Simultaneous Demand Prediction and Planning

Related tags

Deep LearningSPAP
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

  1. Evaluations of charging demand prediction
    python model/run.py --source SOURCE_CITY --target TARGET_CITY --model MODEL_NAME
  2. 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
  3. Evaluations with varied budgets
    python evaluation_varied_budget.py
  4. Evaluations with optimal solution
    python optimal_comparison_BF_tio.py
Owner
Yizong Wang
Hi
Yizong Wang
Tutel MoE: An Optimized Mixture-of-Experts Implementation

Project Tutel Tutel MoE: An Optimized Mixture-of-Experts Implementation. Supported Framework: Pytorch Supported GPUs: CUDA(fp32 + fp16), ROCm(fp32) Ho

Microsoft 344 Dec 29, 2022
Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks"

LUNAR Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks" Adam Goodge, Bryan Hooi, Ng See Kiong and

Adam Goodge 25 Dec 28, 2022
Raster Vision is an open source Python framework for building computer vision models on satellite, aerial, and other large imagery sets

Raster Vision is an open source Python framework for building computer vision models on satellite, aerial, and other large imagery sets (including obl

Azavea 1.7k Dec 22, 2022
Official re-implementation of the Calibrated Adversarial Refinement model described in the paper Calibrated Adversarial Refinement for Stochastic Semantic Segmentation

Official re-implementation of the Calibrated Adversarial Refinement model described in the paper Calibrated Adversarial Refinement for Stochastic Semantic Segmentation

Elias Kassapis 31 Nov 22, 2022
On-device speech-to-intent engine powered by deep learning

Rhino Made in Vancouver, Canada by Picovoice Rhino is Picovoice's Speech-to-Intent engine. It directly infers intent from spoken commands within a giv

Picovoice 510 Dec 30, 2022
Plotting points that lie on the intersection of the given curves using gradient descent.

Plotting intersection of curves using gradient descent Webapp Link --- What's the app about Why this app Plotting functions and their intersection. A

Divakar Verma 2 Jan 09, 2022
Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression

Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression YOLOv5 with alpha-IoU losses implemented in PyTorch. Example r

Jacobi(Jiabo He) 147 Dec 05, 2022
Multispectral Object Detection with Yolov5

Multispectral-Object-Detection Intro Official Code for Cross-Modality Fusion Transformer for Multispectral Object Detection. Multispectral Object Dete

Richard Fang 121 Jan 01, 2023
Training Structured Neural Networks Through Manifold Identification and Variance Reduction

Training Structured Neural Networks Through Manifold Identification and Variance Reduction This repository is a pytorch implementation of the Regulari

0 Dec 23, 2021
A clean and extensible PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners

A clean and extensible PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners A PyTorch re-implementation of Mask Autoencoder trai

Tianyu Hua 23 Dec 13, 2022
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

Super Resolution Examples We run this script under TensorFlow 2.0 and the TensorLayer2.0+. For TensorLayer 1.4 version, please check release. 🚀 🚀 🚀

TensorLayer Community 2.9k Jan 08, 2023
Simultaneous NMT/MMT framework in PyTorch

This repository includes the codes, the experiment configurations and the scripts to prepare/download data for the Simultaneous Machine Translation wi

<a href=[email protected]"> 37 Sep 29, 2022
Fast image augmentation library and easy to use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about library: https://www.mdpi.com/2078-2489/11/2/125

Albumentations Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to inc

11.4k Jan 09, 2023
Code For TDEER: An Efficient Translating Decoding Schema for Joint Extraction of Entities and Relations (EMNLP2021)

TDEER (WIP) Code For TDEER: An Efficient Translating Decoding Schema for Joint Extraction of Entities and Relations (EMNLP2021) Overview TDEER is an e

Alipay 6 Dec 17, 2022
A scikit-learn compatible neural network library that wraps PyTorch

A scikit-learn compatible neural network library that wraps PyTorch. Resources Documentation Source Code Examples To see more elaborate examples, look

4.9k Jan 03, 2023
Scalable machine learning based time series forecasting

mlforecast Scalable machine learning based time series forecasting. Install PyPI pip install mlforecast Optional dependencies If you want more functio

Nixtla 145 Dec 24, 2022
An executor that performs image segmentation on fashion items

ClothingSegmenter U2NET fashion image/clothing segmenter based on https://github.com/levindabhi/cloth-segmentation Overview The ClothingSegmenter exec

Jina AI 5 Mar 30, 2022
AITom is an open-source platform for AI driven cellular electron cryo-tomography analysis.

AITom Introduction AITom is an open-source platform for AI driven cellular electron cryo-tomography analysis. AITom is originated from the tomominer l

93 Jan 02, 2023
Implement some metaheuristics and cost functions

Metaheuristics This repot implement some metaheuristics and cost functions. Metaheuristics JAYA Implement Jaya optimizer without constraints. Cost fun

Adri1G 1 Mar 23, 2022
CoSMA: Convolutional Semi-Regular Mesh Autoencoder. From Paper "Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes"

Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes Implementation of CoSMA: Convolutional Semi-Regular Mesh Autoencoder arXiv p

Fraunhofer SCAI 10 Oct 11, 2022