Deep learning algorithms were used to generate photovoltaic renewable energy in saline water analysis via an oxidation process
The amount of particles and organic matter in wash-waters and effluent from the processing of fruits and vegetables determines whether they need to be treated to fulfil regulatory standards for their intended use. This research proposes a novel technique in photovoltaic cell-based renewable energy i...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , , , , |
| منشور في: |
2023
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| الوصول للمادة أونلاين: | http://hdl.handle.net/11675/10918 http://www.scopus.com/inward/record.url?scp=85153221773&partnerID=8YFLogxK |
| الوسوم: |
إضافة وسم
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| _version_ | 1870679734265839616 |
|---|---|
| author | Anupong, Wongchai |
| author2 | Bostani, Ali Dhiman, Gaurav Mehbodniya, Abolfazl Murali Dharan, A. R. Singh, Bharat Webber, Julian L. |
| author2_role | author author author author author author |
| author_facet | Anupong, Wongchai Bostani, Ali Dhiman, Gaurav Mehbodniya, Abolfazl Murali Dharan, A. R. Singh, Bharat Webber, Julian L. |
| author_role | author |
| dc.creator.none.fl_str_mv | Anupong, Wongchai Bostani, Ali Dhiman, Gaurav Mehbodniya, Abolfazl Murali Dharan, A. R. Singh, Bharat Webber, Julian L. |
| dc.date.none.fl_str_mv | 2023-01-01 2024-02-05T08:32:40Z 2024-02-05T08:32:40Z |
| dc.identifier.none.fl_str_mv | 10.2166/wrd.2023.071 http://hdl.handle.net/11675/10918 http://www.scopus.com/inward/record.url?scp=85153221773&partnerID=8YFLogxK |
| dc.publisher.none.fl_str_mv | IWA Publishing |
| dc.relation.none.fl_str_mv | Electrical and Computer Engineering Water Reuse |
| dc.title.none.fl_str_mv | Deep learning algorithms were used to generate photovoltaic renewable energy in saline water analysis via an oxidation process |
| dc.type.none.fl_str_mv | Conference Presentations/Proceedings info:eu-repo/semantics/publishedVersion |
| description | The amount of particles and organic matter in wash-waters and effluent from the processing of fruits and vegetables determines whether they need to be treated to fulfil regulatory standards for their intended use. This research proposes a novel technique in photovoltaic cell-based renewable energy in saline water analysis using the oxidation process and deep learning techniques. Here, the saline water oxidation is carried out based on photovoltaic cell-based renewable and saline water analysis is done using Markov fuzzy-based Q-radial function neural networks (MFQRFNN). The plan is entirely web-oriented to enable better control and effective monitoring of water consumption. This monitoring makes use of a communication system that collects data in the form of irregularly spaced time series. Experimental analysis has been carried out based on water salinity data in terms of accuracy, precision, recall, specificity, computational cost, and kappa coefficient. |
| id | AUKR_a605fbc762aa2eb75b0b0b99ef36eb1a |
| identifier_str_mv | 10.2166/wrd.2023.071 |
| network_acronym_str | AUKR |
| network_name_str | AU Kuwait Rep |
| oai_identifier_str | oai:dspace.auk.edu.kw:11675/10918 |
| publishDate | 2023 |
| publisher.none.fl_str_mv | IWA Publishing |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Deep learning algorithms were used to generate photovoltaic renewable energy in saline water analysis via an oxidation processAnupong, WongchaiBostani, AliDhiman, GauravMehbodniya, AbolfazlMurali Dharan, A. R.Singh, BharatWebber, Julian L.The amount of particles and organic matter in wash-waters and effluent from the processing of fruits and vegetables determines whether they need to be treated to fulfil regulatory standards for their intended use. This research proposes a novel technique in photovoltaic cell-based renewable energy in saline water analysis using the oxidation process and deep learning techniques. Here, the saline water oxidation is carried out based on photovoltaic cell-based renewable and saline water analysis is done using Markov fuzzy-based Q-radial function neural networks (MFQRFNN). The plan is entirely web-oriented to enable better control and effective monitoring of water consumption. This monitoring makes use of a communication system that collects data in the form of irregularly spaced time series. Experimental analysis has been carried out based on water salinity data in terms of accuracy, precision, recall, specificity, computational cost, and kappa coefficient.IWA Publishing2024-02-05T08:32:40Z2024-02-05T08:32:40Z2023-01-01Conference Presentations/Proceedingsinfo:eu-repo/semantics/publishedVersion10.2166/wrd.2023.071http://hdl.handle.net/11675/10918http://www.scopus.com/inward/record.url?scp=85153221773&partnerID=8YFLogxKElectrical and Computer EngineeringWater Reuseoai:dspace.auk.edu.kw:11675/109182024-02-05T08:32:40Z |
| spellingShingle | Deep learning algorithms were used to generate photovoltaic renewable energy in saline water analysis via an oxidation process Anupong, Wongchai |
| status_str | publishedVersion |
| title | Deep learning algorithms were used to generate photovoltaic renewable energy in saline water analysis via an oxidation process |
| title_full | Deep learning algorithms were used to generate photovoltaic renewable energy in saline water analysis via an oxidation process |
| title_fullStr | Deep learning algorithms were used to generate photovoltaic renewable energy in saline water analysis via an oxidation process |
| title_full_unstemmed | Deep learning algorithms were used to generate photovoltaic renewable energy in saline water analysis via an oxidation process |
| title_short | Deep learning algorithms were used to generate photovoltaic renewable energy in saline water analysis via an oxidation process |
| title_sort | Deep learning algorithms were used to generate photovoltaic renewable energy in saline water analysis via an oxidation process |
| url | http://hdl.handle.net/11675/10918 http://www.scopus.com/inward/record.url?scp=85153221773&partnerID=8YFLogxK |