Simultaneous Demand Prediction and Planning

Last update: Sep 01, 2022

Related tags

Deep Learning SPAP

Overview

Simultaneous Demand Prediction and Planning

Dependencies

Python packages: Pytorch, scikit-learn, Pandas, Numpy, PyYAML

Data

POI: data/poi
Road network: data/roadnet
Transportation: data/transportation
Station profile: data/station_list
Charging records: data/station
Station profile and charging records can be collected in Star Charge APP.

Experiments

Evaluations of charging demand prediction
python model/run.py --source SOURCE_CITY --target TARGET_CITY --model MODEL_NAME
Evaluations based on real plans
1. Even, CG, Real, TIO: python real_world.py
2. Park: python real_world_parking.py
3. Pop: python real_world_population.py
Evaluations with varied budgets
python evaluation_varied_budget.py
Evaluations with optimal solution
python optimal_comparison_BF_tio.py

Owner

Yizong Wang

GitHub Repository

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Simultaneous Demand Prediction and Planning

Related tags

Overview

Simultaneous Demand Prediction and Planning

Dependencies

Data

Experiments

Owner

Yizong Wang

Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022

Lightweight stereo matching network based on MobileNetV1 and MobileNetV2

Creating Multi Task Models With Keras

JstDoS - HTTP Protocol Stack Remote Code Execution Vulnerability

CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images

MvtecAD unsupervised Anomaly Detection

Official PyTorch implementation for "Low Precision Decentralized Distributed Training with Heterogenous Data"

CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes (AAAI2022)

A simple, fully convolutional model for real-time instance segmentation.

Builds a LoRa radio frequency fingerprint identification (RFFI) system based on deep learning techiniques

Reference implementation of code generation projects from Facebook AI Research. General toolkit to apply machine learning to code, from dataset creation to model training and evaluation. Comes with pretrained models.

git《USD-Seg:Learning Universal Shape Dictionary for Realtime Instance Segmentation》(2020) GitHub: [fig2]

Code for "NeRS: Neural Reflectance Surfaces for Sparse-View 3D Reconstruction in the Wild," in NeurIPS 2021

This repo contains the implementation of YOLOv2 in Keras with Tensorflow backend.

Efficient Lottery Ticket Finding: Less Data is More

TensorFlow implementation of Deep Reinforcement Learning papers

The first dataset of composite images with rationality score indicating whether the object placement in a composite image is reasonable.

Trained on Simulated Data, Tested in the Real World

The source code of CVPR 2019 paper "Deep Exemplar-based Video Colorization".

Unofficial implementation of the paper: PonderNet: Learning to Ponder in TensorFlow