Neural-Network-Based Time Control for Microwave Oven Heating of Food Products Distributed by a Solar-Powered Vending Machine with Energy Management Considerations
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Saurabh Sharma & Vijay Kumar Gahlawat & Kumar Rahul & Rahul S Mor & Mohit Malik, 2021. "Sustainable Innovations in the Food Industry through Artificial Intelligence and Big Data Analytics," Logistics, MDPI, vol. 5(4), pages 1-16, September.
- Răzvan Calotă & Mihai Savaniu & Alina Girip & Ilinca Năstase & Matei Răzvan Georgescu & Oana Tonciu, 2022. "Study on Energy Efficiency of an Off-Grid Vending Machine with Compact Heat Exchangers and Low GWP Refrigerant Powered by Solar Energy," Energies, MDPI, vol. 15(12), pages 1-26, June.
- Mojtaba Nabipour & Pooyan Nayyeri & Hamed Jabani & Amir Mosavi, 2020. "Deep learning for Stock Market Prediction," Papers 2004.01497, arXiv.org.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Andreea-Alina CORNEA, 2023. "Big Data in Food Industry: A Technical Summary of Modern Approaches Used in Data Extraction," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 27(2), pages 25-35.
- Priyank Sonkiya & Vikas Bajpai & Anukriti Bansal, 2021. "Stock price prediction using BERT and GAN," Papers 2107.09055, arXiv.org.
- Xiaolu Wei & Yubo Tian & Na Li & Huanxin Peng, 2024. "Evaluating ensemble learning techniques for stock index trend prediction: a case of China," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 23(3), pages 505-530, September.
- Ramakrishnan Ramanathan & Yanqing Duan & Tahmina Ajmal & Katarzyna Pelc & James Gillespie & Sahar Ahmadzadeh & Joan Condell & Imke Hermens & Usha Ramanathan, 2023. "Motivations and Challenges for Food Companies in Using IoT Sensors for Reducing Food Waste: Some Insights and a Road Map for the Future," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
- Mwangakala, Hilda Abraham & Mongi, Hector & Ishengoma, Fredrick & Shao, Deo & Chali, Frederick & Mambile, Cesilia & Julius, Bernard, 2024. "Emerging digital technologies potential in promoting equitable agricultural supply chain: A scoping review," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
- Suya Jin & Guiyan Liu & Qifeng Bai, 2023. "Deep Learning in COVID-19 Diagnosis, Prognosis and Treatment Selection," Mathematics, MDPI, vol. 11(6), pages 1-16, March.
- Mohammed El Amine Senoussaoui & Mostefa Brahami & Issouf Fofana, 2021. "Transformer Oil Quality Assessment Using Random Forest with Feature Engineering," Energies, MDPI, vol. 14(7), pages 1-15, March.
- Arvind Kumar Sinha & Pradeep Shende, 2024. "Uncertainty Optimization Based Feature Selection Model for Stock Marketing," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 357-389, January.
- Nabanita Das & Bikash Sadhukhan & Rajdeep Ghosh & Satyajit Chakrabarti, 2024. "Developing Hybrid Deep Learning Models for Stock Price Prediction Using Enhanced Twitter Sentiment Score and Technical Indicators," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3407-3446, December.
- Damian Ślusarczyk & Robert Ślepaczuk, 2023. "Optimal Markowitz Portfolio Using Returns Forecasted with Time Series and Machine Learning Models," Working Papers 2023-17, Faculty of Economic Sciences, University of Warsaw.
- Pawan Kumar Singh & Anushka Chouhan & Rajiv Kumar Bhatt & Ravi Kiran & Ansari Saleh Ahmar, 2022. "Implementation of the SutteARIMA method to predict short-term cases of stock market and COVID-19 pandemic in USA," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2023-2033, August.
- Rocha, Thiago Torres Martins & Teggar, Mohamed & Trevizoli, Paulo Vinicius & de Oliveira, Raphael Nunes, 2023. "Potential of latent thermal energy storage for performance improvement in small-scale refrigeration units: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
- Mufhumudzi Muthivhi & Terence L. van Zyl, 2022. "Fusion of Sentiment and Asset Price Predictions for Portfolio Optimization," Papers 2203.05673, arXiv.org.
- Juan C. King & Roberto Dale & Jos'e M. Amig'o, 2024. "Blockchain Metrics and Indicators in Cryptocurrency Trading," Papers 2403.00770, arXiv.org.
- Satya Verma & Satya Prakash Sahu & Tirath Prasad Sahu, 2024. "Two-Stage Hybrid Feature Selection Approach Using Levy’s Flight Based Chicken Swarm Optimization for Stock Market Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2193-2224, June.
- El Bhilat, El Mehdi & El Jaouhari, Asmae & Hamidi, L. Saadia, 2024. "Assessing the influence of artificial intelligence on agri-food supply chain performance: the mediating effect of distribution network efficiency," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
- Mohit Malik & Vijay Kumar Gahlawat & Rahul S Mor & Vijay Dahiya & Mukheshwar Yadav, 2022. "Application of Optimization Techniques in the Dairy Supply Chain: A Systematic Review," Logistics, MDPI, vol. 6(4), pages 1-16, October.
- S. Divyashree & Christy Jackson Joshua & Abdul Quadir Md & Senthilkumar Mohan & A. Sheik Abdullah & Ummul Hanan Mohamad & Nisreen Innab & Ali Ahmadian, 2024. "Enabling business sustainability for stock market data using machine learning and deep learning approaches," Annals of Operations Research, Springer, vol. 342(1), pages 287-322, November.
- Zefan Dong & Yonghui Zhou, 2024. "A Novel Hybrid Model for Financial Forecasting Based on CEEMDAN-SE and ARIMA-CNN-LSTM," Mathematics, MDPI, vol. 12(16), pages 1-16, August.
- Prantosh Kumar Paul & Abhijit Bandyopadhyay & Mustafa Kayyali & Nilanjan Das & Ritam Chatterjee & Sushil K. Sharma, 2025. "Integrating Big Data and AI in Nutrition: Current Trends and Future Directions," International Journal of Reliable and Quality E-Healthcare (IJRQEH), IGI Global Scientific Publishing, vol. 14(1), pages 1-22, January.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:19:p:6953-:d:1253846. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.