PSO | Particle Swarm Optimization
kandi X-RAY | PSO Summary
kandi X-RAY | PSO Summary
The following is some guidance for the ranges of the parameters. A typical range is 20-40. For many problems, as few as 10 particles may be enough. For larger or more difficult problems, 100, 200, or more particles might be more appropriate. Generally the range is 0-1, typically very close to 1. Usually they are nearly equal and typically around 2, but they can range from 0-4. If the local parameter is set to 0, then the neighbors take no part in the optimization. The range in the x and y directions, respectively. A good range is -50 to 50 in both directions. In that case, both the world width and height would be 100. Limits how much a particle can move for a given iteration. Typical values to try are 1, 2, and 10. Some implementations define maximum velocity as the world width or height. swarm.py [-v] [test] numParticles inertia cognition socialRate localRate worldWidth worldHeight maxVelocity maxEpochs k fname. Note: do not include an extension for fname, .csv is appended automatically.
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Top functions reviewed by kandi - BETA
- Update the velocity of each particle .
- Creates particle objects
- Distance between world and world coordinates .
- Return the distance between two points .
- Return the nth distance between two points .
- Computes the q - distance .
PSO Key Features
PSO Examples and Code Snippets
Lines of Code : 26License : Permissive (MIT License)
Copydef forward(ctx, input, rois, offset,
spatial_scale,
pooled_size,
output_dim,
no_trans,
group_size=1,
part_size=None,
sample_per_part=4,
Community Discussions
Trending Discussions on PSO
QUESTION
I have a DirectX 12 desktop project on Windows 11 that implements post-processing using a combination of DXTK post-process effects.
The aim of the post-proc sequence is to end up with individual bloom and blur textures (along with a depth texture rendered in a depth pass) which are sampled in a 'big triangle' pixel shader to achieve a depth of field effect for the final backbuffer screen image.
The DXTK PostProcesses operate on the full-size (1920x1080) screen texture. Presently this isn't impacting performance (benchmarked at 60fps), but I imagine it could be an issue when I eventually want to support 4K resolutions in future, where full-size image post-processing could be expensive.
Since the recommended best practice is to operate on a scaled down copy of the source image, I hoped to achieve this by using half-size (i.e. quarter resolution) working textures with the DownScale_2x2 BasicPostProcess option. But after several attempts experimenting with the effect, only the top-left quarter of the original source image is being rendered to the downsized texture... not the full image as expected per the documentation:
DownScale_2x2: Downscales each 2x2 block of pixels to an average. This is intended to write to a render target that is half the size of the source texture in each dimension.
Other points of note:
- scene geometry is first rendered to a _R16G16B16A16_FLOAT MSAA render target and resolved to single-sample 16fp target
- postprocessing operates on resolved single-sample 16fp target (where only the intermediate 'Pass1' & 'Pass2' working render targets are set to half the backbuffer length & width)
- final processed image is tonemapped to the _R10G10B10A2_UNORM swapchain backbuffer for presentation.
The following code snippets show how I'm implementing the DownScale_2x2 shader into my post-process. Hopefully it's enough to resolve the issue and I can update with more info if necessary.
Resource initialization under CreateDeviceDependentResources():
...ANSWER
Answered 2022-Apr-11 at 21:53The PostProcess class uses a 'full-screen quad' rendering model. Since we can rely on Direct3D 10.0 or later class hardware, it makes use of the 'self-generating quad' model to avoid the need for a VB.
As such, the self-generating quad is going to be positioned wherever you have the viewport set. The scissors settings are also needed since it uses the "big-triangle" optimization to avoid having a diagonal seam across the image IF you have the viewport positioned anywhere except the full render target.
I have this detail in the Writing custom shaders tutorial, but I forgot to replicate it in the PostProcess docs on the wiki.
TL;DR: When you go to render to the smaller render target, use:
QUESTION
I have a list that includes the paths of the files (in my case movies), which is called collectMovies and has followed data structure:
ANSWER
Answered 2022-Mar-22 at 22:19Option 1: Eliminate building a list of images from the Movies directory and having to manipulate the path string by using os.listdir() and os.chdir(). IMHO this is a cleaner and less error prone method, should you want to change the path to your movie files.
QUESTION
Our mobile menu works fine in Chrome & Firefox on a Pixel 5.
On an iPhone 5s (the only iPhone I have), an iPad Mini 2 and on an older iPad, the burger menu open & close icons do not show.
On a non-retina desktop display where Chrome & Firefox work in responsive mode (mobile viewport width), Safari will show the mobile menu open icon, but not the close icon.
The open icon is three pipes rotated 90deg: |||
The close icon is a font-awesome symbol:
...ANSWER
Answered 2022-Mar-14 at 05:44Please try this css in your code
QUESTION
I am trying to make a problem more reactive to new inputs here is where the error is given
...ANSWER
Answered 2022-Jan-03 at 01:20Here's a MRE up to the first plot to ilustrate how to deal with reactive objects. Notice the use of () when accessing a reactive value.
QUESTION
When I run the code below, I get this error:
...ANSWER
Answered 2021-Dec-29 at 21:12V_inicial[0],V_inicial[1],V_inicial[2],V_inicial[3] should be an array, I have never use that function but I have been looking to the docummentation that you can read here:
https://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.solve_ivp.html
The function identifies V_inicial[0] as the y0 param and V_inicial[1] as the method param and when you write method='RK45' you are defining another value to method param. Try to use an array, and tell me about :)).
QUESTION
I'm working on powershell script and I'm trying to read only "User" column from my csv file and then convert it to their Microsoft AzureAD Display name but not sure how to do that so I'll be appreciated if I can get any help or suggestion.
My csv file look like this
C:\AuditLogSearch$($CurDate) Final Audit-Log-Records.csv
...ANSWER
Answered 2021-Dec-01 at 16:42You can just update the values on the User property of the imported CSV, there is no need to create a $list = @() to save the results.
Assuming $ImportFile.User contains valid UserPrincipalNames of Azure AD Users, the part you're struggling with would look like this (definitely no need for a function):
QUESTION
In a portfolio optimisation problem, I have a high dimension (n=500) space with upper and lower bounds of [0 - 5,000,000]. With PSO I am finding that the solution converges quickly to a local optima rather and have narrowed down the problem to a number of areas:
- Velocity: Particle velocity rapidly decays to extremely small step sizes [0-10] in the context of the upper/lower bounds [0 - 5,000,000]. One plug I have found is that I could change the velocity update function to a binary step size [e.g. 250,000] by using a sigmoid function but this clearly is only a plug. Any recommendations on how to motivate the velocity to remain high?
- Initial Feasible Solutions: When initialising 1,000 particles, I might find that only 5% are feasible solutions in the context of my constraints. I thought that I could improve the search space by re-running the initialisation until all particles start off in a feasible space but it turns out that this actually results in a worse performance and all the particles just stay stuck close to their initialisation vector.
With respect to my paremeters, w1=c1=c2=0.5. Is this likely to be the source of both problems?
I am open to any advice on this as in theory it should be a good approach to portfolio optimisation but in practice i am not seeing this.
...ANSWER
Answered 2021-Nov-06 at 19:00Consider changing the parameters. Using w=0.5 'stabilizes' the particle and thus, preventing escape from local optima because it already converges. Furthermore, I would suggest to put the value of c1 and c2 to become larger than 1 (I think 2 is the suggested value), and maybe modify the value for c1 (Tendency to move toward global best) slightly smaller than c2 to prevent overcrowding on one solution.
Anyway, have you tried to do the PSO with a larger amount of particles? People usually use 100-200 particles to solve 2-10 dimensional problem. I don't think 1,000 particles in 500 dimensional space will cut it. I would also suggest to use more advanced initialization method instead of normal or uniform distribution (e.g. chaotic map, Sobol sequence, Latin Hypercube sampling).
QUESTION
I'm using SCIP to solve MILPs in Python using PyScipOpt. After solving a problem, the solver statistics can be either 1) printed as a string using printStatistics(), or 2) saved to an external file using writeStatistics(). For example:
ANSWER
Answered 2021-Oct-25 at 07:29PySCIPOpt does not provide access to the statistics directly. The data for the various tables (e.g. separators, presolvers, etc.) are stored separately for every single plugin in SCIP and are sometimes not straightforward to collect.
If you are only interested in certain statistics about the general solving process, then you might want to add PySCIPOpt wrappers for a few of the simple get functions defined in scip_solvingstats.c.
Lastly, you might want to check out IPET for parsing the statistics output.
QUESTION
I have a nested json array and I am trying to get the maximum value of the points attribute in this array.
...ANSWER
Answered 2021-Oct-16 at 18:49you can use the reduce method on the array object to do this
QUESTION
Simply speaking, I have a function f(x, t2) and I want to find the value of x that maximize the integral of f(x, t2) with respect to t2. I choose pso algorithm to do the optimization. The excutable code is as follows
ANSWER
Answered 2021-Sep-01 at 06:33In this case, I would not use tryCatch which is usually more appropriate in testing than in your main code. Why don't you simply test the determinants in your function ? Something like that should work:
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Install PSO
You can use PSO like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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