{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T04:27:12Z","timestamp":1777955232461,"version":"3.51.4"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"2-3","license":[{"start":{"date-parts":[[2023,6,15]],"date-time":"2023-06-15T00:00:00Z","timestamp":1686787200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,6,15]],"date-time":"2023-06-15T00:00:00Z","timestamp":1686787200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100002383","name":"King Saud University","doi-asserted-by":"publisher","award":["RSPD2023Rxxx"],"award-info":[{"award-number":["RSPD2023Rxxx"]}],"id":[{"id":"10.13039\/501100002383","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002383","name":"King Saud University","doi-asserted-by":"publisher","award":["RSPD2023Rxxx"],"award-info":[{"award-number":["RSPD2023Rxxx"]}],"id":[{"id":"10.13039\/501100002383","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cogn Tech Work"],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1007\/s10111-023-00728-4","type":"journal-article","created":{"date-parts":[[2023,6,15]],"date-time":"2023-06-15T13:02:17Z","timestamp":1686834137000},"page":"291-304","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Towards efficient human\u2013machine interaction for home energy management with seasonal scheduling using deep fuzzy neural optimizer"],"prefix":"10.1007","volume":"25","author":[{"given":"Sakeena","family":"Javaid","sequence":"first","affiliation":[]},{"given":"Nadeem","family":"Javaid","sequence":"additional","affiliation":[]},{"given":"Musaed","family":"Alhussein","sequence":"additional","affiliation":[]},{"given":"Khursheed","family":"Aurangzeb","sequence":"additional","affiliation":[]},{"given":"Sohail","family":"Iqbal","sequence":"additional","affiliation":[]},{"given":"Muhammad Shahid","family":"Anwar","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,6,15]]},"reference":[{"key":"728_CR1","doi-asserted-by":"crossref","unstructured":"Ahrarinouri M, Rastegar M, Seifi AR (2020) Multi-agent reinforcement learning for energy management in residential buildings. IEEE Trans Ind Inf.1-8","DOI":"10.1109\/TII.2020.2977104"},{"issue":"9","key":"728_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/s18092802","volume":"18","author":"QU Ain","year":"2018","unstructured":"Ain QU, Iqbal S, Khan SA, Malik AW, Ahmad I, Javaid N (2018) IoT operating system based fuzzy inference system for home energy management system in smart buildings. Sensors 18(9):1\u201330","journal-title":"Sensors"},{"issue":"1","key":"728_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2897165","volume":"49","author":"MR Alam","year":"2016","unstructured":"Alam MR, St-Hilaire M, Kunz T (2016) Computational methods for residential energy cost optimization in smart grids: A survey. ACM Comput Surv (CSUR) 49(1):1\u201334","journal-title":"ACM Comput Surv (CSUR)"},{"key":"728_CR4","doi-asserted-by":"crossref","unstructured":"Ali ANF, Sulaima MF, Razak IAWA, Kadir AFA Mokhlis H (2023) Artificial intelligence application in demand response: advantages, issues, status, and challenges. IEEE Access","DOI":"10.1109\/ACCESS.2023.3237737"},{"key":"728_CR5","first-page":"2010","volume-title":"Adaptive Neuro-Fuzzy Systems","author":"AT Azar","year":"2010","unstructured":"Azar AT (2010) Adaptive Neuro-Fuzzy Systems. Electrical Communication and Electronics Systems Engineering department, Modern Science and Arts University (MSA), Egypt, p 2010"},{"key":"728_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2022.104260","volume":"89","author":"P Balakumar","year":"2023","unstructured":"Balakumar P, Vinopraba T, Chandrasekaran K (2023) Machine learning based demand response scheme for IoT enabled PV integrated smart building. Sustain Cities Soc 89:104260","journal-title":"Sustain Cities Soc"},{"key":"728_CR7","doi-asserted-by":"crossref","unstructured":"Bendaoud NMM, Farah N (2020). Using deep learning for short-term load forecasting. Neural Comput Appl, 1-13","DOI":"10.1007\/s00521-020-04856-0"},{"key":"728_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.buildenv.2019.106612","volume":"170","author":"D Bienvenido-Huertas","year":"2020","unstructured":"Bienvenido-Huertas D, Sanchez-Garcia D, Perez-Fargallo A, Rubio-Bellido C (2020) Optimization of energy saving with adaptive setpoint temperatures by calculating the prevailing mean outdoor air temperature. Build Environ 170:1\u201314","journal-title":"Build Environ"},{"key":"728_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2021.102938","volume":"70","author":"Q Chang","year":"2021","unstructured":"Chang Q, Ma X, Chen M, Gao X, Dehghani M (2021) A deep learning based secured energy management framework within a smart island. Sustain Cities Soc 70:102938","journal-title":"Sustain Cities Soc"},{"issue":"1","key":"728_CR10","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1109\/TCE.2018.2885034","volume":"65","author":"MT Chen","year":"2018","unstructured":"Chen MT, Lin CM (2018) Standby power management of a smart home appliance by using energy saving system with active loading feature identification. IEEE Trans Consum Electron 65(1):11\u201317","journal-title":"IEEE Trans Consum Electron"},{"key":"728_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2021.102856","volume":"69","author":"T Cheng","year":"2021","unstructured":"Cheng T, Zhu X, Gu X, Yang F, Mohammadi M (2021) Stochastic energy management and scheduling of microgrids in correlated environment: A deep learning-oriented approach. Sustain Cities Soc 69:102856","journal-title":"Sustain Cities Soc"},{"issue":"3","key":"728_CR12","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1109\/TCE.2019.2918922","volume":"65","author":"MA Devlin","year":"2019","unstructured":"Devlin MA, Hayes BP (2019) Non-intrusive load monitoring and classification of activities of daily living using residential smart meter data. IEEE Trans Consum Electron 65(3):339\u2013348","journal-title":"IEEE Trans Consum Electron"},{"key":"728_CR13","doi-asserted-by":"crossref","unstructured":"Ganguly S, Ahmed A, Wang F (2019) Optimised building energy and indoor microclimatic predictions using knowledge-based system identification in a historical art gallery. Neural Comput Appl, 1-18","DOI":"10.1007\/s00521-019-04224-7"},{"key":"728_CR14","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1016\/j.ijepes.2019.05.016","volume":"112","author":"AS Gazafroudi","year":"2019","unstructured":"Gazafroudi AS, Shafie-khah M, Heydarian-Forushani E, Hajizadeh A, Heidari A, Corchado JM, Catalao JP (2019) Two-stage stochastic model for the price-based domestic energy management problem. Int J Electr Power Energy Syst 112:404\u2013416","journal-title":"Int J Electr Power Energy Syst"},{"key":"728_CR15","unstructured":"GK JS, Jasper J (2020) MANFIS based SMART home energy management system to support SMART grid. Peer-to-Peer Networking and Applications, 1-12"},{"key":"728_CR16","doi-asserted-by":"crossref","unstructured":"Gray C, Ayre R, Hinton K, Campbell L (2019) \u2018Smart\u2019 Is Not Free: Energy Consumption of Consumer Home Automation Systems. IEEE Trans Consum Electron. 87-95","DOI":"10.1109\/TCE.2019.2962605"},{"key":"728_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2021.121873","volume":"238","author":"C Guo","year":"2022","unstructured":"Guo C, Wang X, Zheng Y, Zhang F (2022) Real-time optimal energy management of microgrid with uncertainties based on deep reinforcement learning. Energy 238:121873","journal-title":"Energy"},{"key":"728_CR18","doi-asserted-by":"publisher","first-page":"19614","DOI":"10.1109\/ACCESS.2020.2968038","volume":"8","author":"V Hosseinnezhad","year":"2020","unstructured":"Hosseinnezhad V, Shafie-Khah M, Siano P, Catalao JP (2020) An optimal home energy management paradigm with an adaptive neuro-fuzzy regulation. IEEE Access 8:19614\u201319628","journal-title":"IEEE Access"},{"key":"728_CR19","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1007\/s10111-017-0455-x","volume":"20","author":"A Jatoba","year":"2018","unstructured":"Jatoba A, Bellas HC, Koster I, Arcuri R, Vidal MCR, de Carvalho PVR (2018) Patient visits in poorly developed territories: a case study with community health workers. Cognit Technol Work 20:125\u2013152","journal-title":"Cognit Technol Work"},{"key":"728_CR20","first-page":"1","volume":"25","author":"S Javaid","year":"2020","unstructured":"Javaid S, Javaid N (2020) Comfort evaluation of seasonally and daily used residential load in smart buildings for hottest areas via predictive mean vote method. Sustain Comput Inf Syst 25:1\u201315","journal-title":"Sustain Comput Inf Syst"},{"key":"728_CR21","doi-asserted-by":"publisher","first-page":"33489","DOI":"10.1109\/ACCESS.2018.2828040","volume":"6","author":"S Javaid","year":"2018","unstructured":"Javaid S, Javaid N, Iqbal S, Guizani M, Al-Mogren A, Alamri A (2018) Energy management with a world-wide adaptive thermostat using fuzzy inference system. IEEE Access 6:33489\u201333502","journal-title":"IEEE Access"},{"issue":"5","key":"728_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/en12050815","volume":"12","author":"S Javaid","year":"2019","unstructured":"Javaid S, Javaid N, Saba T, Wadud Z, Rehman A, Haseeb A (2019) Intelligent resource allocation in residential buildings using consumer to fog to cloud based framework. Energies 12(5):1\u201323","journal-title":"Energies"},{"key":"728_CR23","doi-asserted-by":"crossref","unstructured":"Javaid S, Abdullah M, Javaid N, Sultana T, Ahmed J, Sattar NA (2019). Towards buildings energy management: using seasonal schedules under time of use pricing tariff via deep neuro-fuzzy optimizer. In 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC) (pp. 1594-1599). IEEE","DOI":"10.1109\/IWCMC.2019.8766673"},{"key":"728_CR24","doi-asserted-by":"publisher","first-page":"587","DOI":"10.1007\/s10111-020-00640-1","volume":"23","author":"K Jiang","year":"2021","unstructured":"Jiang K, Wang Y, Feng Z, Sze NN, Yu Z, Cui J (2021) Exploring the crossing behaviours and visual attention allocation of children in primary school in an outdoor road environment. Cognit Technol Work 23:587\u2013604","journal-title":"Cognit Technol Work"},{"key":"728_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.105287","volume":"115","author":"M Khalil","year":"2022","unstructured":"Khalil M, McGough AS, Pourmirza Z, Pazhoohesh M, Walker S (2022) Machine learning, deep learning and statistical analysis for forecasting building energy consumption-A systematic review. Eng Appl Artif Intell 115:105287","journal-title":"Eng Appl Artif Intell"},{"key":"728_CR26","doi-asserted-by":"crossref","unstructured":"Khan A, Javaid N (2020) TACMA: total annual cost minimization algorithm for optimal sizing of hybrid energy systems. J Ambient Intell Humaniz Comput, 1-21","DOI":"10.1007\/s12652-020-01964-6"},{"issue":"5","key":"728_CR27","doi-asserted-by":"publisher","first-page":"2187","DOI":"10.1109\/TSG.2015.2495145","volume":"7","author":"BG Kim","year":"2015","unstructured":"Kim BG, Zhang Y, Van Der Schaar M, Lee JW (2015) Dynamic pricing and energy consumption scheduling with reinforcement learning. IEEE Trans Smart Grid 7(5):2187\u20132198","journal-title":"IEEE Trans Smart Grid"},{"key":"728_CR28","unstructured":"Michael S (2013) Hot cities more sustainable than cold ones, study says. Available online: https:\/\/www.nbcnews.com\/news\/all\/hot-cities-more-sustainable-cold-ones-study-says-flna2b9119109, (accessed on 25 Feb. 2023)"},{"key":"728_CR29","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1016\/j.segan.2016.02.005","volume":"6","author":"E Mocanu","year":"2016","unstructured":"Mocanu E, Nguyen PH, Gibescu M, Kling WL (2016) Deep learning for estimating building energy consumption. Sustain Energy Grids Netw 6:91\u201399","journal-title":"Sustain Energy Grids Netw"},{"issue":"4","key":"728_CR30","doi-asserted-by":"publisher","first-page":"3698","DOI":"10.1109\/TSG.2018.2834219","volume":"10","author":"E Mocanu","year":"2018","unstructured":"Mocanu E, Mocanu DC, Nguyen PH, Liotta A, Webber ME, Gibescu M, Slootweg JG (2018) On-line building energy optimization using deep reinforcement learning. IEEE Trans Smart Grid 10(4):3698\u20133708","journal-title":"IEEE Trans Smart Grid"},{"key":"728_CR31","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1016\/j.neucom.2015.11.015","volume":"177","author":"K Muralitharan","year":"2016","unstructured":"Muralitharan K, Sakthivel R, Shi Y (2016) Multiobjective optimization technique for demand side management with load balancing approach in smart grid. Neurocomputing 177:110\u2013119","journal-title":"Neurocomputing"},{"key":"728_CR32","doi-asserted-by":"publisher","first-page":"3727","DOI":"10.1016\/j.egyr.2022.02.300","volume":"8","author":"S Panda","year":"2022","unstructured":"Panda S, Mohanty S, Rout PK, Sahu BK, Bajaj M, Zawbaa HM, Kamel S (2022) Residential demand side management model, optimization and future perspective: a review. Energy Rep 8:3727\u20133766","journal-title":"Energy Rep"},{"key":"728_CR33","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1016\/j.ijepes.2019.02.016","volume":"109","author":"P Paudyal","year":"2019","unstructured":"Paudyal P, Ni Z (2019) Smart home energy optimization with incentives compensation from inconvenience for shifting electric appliances. Int J Electr Power Energy Syst 109:652\u2013660","journal-title":"Int J Electr Power Energy Syst"},{"key":"728_CR34","doi-asserted-by":"publisher","first-page":"16876","DOI":"10.1109\/ACCESS.2020.2967798","volume":"8","author":"MB Rasheed","year":"2020","unstructured":"Rasheed MB, Qureshi MA, Javaid N, Alquthami T (2020) Dynamic pricing mechanism with the integration of renewable energy source in smart grid. IEEE Access 8:16876\u201316892","journal-title":"IEEE Access"},{"issue":"1","key":"728_CR35","first-page":"1","volume":"10","author":"S Ryu","year":"2017","unstructured":"Ryu S, Noh J, Kim H (2017) Deep neural network based demand side short term load forecasting. Energies 10(1):1\u201320","journal-title":"Energies"},{"issue":"2","key":"728_CR36","doi-asserted-by":"publisher","first-page":"210","DOI":"10.17775\/CSEEJPES.2016.01920","volume":"4","author":"YK Semero","year":"2018","unstructured":"Semero YK, Zhang J, Zheng D (2018) PV power forecasting using an integrated GA-PSO-ANFIS approach and Gaussian process regression based feature selection strategy. CSEE J Power Energy Syst 4(2):210\u2013218","journal-title":"CSEE J Power Energy Syst"},{"issue":"2","key":"728_CR37","doi-asserted-by":"publisher","first-page":"664","DOI":"10.1109\/JSYST.2013.2291943","volume":"8","author":"D Shahgoshtasbi","year":"2014","unstructured":"Shahgoshtasbi D, Jamshidi MM (2014) A new intelligent neuro? Fuzzy paradigm for energy-efficient homes. IEEE Syst J 8(2):664\u2013673","journal-title":"IEEE Syst J"},{"key":"728_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2022.126505","volume":"266","author":"R Shi","year":"2023","unstructured":"Shi R, Jiao Z (2023) Individual household demand response potential evaluation and identification based on machine learning algorithms. Energy 266:126505","journal-title":"Energy"},{"key":"728_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2022.125295","volume":"262","author":"J Shi","year":"2023","unstructured":"Shi J, Li C, Yan X (2023) Artificial intelligence for load forecasting: a stacking learning approach based on ensemble diversity regularization. Energy 262:125295","journal-title":"Energy"},{"issue":"1","key":"728_CR40","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1007\/s10111-019-00554-7","volume":"22","author":"NA Stanton","year":"2020","unstructured":"Stanton NA, Allison CK (2020) Driving towards a greener future: an application of cognitive work analysis to promote fuel-efficient driving. Cognit Technol Work 22(1):125\u2013142","journal-title":"Cognit Technol Work"},{"issue":"10","key":"728_CR41","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1002\/etep.2606","volume":"28","author":"S Tondolo de Miranda","year":"2018","unstructured":"Tondolo de Miranda S, Abaide A, Sperandio M, Santos MM, Zanghi E (2018) Application of artificial neural networks and fuzzy logic to long-term load forecast considering the price elasticity of electricity demand. Int Trans Electr Energy Syst 28(10):1\u201317","journal-title":"Int Trans Electr Energy Syst"},{"key":"728_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.energy.2019.116552","volume":"191","author":"DH Tran","year":"2020","unstructured":"Tran DH, Luong DL, Chou JS (2020) Nature-inspired metaheuristic ensemble model for forecasting energy consumption in residential buildings. Energy 191:1\u201313","journal-title":"Energy"},{"issue":"2","key":"728_CR43","doi-asserted-by":"publisher","first-page":"2135","DOI":"10.1109\/TIV.2023.3240517","volume":"24","author":"Z Wang","year":"2023","unstructured":"Wang Z, Xie X, Chen L, Song S, Wang Z (2023) Intrusion detection and network information security based on deep learning algorithm in urban rail transit management system. IEEE Trans Intell Transp Syst 24(2):2135\u20132143","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"728_CR44","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.119152","volume":"214","author":"G Wang","year":"2023","unstructured":"Wang G, Ma J, Wang Y, Tao T, Ren G, Zhu H (2023) SUDF-RS: a new foreign exchange rate prediction method considering the complementarity of supervised and unsupervised deep representation features. Expert Syst Appl 214:119152","journal-title":"Expert Syst Appl"},{"key":"728_CR45","doi-asserted-by":"crossref","unstructured":"Xu C, He X, Huang T, Huang, J (2019) A combined neurodynamic approach to optimize the real-time price-based demand response management problem using mixed zero-one programming. Neural Comput Appl, 1-11","DOI":"10.1007\/s00521-019-04283-w"},{"issue":"2","key":"728_CR46","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1109\/TCE.2020.2977964","volume":"66","author":"D Yang","year":"2020","unstructured":"Yang D, Gao X, Kong L, Pang Y, Zhou B (2020) An event-driven convolutional neural architecture for non-intrusive load monitoring of residential appliance. IEEE Trans Consum Electron 66(2):173\u2013182","journal-title":"IEEE Trans Consum Electron"},{"issue":"4","key":"728_CR47","doi-asserted-by":"publisher","first-page":"4435","DOI":"10.1109\/TSG.2018.2859821","volume":"10","author":"P Zeng","year":"2018","unstructured":"Zeng P, Li H, He H, Li S (2018) Dynamic energy management of a microgrid using approximate dynamic programming and deep recurrent neural network learning. IEEE Trans Smart Grid 10(4):4435\u20134445","journal-title":"IEEE Trans Smart Grid"}],"container-title":["Cognition, Technology & Work"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10111-023-00728-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10111-023-00728-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10111-023-00728-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,20]],"date-time":"2024-03-20T09:46:27Z","timestamp":1710927987000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10111-023-00728-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,15]]},"references-count":47,"journal-issue":{"issue":"2-3","published-print":{"date-parts":[[2023,8]]}},"alternative-id":["728"],"URL":"https:\/\/doi.org\/10.1007\/s10111-023-00728-4","relation":{},"ISSN":["1435-5558","1435-5566"],"issn-type":[{"value":"1435-5558","type":"print"},{"value":"1435-5566","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,15]]},"assertion":[{"value":"17 March 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 May 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 June 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}