Bike-Sharing | Journey planning algorithms for multi-modal transportation

by kit-algo C++ Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | Bike-Sharing Summary

Bike-Sharing is a C++ library. Bike-Sharing has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

This C++ framework contains several algorithms for the efficient computation of shortest paths in multi-modal transportation networks. All algorithms and data structures have a special focus on handling bike-sharing services and bike sharing stations present in the network. The framework was developed at KIT in the group of Prof. Dorothea Wagner.

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Support

Bike-Sharing has a low active ecosystem.

It has 5 star(s) with 0 fork(s). There are 5 watchers for this library.

It had no major release in the last 6 months.

Bike-Sharing has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Bike-Sharing is current.

Quality

Bike-Sharing has no bugs reported.

Security

Bike-Sharing has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Bike-Sharing is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Bike-Sharing releases are not available. You will need to build from source code and install.

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Bike-Sharing Key Features

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Bike-Sharing Examples and Code Snippets

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Community Discussions

Trending Discussions on Bike-Sharing

How to solve Error when checking input: with incorrect size

ggplot2 error: missing value where TRUE/FALSE needed. I have no idea

Discrepancy between R's Keras and Python's Keras -- Accuracy bug?

loss: nan When build a model for bike sharing

Can someone explain why these two results differ in this simple SQL query?

Group by hour and count MongoDB

Error in function to normalize data applied to a data frame

Linear regression gradient descent algorithms in R produce varying results

Gradient descent algorithm error non-comformable arguments

Error parsing JSON data to an array using GSON

QUESTION

How to solve Error when checking input: with incorrect size

Asked 2020-Jun-02 at 08:13

This is my first attempt to solve task on the kaggle. This is page of the task - https://www.kaggle.com/c/bike-sharing-demand. I wrote this code (I have some excess code lines, because I am not really sure what I need now):

...

ANSWER

Answered 2020-Jun-02 at 08:13

you specified wrong the input dimension of your model. try to define your first layer in this way

Source https://stackoverflow.com/questions/62140528

QUESTION

ggplot2 error: missing value where TRUE/FALSE needed. I have no idea

Asked 2020-Jan-05 at 00:20

I am taking an online R class in Udemy, here is the code for a Linear regression visualization. I got the error message from the last command. The data from the website about bikesharing: https://www.kaggle.com/c/bike-sharing-demand/data

The data looks like:

...

ANSWER

Answered 2020-Jan-05 at 00:20

If you want to add different colors for different hours you can do

Source https://stackoverflow.com/questions/59589198

QUESTION

Discrepancy between R's Keras and Python's Keras -- Accuracy bug?

Asked 2020-Jan-03 at 17:46

I'm playing with some 2D CNN using Keras to predict Bike Sharing Demand.

R performs very poorly vs Python, which reach good accuracy easily. I thought it was because of arrays shape (and some differences between R and Python), so I play with that for a while, ultimately using all possible shapes.

I created the CombinationGrid object elsewhere and it looks like this:

...

ANSWER

Answered 2020-Jan-03 at 17:46

Well, as Skeydan explained to me in the issue I opened, the difference in accuracy falls in the Keras version used.

In the Python code, changing from import keras to import tensorflow.keras as keras makes the accuracy to match between both R and Python.

I found more information about this here and here.

Source https://stackoverflow.com/questions/59462354

QUESTION

loss: nan When build a model for bike sharing

Asked 2019-Mar-03 at 19:03

I'm new and learning of machine learning, kindly bear with me if the way of asking is not fine and question is so simple.

The issue is my developed model is returning loss as nan, please advice me if anything wrong I made. below are the details.

Program Logic

...

ANSWER

Answered 2019-Mar-03 at 19:03

To prevent your gradient from exploding you can clip it like so.

Source https://stackoverflow.com/questions/54966616

QUESTION

Can someone explain why these two results differ in this simple SQL query?

Asked 2019-Jan-15 at 15:45

I'm re-learning SQL and am currently following this dataquest guide. The data set is taken from the bike-sharing service Hubway, and I'm trying to answer the question: Which stations are most frequently used for round trips?

This question involves two tables:

Stations

Trips

Here's the proposed answer from the guide:

...

ANSWER

Answered 2019-Jan-15 at 15:45

Your query groups on a foreign key, the numeric start_station column:

Source https://stackoverflow.com/questions/54181936

QUESTION

Group by hour and count MongoDB

Asked 2018-Oct-05 at 07:19

I'm on a project working with data of a bike-sharing service. Each trip has the following info

...

ANSWER

Answered 2018-Oct-05 at 07:19

The depDate and depHour fields are all string values that denote the day and the hour respectively so there is no need to use the date operators to convert the fields to date objects, all you need is to extract the hour part using $substrCP and then use them directly as expressions in your $group _id as:

Source https://stackoverflow.com/questions/52639932

QUESTION

Error in function to normalize data applied to a data frame

Asked 2017-Sep-13 at 01:10

I have downloaded the bike-sharing-dataset from the UCI Machine learning repository and am trying to implement a multivariate linear regression in R. Here is the format of the data:

...

ANSWER

Answered 2017-Sep-13 at 00:21

To modify in-place, I'd use dplyr::mutate. Something like this should work:

Source https://stackoverflow.com/questions/46186923

QUESTION

Linear regression gradient descent algorithms in R produce varying results

Asked 2017-Sep-12 at 15:19

I am trying to implement a linear regression in R from scratch without using any packages or libraries using the following data:

UCI Machine Learning Repository, Bike-Sharing-Dataset

The linear regression was easy enough, here is the code:

...

ANSWER

Answered 2017-Sep-12 at 15:19

To give you an example of how to write functions like this in a slightly better way, consider the following:

Source https://stackoverflow.com/questions/46163492

QUESTION

Gradient descent algorithm error non-comformable arguments

Asked 2017-Sep-11 at 17:40

I am trying to perform a linear regression from scratch in R, without using any packages or libraries. The data I am using is:

UCI Machine Learning Repository, Bike-Sharing-Dataset

I must apply a batch update gradient descent algorithm to this regression.

I have composed the following code:

...

ANSWER

Answered 2017-Sep-11 at 17:40

Try the following:

Source https://stackoverflow.com/questions/46160343

QUESTION

Error parsing JSON data to an array using GSON

Asked 2017-Jul-24 at 16:13

Before you assume that this question is a duplicate based on its title, I must say that I couldn't find any solutions out there for my specific problem. However, I'd appreciate it if you could suggest some links! That said, my problem is that I keep getting the following GSON exception:

...

ANSWER

Answered 2017-Jul-24 at 16:11

You cannot convert your jsonObject in an Array you must have a jsonArray to do this. Simply add this lines:

Source https://stackoverflow.com/questions/45284965

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Bike-Sharing

You can download it from GitHub.

Support

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