Skip to main content

Cuomo Is Eating De Blasio's Lunch On Congestion Pricing

Cuomo Is Eating De Blasio's Lunch On Congestion Pricing Governor Andrew Cuomo made congestion pricing a centerpiece of his budget presentation earlier this month, pledging to raise $15 billion for transit improvements by tolling vehicles crossing bridges into Manhattan or traveling below 60th Street in Manhattan. According to a recent poll, 52 percent of New York State residents support congestion pricing, and that number climbs even higher for those living in the city. Missing from the conversation: Mayor Bill de Blasio, who at first said he did not "believe" in congestion pricing, and now says that the idea to toll cars coming into his city has nothing to do with him. [ more › ] Gothamist http://bit.ly/2Tm8G4f January 29, 2019 at 11:23PM
Labels:

Comments

Post a Comment

Popular posts from this blog

Solving Van der Pol equation with ivp_solve

Van der Pol’s differential equation is The equation describes a system with nonlinear damping, the degree of damping given by μ. If μ = 0 the system is linear and undamped, but for positive μ the system is nonlinear and damped. We will plot the phase portrait for the solution to Van der Pol’s equation in Python using SciPy’s new ODE solver ivp_solve . The function ivp_solve does not solve second-order systems of equations directly. It solves systems of first-order equations, but a second-order differential equation can be recast as a pair of first-order equations by introducing the first derivative as a new variable. Since y is the derivative of x , the phase portrait is just the plot of ( x , y ). If μ = 0, we have a simple harmonic oscillator and the phase portrait is simply a circle. For larger values of μ the solutions enter limiting cycles, but the cycles are more complicated than just circles. Here’s the Python code that made the plot. from scipy import linspace from ...
Post a Comment
Read more

Explaining models with Triplot, part 1

[This article was first published on R in ResponsibleML on Medium , and kindly contributed to R-bloggers ]. (You can report issue about the content on this page here ) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Explaining models with triplot, part 1 tl;dr Explaining black box models built on correlated features may prove difficult and provide misleading results. R package triplot , part of the DrWhy.AI project, is aiming at facilitating the process of explaining the importance of the whole group of variables, thus solving the problem of correlated features. Calculating the importance of explanatory variables is one of the main tasks of explainable artificial intelligence (XAI). There are a lot of tools at our disposal that helps us with that, like Feature Importance or Shapley values, to name a few. All these methods calculate individual feature importance for each variable separately. The problem arises when features used ...
Post a Comment
Read more