yuquandu / Data-driven-Ship-Fuel-Efficiency-ModelingLinks
This projects adopts machine learning models to quantify the daily/hourly bunker fuel consumption of a ship in different sailing speed, displacement/draft, trim, weather, and sea conditions. The industry data utilized include voyage report data, sensor data, AIS data, and meteorological data. Apart from Python code, here, we also share 130 train…
☆32Updated 3 years ago
Alternatives and similar repositories for Data-driven-Ship-Fuel-Efficiency-Modeling
Users that are interested in Data-driven-Ship-Fuel-Efficiency-Modeling are comparing it to the libraries listed below
Sorting:
- Modeling ship performance curves to reduce fuel consumption☆24Updated 2 years ago
- This project use genetic algorithm to solve the facility location problem in matlab.☆23Updated 7 years ago
- Modelling marine traffic in the ice-covered Baltic Sea using AIS data☆77Updated 5 years ago
- Implementation of Non-dominated Sorting Genetic Algorithm (NSGA-II), a Multi-Objective Optimization Algorithm in Python☆48Updated 7 years ago
- SIMROUTE: Weather Ship Routing (WSR) Code. The software is constructed considering available Copernicus Marine Environment Monitoring Ser…☆62Updated 4 months ago
- Solar energy power generation, we need to predict the production of solar photovoltaic(PV). And the dataset contains attributes like temp…☆24Updated 3 years ago
- Clustering of Taxi Trajectories☆11Updated 7 years ago
- Spatio Temporal DBSCAN algorithm in Python. Useful to cluster spatio-temporal data with irregular time intervals, a prominent example cou…☆35Updated 5 years ago
- ☆44Updated 4 years ago
- N. Singh and S. Singh, "Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Improving Convergence Performance", J…☆25Updated 3 years ago
- Complementary Jupyter notebooks for load forecasting tutorial.☆12Updated 5 years ago
- Capacitated Vehicle Routing Problem with Time Windows (NP-Hard). Winner at ICHack 18.☆29Updated 7 years ago
- We propose Compressive Sensing and Deep Learning framework (CS-DL) for multiple satellite sensor based data fusion. It’s aims to improve …☆24Updated 4 years ago
- optimizing locations of electric vehicle charging stations in the city of Toronto☆30Updated 2 years ago
- LSTM Keras Neural Network to predict ship location using Danish AIS data☆49Updated 6 years ago
- Heuristic global optimization algorithms in Python☆56Updated 4 years ago
- This repository contains Evolutionary Algorithms that can be used for multi-objective optimization. Interactive optimization is supported…☆12Updated last year
- Electric Vehicle Routing Problem☆33Updated 4 years ago
- 交通分配☆25Updated 5 years ago
- Proposed a mathematical model for optimizing the profits and emissions while setting dynamic prices of electricity. A bilevel & multi-obj…☆22Updated 3 years ago
- This is a standalone version of MO-ASMO, a surrogate based multi-objective optimization algorithm.☆22Updated 6 years ago
- ☆16Updated 3 years ago
- Finding the optimal location for public charging stations – a GIS based MILP approach☆16Updated 3 years ago
- Probabilistic Deep Learningfor Electric-Vehicle Energy-Use Prediction☆22Updated 3 years ago
- Predicting the energy consumption of EVs using the RNN and LSTM. Competencies: Machine Learning, RNN, SUMO Simulation. Python Libraries: …☆18Updated 4 years ago
- EVQUARIUM is an evaluation tool that quantifies the accessibility of EV charging station locations using queueing and graph theory. Given…☆19Updated 2 years ago
- Grey Wolf Optimizer Matlab☆66Updated last year
- Multi-Objective Grey Wolf Optimizer☆16Updated 2 years ago
- Predicting solar energy using machine learning (LSTM, PCA, boosting). This is our CS 229 project from autumn 2017. Report and poster are …☆65Updated 4 years ago
- multi-objective optimization, single-objective optimization and reinforcement learning in the field of ensemble learning and time series …☆24Updated last year