I am using the ANN for a product reliability assurance application, i.e.picking some sample within the production process and then estimating the overall quality of the production line output. What kind of optimization algorithm do you think works the best for solving the ANN in such a problem. ?
Dear Sajad Saraygord Afshari ,
Optimization algorithm in neural network
The process of minimizing (or maximizing) any mathematical expression is calledoptimization. Optimizers are algorithms or methods used to change the attributes of theneural network such as weights and learning rate to reduce the losses. Optimizers are used to solve optimization problems by minimizing the function.
https://www.kdnuggets.com/2020/12/optimization-algorithms-neural-networks.html
Regards,
Shafagat
Currently I am using an ant colony optimization, but the overshoot, results in some inaccurate solutions.
in Matlab you can used statistical algorithm and you can also used Neural network algorithm
Dear Dr. Sajad,
To give some good answer:
what parameter(s) of the ANN do you want to optimize?
In MatLab Machine Learning Toolbox is very high capability for analysis.
Dear Abubakar Bala ,
I want to optimize the weightings and also the bias values.
Dear Sajad,
If we give credence to the 'no free lunch theorem' then any optimization algorithm may perfom well for your task.
However, I will suggest an algorithm with few tuning parameters such as differential evolution or cuckoo search.
Best regards,
Abubakar
you can learning the parameters of ANN bu using PSO algorithm or invasive weed algorithm and can be utilized this papers:
https://www.researchgate.net/publication/324759114_Multi-Resolution_Wavelet_PID_Speed_and_Current_Controllers_of_BLDC_Motor_Based_on_Invasive_Weed_Optimization_Technique
Article Speed Control of BLDC Motor Based on Recurrent Wavelet Neural Network
I prepared a complete tutorial about optimizing artificial neural networks using genetic algorithm with Python implementation. It is titled "Artificial Neural Networks Optimization using Genetic Algorithm with Python" It is available here:
https://www.linkedin.com/pulse/artificial-neural-networks-optimization-using-genetic-ahmed-gad
https://www.kdnuggets.com/2019/03/artificial-neural-networks-optimization-genetic-algorithm-python.html
https://towardsdatascience.com/feature-reduction-using-genetic-algorithm-with-python-403a5f4ef0c1
You can read more and more in my 2018 book that covers GA in one of its chapters. The book is cited as “Ahmed Fawzy Gad ‘Practical Computer Vision Applications Using Deep Learning with CNNs’. Dec. 2018, Apress, 978–1–4842–4167–7” which is available here at Springer https://www.springer.com/us/book/9781484241660
Also here at Amazon: https://www.amazon.com/Practical-Computer-Vision-Applications-Learning/dp/1484241665/
Ahmed Fawzy Gad can you send me the reference link of the article about machine learning algorithm
I am an author of three algorithms with many advantages over backpropagation:
1) Bipropagation
2) Border Pairs Method
3) One Step Method
All three are described here on my RG portal: https://www.researchgate.net/profile/Bojan_Ploj/research
could you give some examples of Bipropagation and border pairs method if possible
Did you see my presentation from "IBM developers unconference 2019"?
I look forward to your further questions.
Presentation New Deep Learning Algorithms beyond Backpropagation IBM Deve...
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