Do Random and Chaotic Sequences Really Cause Different PSO Performance? Further Results

09/15/2023
by   Paul Moritz Nörenberg, et al.
0

Empirical results show that PSO performance may be different if using either chaotic or random sequences to drive the algorithm's search dynamics. We analyze the phenomenon by evaluating the performance based on a benchmark of test functions and comparing random and chaotic sequences according to equality or difference in underlying distribution or density. Our results show that the underlying distribution is the main influential factor in performance and thus the assumption of general and systematic performance differences between chaos and random appears not plausible.

READ FULL TEXT
research
02/09/2023

Do Random and Chaotic Sequences Really Cause Different PSO Performance?

Our topic is performance differences between using random and chaos for ...
research
06/03/2019

A test against trend in random sequences

We study a modification of Kendall's tau-test, replacing his permutation...
research
12/22/2021

Comparing balanced ℤ_v-sequences obtained from ElGamal function to random balanced sequences

In this paper, we investigate the randomness properties of sequences in ...
research
10/09/2019

Implementation of irreducible Sobol sequences in prime power bases

We present different implementations for the irreducible Sobol (IS) sequ...
research
11/19/2015

Universal halting times in optimization and machine learning

The authors present empirical distributions for the halting time (measur...
research
07/12/2021

Constrained Sampling from a Kernel Density Estimator to Generate Scenarios for the Assessment of Automated Vehicles

The safety assessment of automated vehicles (AVs) is an important aspect...

Please sign up or login with your details

Forgot password? Click here to reset