D.1: AutoML - Revision history

Admin ugqr649i at 07:52, 8 April 2025

2025-04-08T07:52:38Z

← Older revision		Revision as of 07:52, 8 April 2025
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	• '''Applicable Business Category''': All/Smart Industry		• '''Applicable Business Category''': All/Smart Industry

	• '''Application in relevant Projects/Initiatives''': COGNITWIN		• '''Application in relevant Projects/Initiatives''': Yes, Circular TwAIn, COGNITWIN

	• '''Asset Type''': Executable, Web Application (platform independent)		• '''Asset Type''': Executable, Web Application (platform independent)

Admin ugqr649i at 07:52, 8 April 2025

2025-04-08T07:52:12Z

← Older revision		Revision as of 07:52, 8 April 2025
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	AutoML will be used in CircularTwAIN to cover all of the above listed functionalities. AI Module that will be used to reduce CO2 output from the sensors that are available on the plant and laboratory analysis as a label. This module includes data processing and helps to train multiple ML algorithms at once to compare results.		AutoML will be used in CircularTwAIN to cover all of the above listed functionalities. AI Module that will be used to reduce CO2 output from the sensors that are available on the plant and laboratory analysis as a label. This module includes data processing and helps to train multiple ML algorithms at once to compare results.

	• '''Reference, URL''': Available upon request		• '''Reference, URL''': Available upon request (https://www.teknopar.com.tr/)

	• '''Applicable Business Category''': All/Smart Industry		• '''Applicable Business Category''': All/Smart Industry

Admin ugqr649i at 10:36, 27 December 2024

2024-12-27T10:36:56Z

← Older revision		Revision as of 10:36, 27 December 2024
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	AutoML will be used in CircularTwAIN to cover all of the above listed functionalities. AI Module that will be used to reduce CO2 output from the sensors that are available on the plant and laboratory analysis as a label. This module includes data processing and helps to train multiple ML algorithms at once to compare results.		AutoML will be used in CircularTwAIN to cover all of the above listed functionalities. AI Module that will be used to reduce CO2 output from the sensors that are available on the plant and laboratory analysis as a label. This module includes data processing and helps to train multiple ML algorithms at once to compare results.

	• '''Reference, URL''': ~~Avaliable~~ upon request		• '''Reference, URL''': Available upon request

	• '''~~Relevant Domain/Industry~~''': All/Smart Industry		• '''Applicable Business Category''': All/Smart Industry

	• '''Application in relevant Projects/Initiatives''': COGNITWIN		• '''Application in relevant Projects/Initiatives''': COGNITWIN

	• '''Type''': Web ~~application~~ (platform independent)		• '''Asset Type''': Executable, Web Application (platform independent)
	It has a preconfigured pipeline architecture following wizard like steps implemented by functionalies in the order of provided tabs (data selection, preprocessing, analysis, algorithm selection, model training, model comparison, test, saving). LSTM, KNN, RF, GBT, MLP, SVM		It has a preconfigured pipeline architecture following wizard like steps implemented by functionalies in the order of provided tabs (data selection, preprocessing, analysis, algorithm selection, model training, model comparison, test, saving). LSTM, KNN, RF, GBT, MLP, SVM

	• '''AI Breadth''': ML, DL		• '''AI Breadth''': ML, DL

	• '''Learning Ability''': Supervised Learning, currently, others can be added later		• '''Learning Ability''': Supervised Learning, (currently, others can be added later)

	• '''Related technologies''': Python, Scikit-learn, Keras, Flask (API), Java Script, HTML, CSS,React.js, PostgreSQL, TimeScaleDB		• '''Related technologies''': Python, Scikit-learn, Keras, Flask (API), Java Script, HTML, CSS,React.js, PostgreSQL, TimeScaleDB

	• '''Applicable Research Area''':		• '''Applicable Research Area''': Integrative AI

	~~• '''Applicable Technical Category''':~~

	~~• '''Applicable Business Category''':~~

	• '''~~Asset Type~~''':		• '''Applicable Technical Category''': Machine Learning

	• '''License Information''': Restricted		• '''License Information''': Restricted

Admin ugqr649i at 09:21, 20 December 2024

2024-12-20T09:21:13Z

← Older revision		Revision as of 09:21, 20 December 2024
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	• '''Related technologies''': Python, Scikit-learn, Keras, Flask (API), Java Script, HTML, CSS,React.js, PostgreSQL, TimeScaleDB		• '''Related technologies''': Python, Scikit-learn, Keras, Flask (API), Java Script, HTML, CSS,React.js, PostgreSQL, TimeScaleDB

			• '''Applicable Research Area''':

			• '''Applicable Technical Category''':

			• '''Applicable Business Category''':

			• '''Asset Type''':

	• '''License Information''': Restricted		• '''License Information''': Restricted

Admin ugqr649i at 13:51, 26 April 2023

2023-04-26T13:51:15Z

← Older revision		Revision as of 13:51, 26 April 2023
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	AutoML will be used in CircularTwAIN to cover all of the above listed functionalities. AI Module that will be used to reduce CO2 output from the sensors that are available on the plant and laboratory analysis as a label. This module includes data processing and helps to train multiple ML algorithms at once to compare results.		AutoML will be used in CircularTwAIN to cover all of the above listed functionalities. AI Module that will be used to reduce CO2 output from the sensors that are available on the plant and laboratory analysis as a label. This module includes data processing and helps to train multiple ML algorithms at once to compare results.


	• '''Reference, URL''': Avaliable upon request		• '''Reference, URL''': Avaliable upon request

Admin ugqr649i at 13:51, 26 April 2023

2023-04-26T13:51:07Z

← Older revision		Revision as of 13:51, 26 April 2023
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	• '''Short Description''':		• '''Short Description''':
			AutoML is a software application that enables users to use and apply artifical intelligence (machine learning/deep learning), even if the users are not experienced in these topics. With a wizard like interface, AutoML provides abilities to define/select/clean data set, conduct pre-processing on the selected data set, perform data analysis, train, and test models based on provided algorithm set. By means of graphical interfaces, the application also compares the trained models based on different variables, such as F1 score, accuracy, precision, recall. The generated models are saved to be used later.

			AutoML will be used in CircularTwAIN to cover all of the above listed functionalities. AI Module that will be used to reduce CO2 output from the sensors that are available on the plant and laboratory analysis as a label. This module includes data processing and helps to train multiple ML algorithms at once to compare results.

	• '''Reference, URL''':
			• '''Reference, URL''': Avaliable upon request

	• '''Relevant Domain/Industry''': All/Smart Industry		• '''Relevant Domain/Industry''': All/Smart Industry

	• '''Application in relevant Projects/Initiatives''':		• '''Application in relevant Projects/Initiatives''': COGNITWIN

	• '''Type''':		• '''Type''': Web application (platform independent)
			It has a preconfigured pipeline architecture following wizard like steps implemented by functionalies in the order of provided tabs (data selection, preprocessing, analysis, algorithm selection, model training, model comparison, test, saving). LSTM, KNN, RF, GBT, MLP, SVM

	• '''AI Breadth''':		• '''AI Breadth''': ML, DL

	• '''Learning Ability''':		• '''Learning Ability''': Supervised Learning, currently, others can be added later

	• '''Related technologies''':		• '''Related technologies''': Python, Scikit-learn, Keras, Flask (API), Java Script, HTML, CSS,React.js, PostgreSQL, TimeScaleDB

	• '''License Information''':		• '''License Information''': Restricted

	• '''Related to circularity and sustainability''':		• '''Related to circularity and sustainability''': RUL estimation and predictive maintenance models developed before resulted in energy minimization, and hence carbon footprint reduction. This AI module will be used to minimize steam consumption and CO2 output.

	• '''Audience''':		• '''Audience''': Users, developers, industry independent

Admin ugqr649i: Created page with " • '''Short Description''': • '''Reference, URL''': • '''Relevant Domain/Industry''': All/Smart Industry • '''Application in relevant Projects/Initiatives''':..."

2023-04-26T13:45:38Z

Created page with " • '''Short Description''': • '''Reference, URL''': • '''Relevant Domain/Industry''': All/Smart Industry • '''Application in relevant Projects/Initiatives''':..."

New page

• '''Short Description''':

• '''Reference, URL''':

• '''Relevant Domain/Industry''': All/Smart Industry

• '''Application in relevant Projects/Initiatives''':

• '''Type''':

• '''AI Breadth''':

• '''Learning Ability''':

• '''Related technologies''':

• '''License Information''':

• '''Related to circularity and sustainability''':

• '''Audience''':

Go back to the '''[[AI portfolio of reference implementations]]'''