@Vitarka Kadapa Sir, thank you for sharing videos with a very much information in detail. sir i want to know how this confirmation test is to be carried out and setting out the parameters also to know the improvement of grey relation grade. please make a video as soon as possible.
Hello, I really appreciate you sharing the video. I'm grateful for the thorough explanation. However, I do have one question: Could you make it clear for me, please? The optimal configuration for multiobjective optimization using rank GRA was first discovered A3B1C2D1E3. As well as using the average grey relation by factor level, multiobjective optimization was also discovered in A1B1C2D1E3. Which of one this is the best optimal setting to take into account? WHY?
The one which given from the GRA rank A3B1C2D1E3, was there in the experiments which are conducted by the researcher. We need to understand that the Design of Experiments limits the number of experiments we are performing. Then the one which got from the average of GRG is A1B1C2D1E3 is not there is our list of experiments conducted. So, after conducted an experiment with A1B1C2D1E3 this set, it was found better and we have to consider this one only. For more discussion please email to me Gmail - vitarkaprojects
Sir, does we need weights for each parameter for the calculation of Grade in GRA? Did you took equal weights for all the parameter? I have different weights, Please let me know how to proceed with different weights. Thankyou
@Vitarka Kadapa Sir I have an example data which when I solved, It turns out to be such that the optimal value of GRG comes out to be 1.015. I wonder is it right since its more than 1 , i am confused
Coefficient of determination is an algorithm specific parameter, if you tune it you will get better results. 0 to 1 it ranges, 0.5 is the middle value. You can vary from 0 to 1 of any interval. Based on the results you can derive into conclusion
In Grade if two value are same for different experiment or levels which one we should choose at number 1 rank. We should consider at number 1 rank for both experiment no. Or something else? Please reply
Since it was a multi attribute decision making so it will be left over to decision maker. Decision maker has to decide to which output response consider for selecting from he top ranks of the two experiments
@Vitarka Kadapa Sir, Thank you for sharing such informative, step by step videos. I am watching your videos and getting a strong based understanding of the same. Sir, I request you to "please provide the link of the video having "ANOVA & CONFIRMATION EXPERIMENT "with the example" IN CONTINUATION OF THIS VIDEO.
@@Vitarka Sure the softwares have not any direct command. I have tried it. Could you please make a video on mix design using MINITAB or Design expert software?
In this research paper, weight of output parameters (MRR, Surface roughness, etc.) not considered. If it is considered then Grade will be changed and rather say it will be more accurate. If we wish to find the weight then what to do sir?
Basically weight has to be considered but this one I explained based on the authors how they wrote the outputs. What you are saying was right it is good and accurate if they consider the weights.
Hi thank you so much for the video. Really appreciate it with the detailed explanation. However, i am having a doubt that while calculating the normalization values we have to take S/N ratio values or response values? as mentioned in your video ruclips.net/video/48cc72YWdk8/видео.html you took SN values, but in this you chose response values. Request to clear the doubt and hope to see your response. Thank you
You are amazing. I am hooked to these videos. Will tell about these to my students.
@Vitarka Kadapa Sir, thank you for sharing videos with a very much information in detail. sir i want to know how this confirmation test is to be carried out and setting out the parameters also to know the improvement of grey relation grade. please make a video as soon as possible.
Welcome, Will try to do it
Hello, I really appreciate you sharing the video. I'm grateful for the thorough explanation. However, I do have one question: Could you make it clear for me, please?
The optimal configuration for multiobjective optimization using rank GRA was first discovered A3B1C2D1E3. As well as using the average grey relation by factor level, multiobjective optimization was also discovered in A1B1C2D1E3.
Which of one this is the best optimal setting to take into account? WHY?
The one which given from the GRA rank A3B1C2D1E3, was there in the experiments which are conducted by the researcher. We need to understand that the Design of Experiments limits the number of experiments we are performing. Then the one which got from the average of GRG is A1B1C2D1E3 is not there is our list of experiments conducted. So, after conducted an experiment with A1B1C2D1E3 this set, it was found better and we have to consider this one only.
For more discussion please email to me Gmail - vitarkaprojects
@@Vitarka okay thank!
Sir, does we need weights for each parameter for the calculation of Grade in GRA? Did you took equal weights for all the parameter? I have different weights, Please let me know how to proceed with different weights. Thankyou
Yes we need weights for each parameter. If not we can consider equal weights.
Please write to me
Gmail - vitarkaprojects
@@Vitarka Thankyou Sir
Sir, can you please explain the deviation sequence calculation? How we are subtracting "Normalised value" with 1? From where we are taking 1?
You can see the formula from there I am using it. It will maximum value of the previous step and it will be 1.
@Vitarka Kadapa
Please help, how to select the initial process parameters in confirmation test? What is the criteria for doing so?
Sir the initial process parameters you can choose as first experiment or middle experiment
@@Vitarka Thanks
Excellent description about grey analayis. thank you very much sir
Welcome sir
@Vitarka Kadapa Sir I have an example data which when I solved, It turns out to be such that the optimal value of GRG comes out to be 1.015. I wonder is it right since its more than 1 , i am confused
Ideally when the normalization is using the MCDM techniques. the Grade (GRG) value should lie between 0 to 1. Please re calculate and verify it.
Please, when should we expect your tutorials on ANN and GA? Thanks
For sure i will work on it and upload.
Is GRA applicable for two responses ?
Say Hardness and corrosion rate?
Yes you can apply
sir, in GRC why enter 0.5 and 1 ? follow the formula or how? thanks btw
Coefficient of determination is an algorithm specific parameter, if you tune it you will get better results. 0 to 1 it ranges, 0.5 is the middle value. You can vary from 0 to 1 of any interval. Based on the results you can derive into conclusion
Hi, thank you so much & very well explained. It is more useful to beginner like me. Keep rocking. Happy new year 2023
Thank you
In Grade if two value are same for different experiment or levels which one we should choose at number 1 rank.
We should consider at number 1 rank for both experiment no. Or something else?
Please reply
Since it was a multi attribute decision making so it will be left over to decision maker. Decision maker has to decide to which output response consider for selecting from he top ranks of the two experiments
@@Vitarka thank you for your quick response 🙏
Very clearly explained the concepts. Thanks a lot
You are most welcome
@Vitarka Kadapa Sir, Thank you for sharing such informative, step by step videos. I am watching your videos and getting a strong based understanding of the same. Sir, I request you to "please provide the link of the video having "ANOVA & CONFIRMATION EXPERIMENT "with the example" IN CONTINUATION OF THIS VIDEO.
You are most welcome.
you can watch - ruclips.net/video/nurpUgUjEX4/видео.html
one more ruclips.net/video/nY7y18DKYbA/видео.html
@Vitarka Kadapa Sir. Thanks Sir🙏
Sir how we choosed 5 as a output in grade analysis,
It's Avarage or given value
Sir, if you are mentioning the fifth experiment, then it was take as highest grade value.
commendable work.
Thank you
thanks for your efforts, it is very clear
Welcome
Nice explanation can you share xls file
Please write to me
Gmail - vitarkaprojects
Thanks for this amazing video.
Does MINITAB or Design Expert have the direct commands for GRA ?
I am not sure about the Softwares. But we can do simple in excel.
@@Vitarka Sure the softwares have not any direct command. I have tried it.
Could you please make a video on mix design using MINITAB or Design expert software?
Will check it.
how to apply Genetic algorithm for RSM
You will get an objective function in rsm with that one need t code the genetic algorithm
How should I contact you ??
Need little help sir !!
go to the about section of the channel, you can find the email address contact me there.
Can you plzz make a video of using genetic algorithm optimization
surely.
In this research paper, weight of output parameters (MRR, Surface roughness, etc.) not considered. If it is considered then Grade will be changed and rather say it will be more accurate. If we wish to find the weight then what to do sir?
Basically weight has to be considered but this one I explained based on the authors how they wrote the outputs. What you are saying was right it is good and accurate if they consider the weights.
If you need how to calculate the weights you can refer my video on AHP - ruclips.net/video/K3maOypAd4A/видео.html
@@Vitarka Sir, I have watched your video on Entropy method. Can we use this method to calculate weight?
yes sir you can use it
Hi
Fuzzy Grey Analysis pe video banaye sir.
Will check the possibility and do it sir
Please upload the video for IC engine Performance
ANY REFERENCE JOURNAL PAPER ON IT SEND ME I WILL TRY TO PREPARE
Can u make video on Second Synthetic GRA model sir
Sir, please share me the reference paper link i will go thru it and try to prepare a video on it
Thank you so much
You're most welcome
Thankyou
You’re welcome 😊
We can write an A star paper together.
Hi thank you so much for the video. Really appreciate it with the detailed explanation. However, i am having a doubt that while calculating the normalization values we have to take S/N ratio values or response values? as mentioned in your video ruclips.net/video/48cc72YWdk8/видео.html you took SN values, but in this you chose response values. Request to clear the doubt and hope to see your response. Thank you
Same here. Waiting for it.
I have used reference journal papers, based on the author input i have solved it. But it will give different outputs if you use sn values.
@@Vitarka Noted.
Its preferable to use SN ratio as per the taguchi GRA