Geraldine-Winston / Modeling-Coastal-Erosion-using-RNNs-and-shoreline-satellite-data.Links
This project uses Recurrent Neural Networks (RNNs) to model and predict coastal shoreline changes over time. By training on historical satellite-derived shoreline data, the framework forecasts future erosion trends, supporting coastal management and mitigation strategies. It demonstrates the potential of deep learning in environmental monitoring…
☆28Updated 7 months ago
Alternatives and similar repositories for Modeling-Coastal-Erosion-using-RNNs-and-shoreline-satellite-data.
Users that are interested in Modeling-Coastal-Erosion-using-RNNs-and-shoreline-satellite-data. are comparing it to the libraries listed below
Sorting:
- ☆23Updated 8 months ago
- ☆22Updated 8 months ago
- ☆23Updated 8 months ago
- This project uses LSTM networks to predict reservoir properties like porosity from sequential well log data, enabling improved reservoir …☆27Updated 7 months ago
- Geraldine-Winston / Prediction-of-Vector-Borne-Disease-Spread-e.g.-Malaria-under-climate-scenarios-using-ML.☆22Updated 8 months ago
- ☆19Updated 8 months ago
- pchukwuemeka424 / Using-GIS-and-machine-learning-to-monitor-sandbars-along-the-Niger-River-in-the-Niger-Delta-Nigeria.This project uses Geographic Information Systems (GIS) and machine learning to monitor sandbars along the Niger River in Nigeria's Niger …☆36Updated 8 months ago
- A desktop app for hospital operations including patient registration, billing, appointment scheduling, and report generation. Uses SQLite…☆35Updated 8 months ago
- A WhatsApp bot designed to provide Nigerian farmers with real-time agricultural information including weather forecasts, crop prices, pe…☆23Updated 7 months ago
- ☆24Updated 9 months ago
- ☆36Updated 9 months ago
- ☆23Updated 8 months ago
- ☆23Updated 8 months ago
- This project aims to build accurate and scalable demand forecasting models for e-commerce and retail businesses☆32Updated 8 months ago
- This Python-based project leverages machine learning to predict air quality levels using synthetic pollutant data, simulating real-world …☆36Updated 10 months ago
- Analyze telecom customer data to predict churn. Implement preprocessing pipelines, feature engineering, and classification algorithms (Lo…☆35Updated 8 months ago
- Develop a frontend JavaScript tool that checks password complexity, entropy, and compliance with best practices. Use zxcvbn.js or a custo…☆37Updated 8 months ago
- Scrape Twitter data using Tweepy, preprocess using NLTK or spaCy, and apply sentiment classification using a pretrained transformer (e.g.…☆35Updated 8 months ago
- Build a chatbot that answers user queries in a specialized domain (e.g., health, law, or climate change). Uses OpenAI’s GPT API and is de…☆42Updated 8 months ago
- ☆37Updated 11 months ago
- ☆26Updated 8 months ago
- Use ARIMA, SARIMA, and Facebook Prophet to forecast inflation trends and food price changes in Nigeria. Include seasonal decomposition, r…☆35Updated 8 months ago
- ☆37Updated 11 months ago
- Use supervised classification methods (SVM/Random Forest) and Google Earth Engine (GEE) to classify land cover for a specific region (e.g…☆35Updated 8 months ago
- This project uses reinforcement learning to optimize renewable energy grid operations, balancing energy demand, solar and wind generation…☆37Updated 7 months ago
- ☆19Updated 8 months ago
- Create a simulated ransomware that encrypts user files and displays a decryption notice (for learning and training only). Demonstrates en…☆43Updated 8 months ago
- ☆19Updated 8 months ago
- A full-stack app to manage to-do lists with real-time sync and user authentication.☆36Updated 8 months ago
- Aggregate data from APIs like VirusTotal, AlienVault OTX, and display Indicators of Compromise (IOCs), threat scores, and attack campaign…☆43Updated 8 months ago