ to start using the Marine Species Population Dynamics Prediction Platform.

Welcome to make contributions to enhance the platform. Please fork the repository and submit pull requests for review.

This project is licensed under the MIT License. See the LICENSE file for details.