Particle Swarm Optimization in MATLAB - Yarpiz Video Tutorial - Part 1/3

[@bhaskartripathi]

One of the best Particle Swarm Optimization videos ever..

[@YarpizProjects]

Thanks. Very nice to hear that.

[@SyedTAMU]

I didn't knew anything about this topic... and was always afraid of learning it... Saw this video today on the recommendation of my friend... and I must say this is the best possible explanation of this topic... putting understanding and life in those useful but non-cooperative mathematical equations.. A big hug and many thanks...

[@qiblaji]

this is one of the best videos on the topic. Awesome work, Professor

[@ebrahimaghajari1556]

It's a real perfect explanation of PSO.Excellent Sir!!!

[@asmaayari2167]

Very Very good and helpful video!!!!!! Thanks a lot. Your explanation, your knowledge, your English, your figures... All is awesome.

[@a.a.a7385]

Thanks, It was a prominent and straightforward explanation

[@ehabliath778]

ٌThe best explanation of the PSO algorithm ever , really thanks

[@anitham5436]

Your way of explanation is truely very clearly sir..thank you

[@Gojo_Satorou274]

Just wanted to say, I really love your style of explanation. Such a lovely channel.

[@daggawagga]

It is so good when you find such a diamond almost randomly on youtube I wish someone would make such a clear video on other algorithms such as cat swarm algorithm

[@princessmaram5397]

The word Thank you is not enough to express my gratitude Dr. Mostefa for this wonderful video about pso. Could you please, do another video about shuffled frog leaping algorithm?

[@SolvingOptimizationProblems]

Very clear explanation about Particle Swarm Optimisation (PSO). Thank you very much Professor!

[@YarpizProjects]

Thank you very much. Very nice to hear that.

[@DesertRose124]

I tried several videos and yours is the best. Thank you so much.

[@navneetarya1184]

best video for PSO

[@shalipse]

Excellent video, could you please explain what you mean by j-th component of velocity you mentioned 17:50 onward. Thank you

[@Unstable_Diffusion89]

the jth component of velocity represents the different spacial dimensions of the velocity vector. So in a 3d space there would be three j components for the velocity vector.

[@dhakriVideos]

gbest lecture among i come across about PSO

[@honestdisliker4362]

the best explanation in you tube

[@sridharsidhu1882]

Excellent explanation. We want you to make as many videos as possible on MATLAB in the same way. Thank you.

[@abdurehmanmuleta6648]

Excellent explanation of PSO. Thank you.

[@alpmuhiddinoglu251]

It was a great video in order to understand this method.

[@YarpizProjects]

Thank you very much. Very nice to hear that.

[@ramakantpatil2696]

Excellent video by professor, thanking you.

[@Evan-zj5mt]

Great video! Shame you've not done more, your explanations are very good. An explanation of something like ant colony or NSGA II would be warmly received I'm sure :)

[@loganathanv564]

Very good explanation. The value of r1 and r2 is clearly mentioned that it is in the range between 0 to 1. Kindly mention the possible range or values of the acceleration coefficients c1 and c2. Thank You.

[@matinislami7893]

so nice explanation with proper example. thank for that.

[@derivevarp111]

well explained! easy to understand the fundamental of this complicated concept.

[@mahmoudghorab1284]

Awesome explanation Sir, please make more videos like this for more algorithms such as SA ,GA and , ante colony......etc

[@ahmedshaaban3813]

Very good explanation. Thank You.

[@YarpizProjects]

Thanks. You're welcome.

[@ricardofuentes5383]

Great video, thanks for sharing your knowledge!!

[@Mohammad_1234uk]

Excellent job , my highly appreciate for your efforts . its really easy and very helpful for understanding

[@passoanf]

Very good explanation.

[@ashishsingh1691]

very nice explanation and coding part was also very helpful and nicely explaned

[@eshafeeqee]

Great Explanation

[@hazemahmed8333]

thank you, professor, your explanation is amazing!

[@jeevatetrex2615]

Nice presentation sir,thank you so much

[@jonasgun]

Excellent explanation!

[@AlieDenno]

Brilliant explanation, Thanks.

[@SMARTPALASH]

wow really very simple and easily understandable thank you so much SIR.

[@thefiat18]

what is the j-th component of the velocity @17:54 ? what is the physical meaning of j-th component?

[@hamdidjeridane5727]

I think it depends on the global best, since global best may vary during simulation, it goes from. Worst to best

[@woongteng]

xi(t) is a vector. Thus it has dimensions. If xi(t) moves in a 2D plane as shown in the lecture, xi(t) has two vector components. j-th component means these components of xi(t). In this case, j has component 1 and 2 which correspond to x and y components in a x-y coordinate. It is that xi(t) = [xi1(t), xi2(t)]. Therefore, xi1(t) is the x component of xi(t), and xi2(t) is the y component of xi(t). It is also same for velocity vi(t) and vij(t).

[@hadialidoust3543]

Thank you mostafa

[@cuteyo4372]

Best explanation !! Thanks a lot for this video

[@walktalklearnenglishthroug7145]

دکتر سید مصطفی کلامی هریس. مدیر و بنیانگزار سایت فرادرس. آموزش شما بسیار عالی و جامع بود. امیدوارم ویدئوهای بیشتری را به زبان انگلیسی به اشتراک بگذارید. موفق و پیروز باشید.

[@pramitd]

Awesome explanation.

[@54908710]

Thanks for the great work!

[@hasan5658]

just amazing teacher... could you please cover topics on bee colony algorithm???

[@edemialemgedefaye4502]

Thanks a lot! Which is very helpful for researchers

[@ahmadwafa4367]

Thank you for your useful explanation

[@Antypodish]

Amazing work, many thx for sharing. Exactly what I need, and other lectures.

[@aamirmustafa7731]

Great video for learning

[@sabrinabou9078]

Thank you very much! Great video

[@erensahin9933]

Great video!

[@kalimullah2773]

Great explanation

[@kirtanpanda8123]

Best and easy to understand

[@omidasadi2264]

thanks for sharing gharpiz ...

[@omidasadi2264]

nice english torkish accent ;D

[@mphathelenimudau7305]

wow...i love this video. please upload another one

[@YarpizProjects]

All of three parts of this video tutorial, is available via following links: Part 1: kzbin.info/www/bejne/qXOUn2yXbt6rgM0 Part 2: kzbin.info/www/bejne/roHOg3-VfNlphqs Part 3: kzbin.info/www/bejne/f3SliqWBqKuDp6M

[@yalamanchilisurekha1601]

Yarpiz

[@mandeepkhaleriya1314]

+Yarpiz please provide me your mail I'd. ...i want to discuss with you...so reply me asap.

[@sandhyanair3446]

Very well explained !!

[@faheemgulzar04]

Very nice explanation. please can you upload video on PID tuning using PSO?

[@nikhildeshmukh1747]

Simply the best

[@beypazariofficial]

mastapha nice work

[@haohuynhnhat3881]

this is very useful. thanks for sharing it!

[@afifputranugraha8953]

very awesome and very helpfull video :) Thank you very much, its really help me

[@YarpizProjects]

Nice to hear that. Thanks and you're welcome.

[@jecking2]

Very helpful video sir. Please upload tutorial video also for multi-objective algorithms like SPEA-2, NSGA-2 and their implementation in matlab.

[@engsamia236]

you are the best ...thanks

[@yazidmounir3054]

Very very good and helpful

[@RK-0731]

Great work, thanks

[@bbq2024lovely]

What a great video Thanks

[@rafaelafarias8635]

Great video! Thank you.

[@mkbx01]

please make Multiple Objective PSO video ,,, I want learn about MOPSO ,,,

[@KanokpornChangkhuntod]

Please Upload Next Part Thank you for your knowledge

[@YarpizProjects]

All of three parts of this video tutorial, is available via following links: Part 1: kzbin.info/www/bejne/qXOUn2yXbt6rgM0 Part 2: kzbin.info/www/bejne/roHOg3-VfNlphqs Part 3: kzbin.info/www/bejne/f3SliqWBqKuDp6M

[@shadymsadek4943]

Great Work

[@djameling]

Very good and helpful video

[@remomein05]

thank you Sir. Please do videos for other techniques.

[@badriehmustafa2296]

Very Helpful, Thank You

[@lucascardoso2271]

Very good!

[@faridhasanov6094]

Hey, can you answer one question ? What is the difference between this algorithm and neighborhood algorithm ?Well, they seem to have similar or approximately similar algorithm - random population initialized , the best solutions are chosen , and next solutions are going to be chosen by “ walking by” around the best solution. In particle swarm it is some value , let’s say if solution was 15, it will walk on the range from 5 to 25. In neighborhood algorithm , voronoi cell is implemented , which does practically the same thing: walking in the close neighborhood of the best solution. What is the difference between methods then ?

[@instituteofcompetitionexpl1588]

I am having one project in PSO .I want to implement microstrip antenna using Ebg at 2.4 GHz

[@lahcenerouani3735]

so amazing wow wonderful thanks Sir

[@BurRun-kt3tf]

អរគុណ Thank❤

[@yurischeuer]

Thanks for the video!

[@DikshaMauryadreamtofly]

Thank you sir, for this informative lecture. can you also explain wolf search optimization?

[@asan7440]

Thank you for your efforts Is it possible to create a problem code with multiple tasks simultaneously related to each other? And how to get the result to be integer only ?

[@annalizaestrebelloscholtz5353]

Great job! Thank you for uploading, this helps a lot in my research.

[@danishiqbal324]

Very Good

[@AssassinGrudge]

at 14:46 the new velocity feels wrong

[@56-shashankkumarsingh50]

nicely explained

[@shishirakantajena834]

Why are we using random function in the equation?? Is it for the randomness of the particles used for observation or whether any specific reason is there for use of random function in the codes??

[@youcefghibeche]

it was very helpful thank you very much

[@yerraprathyusha201]

Hi yarpiz, very helpful tutorial. Do you suggest any material for finding shortest distance between two locations(3d Cartesian points)with obstacles in between using PSO

[@xuanruizhang156]

Very helpful video. But I have some questions: 1) since g(t) is the best point of all particles, p_i(t) is the best point of the particle i, does it mean that g(t) is better than p_i(t), then why would v(t+1) stil considers p_i(t) instead of only considering g(t)? 2) Since g(t) is the best point of all, and each particle is somewhat moving towards g(t), wouldn't this algorithm easily fall into a local optimum？ Thanks a lot!

[@idea9423]

Thank you, please make a vedeo about grey Wolf méthod andlévy_flight moth_flame method

[@acrtvnomad3115]

Thanks so muchh!

[@FathallaABC123]

Great job

[@sharma_ji_ka_ladka321]

thanks yarpiz, can you make vidoes on mopso with line to line code explanation

[@nawfalnazar2386]

wonderful video !!!!!!!! Gooooooooood

[@sabrinabba2896]

Great vedio thank you so much

[@kartik303]

Superb

[@ns3lover779]

thank you so much

[@parampalsinghgill7697]

Thankyou for such a good video sir. My one confusion: Why do we consider position and velocity have same dimension.... later in the video as well velocity seems like we are just estimating the new position of the particle, but we are referring to it as velocity ? Can you/anybody please clarify?

[@tomassaavedra4543]

thanks a lot man!

[@fatimaharfouchi5384]

thank you

[@engineer4340]

dear sir greeting first i like to thanks for your explanation the second if we have inequality constrains how can we implementation it inside PSO