Artículos de revistas sobre el tema "Energy Efficient Machine Learning System"
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Reddy, V. Sandeep Kumar, Saravanan T., N. T. Velusudha y T. Sunder Selwyn. "Smart Grid Management System Based on Machine Learning Algorithms for Efficient Energy Distribution". E3S Web of Conferences 387 (2023): 02005. http://dx.doi.org/10.1051/e3sconf/202338702005.
Texto completoHusainy, Avesahemad S. N., Sairam A. Patil, Atharva S. Sinfal, Vasim M. Mujawar y Chandrashekhar S. Sinfal. "Parameter Optimization of Refrigeration Chiller by Machine Learning". Asian Journal of Electrical Sciences 12, n.º 1 (22 de junio de 2023): 39–45. http://dx.doi.org/10.51983/ajes-2023.12.1.3684.
Texto completoWu, Qingying, Benjamin K. Ng y Chan-Tong Lam. "Energy-Efficient Cooperative Spectrum Sensing Using Machine Learning Algorithm". Sensors 22, n.º 21 (27 de octubre de 2022): 8230. http://dx.doi.org/10.3390/s22218230.
Texto completoZhang, Huanhuan, Jigeng Li y Mengna Hong. "Machine Learning-Based Energy System Model for Tissue Paper Machines". Processes 9, n.º 4 (9 de abril de 2021): 655. http://dx.doi.org/10.3390/pr9040655.
Texto completoNour, Samar, Shahira Habashy y Sameh Salem. "Energy-Efficient Cache Partitioning Using Machine Learning for Embedded Systems". Jordan Journal of Electrical Engineering 9, n.º 3 (2023): 285. http://dx.doi.org/10.5455/jjee.204-1669909560.
Texto completoIsmail, Mahmoud M. "A Machine Learning Approach for Energy-Efficient IoT Systems". Journal of Intelligent Systems and Internet of Things 1, n.º 1 (2020): 61–69. http://dx.doi.org/10.54216/jisiot.010105.
Texto completoWaqas Khan, Prince, Yung-Cheol Byun, Sang-Joon Lee y Namje Park. "Machine Learning Based Hybrid System for Imputation and Efficient Energy Demand Forecasting". Energies 13, n.º 11 (26 de mayo de 2020): 2681. http://dx.doi.org/10.3390/en13112681.
Texto completoDixit, Abhishek y Santosh Kumar. "Machine Learning Based Efficient Protection Scheme for AC Microgrid". INTERNATIONAL RESEARCH JOURNAL OF ENGINEERING & APPLIED SCIENCES 10, n.º 4 (31 de diciembre de 2022): 18–23. http://dx.doi.org/10.55083/irjeas.2022.v10i04009.
Texto completoKhan, Murad, Junho Seo y Dongkyun Kim. "Towards Energy Efficient Home Automation: A Deep Learning Approach". Sensors 20, n.º 24 (15 de diciembre de 2020): 7187. http://dx.doi.org/10.3390/s20247187.
Texto completoLee, Jin-Hyun, Hye-In Lee, Kyoung-Hwan Ji y Young-Hum Cho. "Optimal Economizer Control of VAV System using Machine Learning". E3S Web of Conferences 396 (2023): 03034. http://dx.doi.org/10.1051/e3sconf/202339603034.
Texto completoLokesh, Nitish y Dr Pawan Kumar. "Billing System using Machine Learning". International Journal for Research in Applied Science and Engineering Technology 10, n.º 4 (30 de abril de 2022): 1420–26. http://dx.doi.org/10.22214/ijraset.2022.41546.
Texto completoKang, Minseon, Yongseok Lee y Moonju Park. "Energy Efficiency of Machine Learning in Embedded Systems Using Neuromorphic Hardware". Electronics 9, n.º 7 (30 de junio de 2020): 1069. http://dx.doi.org/10.3390/electronics9071069.
Texto completoSankar, Sasirekha, S. Amudha, P. Madhavan y Dev Krishna Lamba. "Energy Efficient Medium-Term Wind Speed Prediction System using Machine Learning Models". IOP Conference Series: Materials Science and Engineering 1130, n.º 1 (1 de abril de 2021): 012085. http://dx.doi.org/10.1088/1757-899x/1130/1/012085.
Texto completoTrivedi, Vijay K. "Energy Aware Routing Protocol with Data Fusion and Machine Learning". International Journal of Wireless and Ad Hoc Communication 5, n.º 1 (2022): 22–35. http://dx.doi.org/10.54216/ijwac.050102.
Texto completoTalei, Hanaa, Driss Benhaddou, Carlos Gamarra, Houda Benbrahim y Mohamed Essaaidi. "Smart Building Energy Inefficiencies Detection through Time Series Analysis and Unsupervised Machine Learning". Energies 14, n.º 19 (23 de septiembre de 2021): 6042. http://dx.doi.org/10.3390/en14196042.
Texto completoDarus, Muhamad Firdaus, Fakrulradzi Idris y Norlezah Hashim. "Energy-efficient non-orthogonal multiple access for wireless communication system". International Journal of Electrical and Computer Engineering (IJECE) 13, n.º 2 (1 de abril de 2023): 1654. http://dx.doi.org/10.11591/ijece.v13i2.pp1654-1668.
Texto completoK., Babu, Sivasubramanian S., Nivetha C.S., Senthil Kumar R. y Mohana Soundari. "Intelligent Energy Management System for Smart Grids Using Machine Learning Algorithms". E3S Web of Conferences 387 (2023): 05004. http://dx.doi.org/10.1051/e3sconf/202338705004.
Texto completoCaliskan, Abdullah, Conor O’Brien, Krishna Panduru, Joseph Walsh y Daniel Riordan. "An Efficient Siamese Network and Transfer Learning-Based Predictive Maintenance System for More Sustainable Manufacturing". Sustainability 15, n.º 12 (8 de junio de 2023): 9272. http://dx.doi.org/10.3390/su15129272.
Texto completoM.Prakash, U., Priyanshu Madan, K. R. GokulAnand y S. Prabhakaran. "Intelligent Lighting System and Garbage Monitoring System". International Journal of Engineering & Technology 7, n.º 3.12 (20 de julio de 2018): 876. http://dx.doi.org/10.14419/ijet.v7i3.12.16554.
Texto completoA., Nagesh*. "Energy Audit System for Households using Machine Learning". Regular issue 10, n.º 7 (30 de mayo de 2021): 33–36. http://dx.doi.org/10.35940/ijitee.g8895.0510721.
Texto completoKhirirat, Sarit, Sindri Magnússon, Arda Aytekin y Mikael Johansson. "A Flexible Framework for Communication-Efficient Machine Learning". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 9 (18 de mayo de 2021): 8101–9. http://dx.doi.org/10.1609/aaai.v35i9.16987.
Texto completoAbebe, Misganaw, Yongwoo Shin, Yoojeong Noh, Sangbong Lee y Inwon Lee. "Machine Learning Approaches for Ship Speed Prediction towards Energy Efficient Shipping". Applied Sciences 10, n.º 7 (28 de marzo de 2020): 2325. http://dx.doi.org/10.3390/app10072325.
Texto completoLeonowicz, Zbigniew y Michal Jasinski. "Machine Learning and Data Mining Applications in Power Systems". Energies 15, n.º 5 (24 de febrero de 2022): 1676. http://dx.doi.org/10.3390/en15051676.
Texto completoLiu, Junxia y Wen Liu. "CA Energy Saving Joint Resource Optimization Scheme Based on 5G Channel Information Prediction of Machine Learning". Sustainability 14, n.º 24 (19 de diciembre de 2022): 17012. http://dx.doi.org/10.3390/su142417012.
Texto completoBaidoo, Charity Yaa Mansa, Winfred Yaokumah y Ebenezer Owusu. "Estimating Overhead Performance of Supervised Machine Learning Algorithms for Intrusion Detection". International Journal of Information Technologies and Systems Approach 16, n.º 1 (3 de febrero de 2023): 1–19. http://dx.doi.org/10.4018/ijitsa.316889.
Texto completoN, Miss Swapna y Mrs Renuka Malge. "Classification and Detection of Bone Fracture Using Machine Learning". International Journal for Research in Applied Science and Engineering Technology 10, n.º 7 (31 de julio de 2022): 1636–40. http://dx.doi.org/10.22214/ijraset.2022.45523.
Texto completoHuang, Xiaoyan, Ke Zhang, Fan Wu y Supeng Leng. "Collaborative Machine Learning for Energy-Efficient Edge Networks in 6G". IEEE Network 35, n.º 6 (noviembre de 2021): 12–19. http://dx.doi.org/10.1109/mnet.100.2100313.
Texto completoAlhmiedat, Tareq. "Fingerprint-Based Localization Approach for WSN Using Machine Learning Models". Applied Sciences 13, n.º 5 (27 de febrero de 2023): 3037. http://dx.doi.org/10.3390/app13053037.
Texto completoCardoso, Daniel, Daniel Nunes, João Faria, Paulo Fael y Pedro D. Gaspar. "Intelligent Micro-Cogeneration Systems for Residential Grids: A Sustainable Solution for Efficient Energy Management". Energies 16, n.º 13 (6 de julio de 2023): 5215. http://dx.doi.org/10.3390/en16135215.
Texto completoOh, Myeung Suk, Gibum Kim y Hyuncheol Park. "Machine-Learning-Based Link Adaptation for Energy-Efficient MIMO-OFDM Systems". Journal of Korean Institute of Electromagnetic Engineering and Science 27, n.º 5 (7 de junio de 2016): 407–15. http://dx.doi.org/10.5515/kjkiees.2016.27.5.407.
Texto completoKaushik, Akshay y Varun Goel. "Building an Efficient Intrusion Detection System using Feature Selection and Machine Learning". International Journal for Research in Applied Science and Engineering Technology 10, n.º 5 (31 de mayo de 2022): 5314–23. http://dx.doi.org/10.22214/ijraset.2022.43434.
Texto completoChatterjee, Rajdeep, Oindrila Das, Ridam Kundu y Soumik Podder. "Machine Learning Inspired Smart Agriculture System with Crop Prediction". International Journal for Research in Applied Science and Engineering Technology 11, n.º 1 (31 de enero de 2023): 1511–17. http://dx.doi.org/10.22214/ijraset.2023.48841.
Texto completoNoori, Nematullah, Vyenkatesh Bawanthad, Mayur Pakhare, Ramashray Agrawal y Vinod Kimbahune. "Phishing URL Detection using Machine Learning". International Journal for Research in Applied Science and Engineering Technology 11, n.º 5 (31 de mayo de 2023): 3645–48. http://dx.doi.org/10.22214/ijraset.2023.52342.
Texto completoMittal, Mohit, Rocío Pérez de Prado, Yukiko Kawai, Shinsuke Nakajima y José E. Muñoz-Expósito. "Machine Learning Techniques for Energy Efficiency and Anomaly Detection in Hybrid Wireless Sensor Networks". Energies 14, n.º 11 (27 de mayo de 2021): 3125. http://dx.doi.org/10.3390/en14113125.
Texto completoR., Udendhran, Sasikala R., Nishanthi R. y Vasanthi J. "Smart Energy Consumption Control in Commercial Buildings Using Machine Learning and IOT". E3S Web of Conferences 387 (2023): 02003. http://dx.doi.org/10.1051/e3sconf/202338702003.
Texto completoReddy, Suraka Maha Lakshmi y Adusumilli Yagna Gayathri. "Healthcare Monitoring System for Diabetic Patients Using Machine Learning". International Journal for Research in Applied Science and Engineering Technology 10, n.º 11 (30 de noviembre de 2022): 122–32. http://dx.doi.org/10.22214/ijraset.2022.47262.
Texto completoKhabbouchi, Imed, Dhaou Said, Aziz Oukaira, Idir Mellal y Lyes Khoukhi. "Machine Learning and Game-Theoretic Model for Advanced Wind Energy Management Protocol (AWEMP)". Energies 16, n.º 5 (24 de febrero de 2023): 2179. http://dx.doi.org/10.3390/en16052179.
Texto completoKhac Le, Hung y SoYoung Kim. "Machine Learning Based Energy-Efficient Design Approach for Interconnects in Circuits and Systems". Applied Sciences 11, n.º 3 (20 de enero de 2021): 915. http://dx.doi.org/10.3390/app11030915.
Texto completoNeelaveni, Dr R., Abhinav . y Sahas . "Analysis of Efficient Intrusion Detection System using Ensemble Learning". International Journal for Research in Applied Science and Engineering Technology 11, n.º 5 (31 de mayo de 2023): 1521–30. http://dx.doi.org/10.22214/ijraset.2023.51858.
Texto completoForootan, Mohammad Mahdi, Iman Larki, Rahim Zahedi y Abolfazl Ahmadi. "Machine Learning and Deep Learning in Energy Systems: A Review". Sustainability 14, n.º 8 (18 de abril de 2022): 4832. http://dx.doi.org/10.3390/su14084832.
Texto completoLokesh, Nitish y Dr Pawan Kumar. "A Literature Review on Billing System using Machine Learning". International Journal for Research in Applied Science and Engineering Technology 10, n.º 4 (30 de abril de 2022): 645–48. http://dx.doi.org/10.22214/ijraset.2022.41199.
Texto completoR, Praveenkumar, Kirthika ., Durai Arumugam y Dinesh . "Hybridization of Machine Learning Techniques for WSN Optimal Cluster Head Selection". International Journal of Electrical and Electronics Research 11, n.º 2 (19 de junio de 2023): 426–33. http://dx.doi.org/10.37391/ijeer.110224.
Texto completoAladwani, Habeeb A. H. R., Mohd Khairol Anuar Ariffin y Faizal Mustapha. "A supervised machine-learning method for optimizing the automatic transmission system of wind turbines". Engineering Solid Mechanics 10, n.º 1 (2022): 35–56. http://dx.doi.org/10.5267/j.esm.2021.11.001.
Texto completoTovar, Nathaniel, Sean (Seok-Chul) Kwon y Jinseong Jeong. "Image Upscaling with Deep Machine Learning for Energy-Efficient Data Communications". Electronics 12, n.º 3 (30 de enero de 2023): 689. http://dx.doi.org/10.3390/electronics12030689.
Texto completoLi, Sijia, Arman Oshnoei, Frede Blaabjerg y Amjad Anvari-Moghaddam. "Hierarchical Control for Microgrids: A Survey on Classical and Machine Learning-Based Methods". Sustainability 15, n.º 11 (1 de junio de 2023): 8952. http://dx.doi.org/10.3390/su15118952.
Texto completoPandey, Mrs Arjoo. "Machine Learning". International Journal for Research in Applied Science and Engineering Technology 11, n.º 8 (31 de agosto de 2023): 864–69. http://dx.doi.org/10.22214/ijraset.2023.55224.
Texto completoGayke, Prof P. S., Gaurav Bhise, Nikhil Bhor, Jagdish Bhagwat y Tanvi Alkute. "An Efficient Spam Detection Technique for IoT Devices Using Machine Learning". International Journal for Research in Applied Science and Engineering Technology 11, n.º 5 (31 de mayo de 2023): 7534–37. http://dx.doi.org/10.22214/ijraset.2023.53527.
Texto completoStyła, Michał, Bartłomiej Kiczek, Grzegorz Kłosowski, Tomasz Rymarczyk, Przemysław Adamkiewicz, Dariusz Wójcik y Tomasz Cieplak. "Machine Learning-Enhanced Radio Tomographic Device for Energy Optimization in Smart Buildings". Energies 16, n.º 1 (27 de diciembre de 2022): 275. http://dx.doi.org/10.3390/en16010275.
Texto completoAlagumalai, Avinash, Balaji Devarajan, Hua Song, Somchai Wongwises, Rodrigo Ledesma-Amaro, Omid Mahian, Mikhail Sheremet y Eric Lichtfouse. "Machine learning in biohydrogen production: a review". Biofuel Research Journal 10, n.º 2 (1 de junio de 2023): 1844–58. http://dx.doi.org/10.18331/brj2023.10.2.4.
Texto completoPetruschke, L., G. Elserafi, B. Ioshchikhes y M. Weigold. "MACHINE LEARNING BASED IDENTIFICATION OF ENERGY EFFICIENCY MEASURES FOR MACHINE TOOLS USING LOAD PROFILES AND MACHINE SPECIFIC META DATA". MM Science Journal 2021, n.º 5 (3 de noviembre de 2021): 5061–68. http://dx.doi.org/10.17973/mmsj.2021_11_2021153.
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