ruiluhuang

Ebook-An_introduction_to_robust_optimization

loggibud

Real-world benchmarks for urban delivery problems, including vehicle routing and facility location problems.

CEEMDAN-VMD-GRU

CEEMDAN-VMD-LSTM Forecasting model (a light version of CEEMDAN_LSTM)

Multivariate-multi-step-time-series-forecasting-via-LSTM

多元多步时间序列的LSTM模型预测——基于Keras

CEEMDAN-LSTM

Paper-Reproduce: (ESWA) Forecasting the realized volatility of stock price index: A hybrid model integrating CEEMDAN and LSTM

TimeSeries-Seq2Seq-deepLSTMs-Keras

This project aims to give you an introduction to how Seq2Seq based encoder-decoder neural network architectures can be applied on time series data to make forecasts. The code is implemented in pyhton with Keras (Tensorflow backend).

Distributionally-Robust-Optimization-Notes

Notes for Distributionally Robust Optimization (DRO) 分布鲁棒优化学习笔记

CCG-and-Benders-Case-for-Two-stage-Robust-Optimization

复现经典论文《Solving two-stage robust optimization problems using a column-and-constraint generation method》算例

facility-location-gurobi

Exact approach to solve the facility location problem with Gurobi.

Time-Series-Demand-Forecasting

Time-series demand forecasting is constructed by using LSTM, GRU, LSTM with seq2seq architecture, and prophet models.

OR_location_routing_problem_study

Facility Location and routing problems: Survey, Models and Algorithm

Facility-Location-in-Genetic-Algorithm

This project use genetic algorithm to solve the facility location problem in matlab.

Data-Driven-Optimization

A repository holding methods from data-driven-optimization used in data science and operations research including sample average approximations, bandit problems, robust optimization, stochastic optimization and reinforcement learning.

IEEE-08390898

Some codes of the paper: "Planning fully renewable powered charging stations on highways: a data-driven robust optimization approach"

Facility_Location

This repository contains resources for Facility Location and Location Allocation. It is intended for research and educational use. Nothing within this repository may be used for commercial activities.

Robust-Optimization-using-Machine-Learning-for-building-Uncertainty-Sets

Built uncertainty sets for demand forecasting of Hubway bikes and solved the optimization problem of bike rebalancing within stations.

Univariate-Time-Series-using-LSTM

Advanced-Time-series-analysis

Advance Time Series Analysis using Probabilistic Programming, Auto Regressive Neural Networks and XGBoost Regression.

Multi-Step-Time-Series-Prediction-using-RNN-LSTM-for-household-power-consumption

Household Power Consumption Prediction using RNN LSTM

Uncertainty-Modeling-and-Optimization

Notes for Robust Optimization.

Ang-Xuan-Statistical-model-machine-learning-model-and-deep-learning-model

Statistical model, machine learning model and deep learning model Arima, Sarima and Lasso codes for statistical ANN, Decision Tree and GBDT for machine learning CNN, RNN, LSTM for deep learning

flu_multistep_prediction

This repository contains the Comprehensive Learning Particle Swarm Optimization based Machine Learning(CLPSO-ML) framework, incorporating two ML methods(SVR & MLP) and three multi-step-ahead strategies(iterated strategy, direct strategy and MIMO strategy), for multi-step-ahead influenza prediction.

robust_optimization

LSTM-SPP

A Simple Multi-Variate, Multi-Step LSTM Stock Price Prediction Model in Python.

Patient_Admission_Scheduling_Optimization

Optimizing the patient admission scheduling plan to minimize all cost and waiting time

Stock-Market-Analysis-Prediction-Model

Stock data importing from Yahoo and Tiingo, resampling in terms of quarters, months, weeks, constructing moving windows, checking volatility of stocks, rolling means, comparing performances of different stocks using subplots, data preprocessing, model building with deep learning and predicting stock prices for future.

Robust-Optimization

Parameter_Prediction_WSN

Evaluation of Machine Learning Models such as Linear Regression, Decision Tree, XGBoost, Random Forest, SVR, KNN, LSTM, and MLP based on performance metrics such as RMSE, R2, MSE, and MAE for Parameter Prediction in Wireless Sensor Netwroks

Project-Earthquake-prediction

Using Deep learning model Simple MLP we are using rolling window concept to predict the earthquakes

MultStepTimeSeries

A repository for multivariate multi-step time series prediction