Lecture 38: Particle Swarm Optimization

[@SolvingOptimizationProblems]

I have been using Genetic Algorithm (GA) for 10 years but now I am learning Particle Swarm Optimization (PSO). Thank you very much professor!!!

[@mdkawsherhamid5068]

how can I contact with you?

[@codecode855]

I’m doing a thesis using PSO . This really helped thanks .

[@mallikarjunamathada1322]

Respected Sir Nice Video Lecture. Thank you very much Sir for your explanation with Example

[@nesrineibrahim5122]

thanks a lot for the perfect illustration about PSO algorithm

[@aayushpaliwal3450]

BIG BIG thanks to NPTEL and all the IIT's for this.

[@Ashutosh12394]

your class is crispy thank you sir

[@RaviSankar-ln3ki]

Thank you Sir. Indebted to you forever.

[@madhub4669]

Thank you sir for illustrating the PSO concept

[@jalalsrar4708]

Thanks Professor, its clear and so nice lecture.

[@VenkataRamaRajuLolabhattu]

Thank you very much Biswajit Mahanty sir.. Thank you..

[@ArvindBashyam-vs5nf]

during @9.36 how is adding a position to velocity gives us position. And how does multiplying a force (W) with vt and add a random value to it brings us a velocity. Kindly clear my doubt if anybody knows it

[@thankyouthankyou1172]

i like your videos, it's very clear and calm. many thanks Prof.

[@mohamedzain8628]

Thank you, keep the inspiration for us

[@dimasprasetyo3440]

Thank you so much for your explanation

[@chandarani9379]

thanks sir,for great video on pso...

[@phannsurabaya]

Thank you very much Sir!!

[@PawanMishra-zt3vb]

Hello Sir, i have a doubt?
Sir. if talk about the population structure like(Np*D), where np- random vector, and d- no of particle in each vector. So in such case:- we have to generate random population for velocity like explicitly or will take the random velocity from our initial population structure.

[@bhaskartripathi]

Very nice explaination. Thank you sir

[@Bengal2923]

Please upload a video on Grey wolf optimizer

[@omarsilva924]

Wonderful lecture. Thank you

[@inesacademic]

thank you so much

[@yazidmounir3054]

Thanks sir for this best explanation.

[@rahular4596]

really awesome sir

[@WahranRai]

5:53 IT IS NOT LOCAL BEST : IT IS PERSONAL BEST !
standard gbest PSO is talking about personal best and global best
standard lbest PSO is talking about personal best and local best (with neighborhood)

[@rameshbssv7181]

Is there any lecture on flower pollination

[@abizarkhalil]

Sir, will your goodself explain, how entre own parameters such that
"false positive rate, Intrusion detection rate and detection time" for
the intrusion detection system, to find out malicious node.

[@rahe_hidayat1]

why random noumbers?

[@lishuai8]

beetle antennae search is similar to PSO but only has a single particle @​

[@shibashishmukherjee9662]

where can i find rest of the playlist on this course?

[@prasenjitsahana2356]

there is only one lecture about Particle Swarm Optimization.

[@ankur8551]

search for course title on youtube

[@arunkumar-cz8kz]

tq sir
I enjoyed

[@archanren8348]

Professor, the flowchart may has a error.

[@sumitagrawal6397]

how we find out value of LBP(2)? i don't get it

[@snehanshus7039]

LBP(2) stores positions wrt LBF(2).

[@snehanshus7039]

look at CP(2) and LBF(2). Max (LBF(2))= GBF and the corresponding position is the 4th particle, so update LBP (2) with the 4th

[@mariolopezgonzalez9445]

valoo

[@er.shashikantkumar9584]

A lot information, but very boring lecture delivered. Please make it simple and ineresting.