{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T13:14:17Z","timestamp":1768914857007,"version":"3.49.0"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2019,4,20]],"date-time":"2019-04-20T00:00:00Z","timestamp":1555718400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2020,1]]},"DOI":"10.1007\/s12652-019-01299-x","type":"journal-article","created":{"date-parts":[[2019,4,20]],"date-time":"2019-04-20T08:02:35Z","timestamp":1555747355000},"page":"209-236","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["A fog based load forecasting strategy based on multi-ensemble classification for smart grids"],"prefix":"10.1007","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3711-9788","authenticated-orcid":false,"given":"Asmaa H.","family":"Rabie","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shereen H.","family":"Ali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmed I.","family":"Saleh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hesham A.","family":"Ali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,4,20]]},"reference":[{"issue":"2","key":"1299_CR1","first-page":"833","volume":"7","author":"M Afzal","year":"2016","unstructured":"Afzal M, Ashraf SMA (2016) Genetic algorithm for outlier detection. Int J Comput Sci Inf Technol (IJCSIT) 7(2):833\u2013835","journal-title":"Int J Comput Sci Inf Technol (IJCSIT)"},{"issue":"3","key":"1299_CR2","doi-asserted-by":"publisher","first-page":"383","DOI":"10.1007\/s12652-017-0452-1","volume":"8","author":"M Al-Ayyoub","year":"2017","unstructured":"Al-Ayyoub M, Jararweh Y, Rabab\u2019ah A, Aldwairi M (2017) Feature extraction and selection for Arabic tweets authorship authentication. J Ambient Intell Hum Comput 8(3):383\u2013393","journal-title":"J Ambient Intell Hum Comput"},{"issue":"10","key":"1299_CR3","first-page":"277","volume":"7","author":"H Alkhraisat","year":"2016","unstructured":"Alkhraisat H, Rashaideh H (2016) Dynamic inertia weight particle swarm optimization for solving nonogram puzzles. Int J Adv Comput Sci Appl (IJACSA) 7(10):277\u2013280","journal-title":"Int J Adv Comput Sci Appl (IJACSA)"},{"issue":"10","key":"1299_CR4","first-page":"1","volume":"2","author":"HF Atlam","year":"2018","unstructured":"Atlam HF, Walters RJ, Wills GB (2018) Fog computing and the internet of things: a review. Big Data Cognit Comput 2(10):1\u201318","journal-title":"Big Data Cognit Comput"},{"key":"1299_CR5","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/j.biosystems.2018.12.009","volume":"176","author":"SM Ayyad","year":"2019","unstructured":"Ayyad SM, Saleh AI, Labib LM (2019) Gene expression cancer classification using modified K-Nearest Neighbors technique. BioSystems 176:41\u201351","journal-title":"BioSystems"},{"issue":"2","key":"1299_CR6","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1007\/s12652-018-0702-x","volume":"10","author":"RK Barik","year":"2019","unstructured":"Barik RK, Dubey H, Mankodiya K, Sasane SA, Misra C (2019) GeoFog4Health: a fog-based SDI framework for geospatial health big data analysis. J Ambient Intell Hum Comput 10(2):551\u2013567","journal-title":"J Ambient Intell Hum Comput"},{"key":"1299_CR7","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1016\/j.scs.2017.12.034","volume":"38","author":"SE Bibri","year":"2018","unstructured":"Bibri SE (2018) The IoT for smart sustainable cities of the future: an analytical framework for sensor-based big data applications for environmental sustainability. Sustain Cities Soc 38:230\u2013253","journal-title":"Sustain Cities Soc"},{"key":"1299_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-018-1772-4","author":"Y Chen","year":"2018","unstructured":"Chen Y, Xiong J, Xu W, Zuo J (2018) A novel online incremental and decremental learning algorithm based on variable support vector machine. Cluster Comput. \nhttps:\/\/doi.org\/10.1007\/s10586-018-1772-4","journal-title":"Cluster Comput"},{"key":"1299_CR9","unstructured":"Di Mauro M, Di Sarno C (2014) A framework for Internet data real-time processing: a machine-learning approach. In: Proceedings of the 2014 international carnahan conference on security technology (ICCST), Rome, Italy, pp 1\u20136"},{"key":"1299_CR10","unstructured":"Elgarhy SM, Othman MM, Taha A, Hasanien HM (2018) Short term load forecasting using ANN technique. In: Proceedings of the 2017 nineteenth international middle east power systems conference (MEPCON), Cairo, Egypt, pp 1385\u20131394"},{"key":"1299_CR11","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1016\/j.procs.2017.08.280","volume":"113","author":"W Etaiwi","year":"2017","unstructured":"Etaiwi W, Biltawi M, Naymat G (2017) Evaluation of classification algorithms for banking customer\u2019s behavior under Apache Spark Data Processing System. Procedia Computer Science 113:559\u2013564","journal-title":"Procedia Computer Science"},{"issue":"3","key":"1299_CR12","doi-asserted-by":"publisher","first-page":"941","DOI":"10.1007\/s12205-018-1337-3","volume":"22","author":"X Feng","year":"2018","unstructured":"Feng X, Li S, Yuan C, Zeng P, Sun Y (2018) Prediction of slope stability using naive bayes classifier. KSCE J Civ Eng 22(3):941\u2013950","journal-title":"KSCE J Civ Eng"},{"issue":"4","key":"1299_CR13","doi-asserted-by":"publisher","first-page":"1197","DOI":"10.1007\/s12652-018-0685-7","volume":"9","author":"S Fong","year":"2018","unstructured":"Fong S, Li J, Song W, Tian Y, Wong RK, Dey N (2018) Predicting unusual energy consumption events from smart home sensor network by data stream mining with misclassified recall. J Ambient Intell Hum Comput 9(4):1197\u20131221","journal-title":"J Ambient Intell Hum Comput"},{"issue":"6","key":"1299_CR14","doi-asserted-by":"publisher","first-page":"1873","DOI":"10.1007\/s12652-017-0648-4","volume":"9","author":"N Ghadimi","year":"2018","unstructured":"Ghadimi N, Akbarimajd A, Shayeghi H, Abedinia O (2018) A new prediction model based on multi-block forecast engine in smart grid. J Ambient Intell Hum Comput 9(6):1873\u20131888","journal-title":"J Ambient Intell Hum Comput"},{"key":"1299_CR15","doi-asserted-by":"publisher","first-page":"565","DOI":"10.1016\/j.apenergy.2018.10.061","volume":"233","author":"Y He","year":"2019","unstructured":"He Y, Qin Y, Wang S, Wang X, Wang C (2019) Electricity consumption probability density forecasting method based on LASSO-Quantile Regression Neural Network. Appl Energy 233:565\u2013575","journal-title":"Appl Energy"},{"key":"1299_CR16","doi-asserted-by":"publisher","first-page":"592","DOI":"10.1016\/j.procs.2015.07.250","volume":"56","author":"M Jaradat","year":"2015","unstructured":"Jaradat M, Jarrah M, Bousselham A, Jararweh Y, Al-Ayyouba M (2015) The internet of energy: smart sensor networks and big data management for smart grid. Procedia Comput Sci 56:592\u2013597","journal-title":"Procedia Comput Sci"},{"issue":"4","key":"1299_CR17","doi-asserted-by":"publisher","first-page":"1683","DOI":"10.1007\/s11277-018-5336-y","volume":"99","author":"M Khan","year":"2018","unstructured":"Khan M, Han K, Karthik S (2018) Designing smart control systems based on internet of things and big data analytics. Wireless Pers Commun 99(4):1683\u20131697","journal-title":"Wireless Pers Commun"},{"issue":"1","key":"1299_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-015-0032-1","volume":"2","author":"S Landset","year":"2015","unstructured":"Landset S, Khoshgoftaar TM, Richter AN, Hasanin T (2015) A survey of open source tools for machine learning with big data in the Hadoop ecosystem. J Big Data 2(1):1\u201336","journal-title":"J Big Data"},{"key":"1299_CR19","doi-asserted-by":"publisher","first-page":"2085","DOI":"10.1016\/j.proeng.2011.11.2410","volume":"26","author":"X Li","year":"2011","unstructured":"Li X, Wang K, Liu L, Xin J, Yang H, Gao C (2011) Application of the entropy weight and TOPSIS method in safety evaluation of coal mines. Procedia Eng 26:2085\u20132091","journal-title":"Procedia Eng"},{"key":"1299_CR20","unstructured":"Li N, Zeng L, He Q, Shi Z (2012) Parallel implementation of apriori algorithm based on map-reduce. In: Proceedings of the 2012 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel\/Distributed Computing, Kyoto, Japan, pp 236\u2013241"},{"issue":"7","key":"1299_CR21","first-page":"1362","volume":"3","author":"A Mahajan","year":"2016","unstructured":"Mahajan A, Patil P (2016) Internet of things based residential power load forecasting. Int Res J Eng Technol (IRJET) 3(7):1362\u20131364","journal-title":"Int Res J Eng Technol (IRJET)"},{"issue":"1","key":"1299_CR22","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1007\/s12652-017-0525-1","volume":"9","author":"H Malik","year":"2018","unstructured":"Malik H, Shakshuki EM (2018) Performance evaluation of counter selection techniques to detect discontinuity in large-scale-systems. J Ambient Intell Hum Comput 9(1):43\u201359","journal-title":"J Ambient Intell Hum Comput"},{"issue":"1","key":"1299_CR23","first-page":"1","volume":"55","author":"R Meng","year":"2018","unstructured":"Meng R, Rice SG, Wang J, Sun X (2018) A fusion steganographic algorithm based on faster R-CNN. Comput Mater Continua 55(1):1\u201316","journal-title":"Comput Mater Continua"},{"issue":"1","key":"1299_CR24","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1007\/s12652-016-0426-8","volume":"9","author":"SM Mousavi","year":"2018","unstructured":"Mousavi SM, Harwood A, Karunasekera S, Maghrebi M (2018) Enhancing the quality of geometries of interest (GOIs) extracted from GPS trajectory data using spatio-temporal data aggregation and outlier detection. J Ambient Intell Hum Comput 9(1):173\u2013186","journal-title":"J Ambient Intell Hum Comput"},{"key":"1299_CR25","unstructured":"Okay FY, Ozdemir S (2016) A fog computing based smart grid model. In: Proceedings of the 2016 international symposium on networks, computers and communications (ISNCC), Yasmine Hammamet, Tunisia, pp 1\u2013 6"},{"issue":"4","key":"1299_CR26","doi-asserted-by":"publisher","first-page":"956","DOI":"10.1007\/s11036-017-0961-3","volume":"23","author":"M Ozger","year":"2018","unstructured":"Ozger M, Cetinkaya O, Akan OB (2018) Energy harvesting cognitive radio networking for iot-enabled smart grid. Mob Netw Appl 23(4):956\u2013966","journal-title":"Mob Netw Appl"},{"issue":"12","key":"1299_CR27","first-page":"332","volume":"2","author":"AH Rabie","year":"2015","unstructured":"Rabie AH, Saleh AI, Abo-Al-Ez KM (2015) A new strategy of load forecasting technique for smart grids. Int J Modern Trends Eng Res (IJMTER) 2(12):332\u2013341","journal-title":"Int J Modern Trends Eng Res (IJMTER)"},{"issue":"1","key":"1299_CR28","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1007\/s10586-018-2848-x","volume":"22","author":"AH Rabie","year":"2019","unstructured":"Rabie AH, Ali SH, Ali HA, Saleh AI (2019) A fog based load forecasting strategy for smart grids using big electrical data. Cluster Comput 22(1):241\u2013270","journal-title":"Cluster Comput"},{"issue":"1","key":"1299_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-017-0110-7","volume":"5","author":"S Rathee","year":"2018","unstructured":"Rathee S, Kashyap A (2018) Adaptive\u2013Miner: an efficient distributed association rule mining algorithm on Spark. J Big Data 5(1):1\u201317","journal-title":"J Big Data"},{"issue":"3","key":"1299_CR30","doi-asserted-by":"publisher","first-page":"633","DOI":"10.1016\/j.aei.2015.06.001","volume":"29","author":"N Sajadfara","year":"2015","unstructured":"Sajadfara N, Mab Y (2015) A hybrid cost estimation framework based on feature-oriented data mining approach. Adv Eng Inf 29(3):633\u2013647","journal-title":"Adv Eng Inf"},{"issue":"3","key":"1299_CR31","doi-asserted-by":"publisher","first-page":"422","DOI":"10.1016\/j.aei.2016.05.005","volume":"30","author":"AI Saleh","year":"2016","unstructured":"Saleh AI, Rabie AH, Abo-Al-Ez KM (2016) A data mining based load forecasting strategy for smart electrical grids. Adv Eng Inform 30(3):422\u2013448","journal-title":"Adv Eng Inform"},{"issue":"3","key":"1299_CR32","doi-asserted-by":"publisher","first-page":"1219","DOI":"10.1007\/s10614-018-9795-8","volume":"53","author":"A Torabi","year":"2019","unstructured":"Torabi A, Mousavy SAK, Dashti V, Saeedi M, Yousefi N (2019) A new prediction model based on cascade NN for wind power prediction. Comput Econ 53(3):1219\u20131243","journal-title":"Comput Econ"},{"issue":"2","key":"1299_CR33","first-page":"243","volume":"55","author":"Y Tu","year":"2018","unstructured":"Tu Y, Lin Y, Wang J, Kim JU (2018) Semi-supervised learning with generative adversarial networks on digital signal modulation classification. Comput Mater Continua 55(2):243\u2013254","journal-title":"Comput Mater Continua"},{"issue":"1","key":"1299_CR34","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1007\/s10846-018-0905-6","volume":"91","author":"KP Valavanis","year":"2018","unstructured":"Valavanis KP (2018) The entropy based approach to modeling and evaluating autonomy and intelligence of robotic systems. J Intell Rob Syst 91(1):7\u201322","journal-title":"J Intell Rob Syst"},{"issue":"2","key":"1299_CR35","first-page":"110","volume":"4","author":"S Vimala","year":"2018","unstructured":"Vimala S, Sharmili KC (2018) Prediction of loan risk using naive bayes and support vector machine. Int Conf Adv Comput Technol (ICACT) 4(2):110\u2013113","journal-title":"Int Conf Adv Comput Technol (ICACT)"},{"issue":"3","key":"1299_CR36","first-page":"508","volume":"5","author":"XX Wang","year":"2014","unstructured":"Wang XX, Ma LY (2014) A compact K nearest neighbor classification for power plant fault diagnosis. J Inf Hiding Multimedia Signal Proc 5(3):508\u2013517","journal-title":"J Inf Hiding Multimedia Signal Proc"},{"issue":"3","key":"1299_CR37","first-page":"527","volume":"35","author":"D Wang","year":"2015","unstructured":"Wang D, Sun Z (2015) Big data analysis and parallel load forecasting of electric power user Side. Proc Chin Soc Electr Eng (Proceed CSEE) 35(3):527\u2013537","journal-title":"Proc Chin Soc Electr Eng (Proceed CSEE)"},{"issue":"3","key":"1299_CR38","doi-asserted-by":"publisher","first-page":"1065","DOI":"10.1007\/s12652-017-0612-3","volume":"10","author":"L Wang","year":"2019","unstructured":"Wang L, Guo C, Li Y, Du B, Guo S (2019) An outsourcing service selection method using ANN and SFLA algorithms for cement equipment manufacturing enterprises in cloud manufacturing. J Ambient Intell Hum Comput 10(3):1065\u20131079","journal-title":"J Ambient Intell Hum Comput"},{"key":"1299_CR39","doi-asserted-by":"publisher","first-page":"598","DOI":"10.1016\/j.energy.2018.10.076","volume":"166","author":"J Wu","year":"2019","unstructured":"Wu J, Cui Z, Chen Y, Kong D, Wang YG (2019) A new hybrid model to predict the electrical load in five states of Australia. Energy 166:598\u2013609","journal-title":"Energy"},{"issue":"3","key":"1299_CR40","first-page":"541","volume":"55","author":"L Xiang","year":"2018","unstructured":"Xiang L, Li Y, Hao W, Yang P, Shen X (2018) Reversible natural language watermarking using synonym substitution and arithmetic coding. Comput Mater Continua 55(3):541\u2013559","journal-title":"Comput Mater Continua"},{"key":"1299_CR41","doi-asserted-by":"crossref","unstructured":"Xu M, Huang G, Zhang M, Cui P, Wang C (2018) Load forecasting research based on high performance intelligent data processing of power big data. In: Proceedings of the 2018 2nd international conference on algorithms, computing and systems (ICACS \u201818), Beijing, China, pp 55\u201360","DOI":"10.1145\/3242840.3242842"},{"issue":"2","key":"1299_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/electronics8020122","volume":"8","author":"M Zahid","year":"2019","unstructured":"Zahid M, Ahmed F, Javaid N, Abbasi R, Kazmi HZ, Javaid A, Bilal M, Akbar M, Ilahi M (2019) electricity price and load forecasting using enhanced convolutional neural network and enhanced support vector regression in smart grids. Electronics 8(2):1\u201332","journal-title":"Electronics"},{"issue":"1","key":"1299_CR43","first-page":"121","volume":"55","author":"D Zeng","year":"2018","unstructured":"Zeng D, Dai Y, Li F, Sherratt RS, Wang J (2018) Adversarial learning for distant supervised relation extraction. Comput Mater Continua 55(1):121\u2013136","journal-title":"Comput Mater Continua"},{"key":"1299_CR44","doi-asserted-by":"crossref","unstructured":"Zhang Y (2015) TOPSIS method based on entropy weight for supplier evaluation of power grid enterprise. In: Proceedings of the 2nd international conference on education reform and modern management, pp 334\u2013337","DOI":"10.2991\/ermm-15.2015.88"},{"issue":"3","key":"1299_CR45","doi-asserted-by":"publisher","first-page":"59","DOI":"10.17775\/CSEEJPES.2015.00036","volume":"1","author":"P Zhang","year":"2015","unstructured":"Zhang P, Wu X, Wang X, Bi S (2015) Short-term load forecasting based on big data technologies. CSEE J Power Energy Syst 1(3):59\u201367","journal-title":"CSEE J Power Energy Syst"},{"key":"1299_CR46","doi-asserted-by":"crossref","unstructured":"Zhang R, Xu Y, Dong ZY, Kong W, Wong KP (2016) A Composite k-nearest neighbor model for day-ahead load forecasting with limited temperature forecasts. In: Proceedings of the 2016 IEEE power and energy society general meeting (PESGM), Boston, MA, USA, pp 1\u20135","DOI":"10.1109\/PESGM.2016.7741097"},{"issue":"9","key":"1299_CR47","doi-asserted-by":"publisher","first-page":"2795","DOI":"10.1007\/s00521-016-2204-0","volume":"28","author":"L Zhang","year":"2017","unstructured":"Zhang L, Shan L, Wang J (2017) Optimal feature selection using distance-based discrete firefly algorithm with mutual information criterion. Neural Comput Appl 28(9):2795\u20132808","journal-title":"Neural Comput Appl"},{"key":"1299_CR48","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1007\/s11042-018-6562-8","volume":"25","author":"J Zhang","year":"2018","unstructured":"Zhang J, Jin X, Sun J, Wang J, Sangaiah AK (2018a) Spatial and semantic convolutional features for robust visual object tracking. Multimedia Tools Appl 25:26. \nhttps:\/\/doi.org\/10.1007\/s11042-018-6562-8","journal-title":"Multimedia Tools Appl"},{"issue":"5","key":"1299_CR49","doi-asserted-by":"publisher","first-page":"1774","DOI":"10.1109\/TNNLS.2017.2673241","volume":"29","author":"S Zhang","year":"2018","unstructured":"Zhang S, Li X, Zong M, Zhu X, Wang R (2018b) Efficient kNN classification with different numbers of nearest neighbors. IEEE Trans Neural Netw Learn Syst 29(5):1774\u20131784","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"1299_CR50","doi-asserted-by":"crossref","unstructured":"Zhao H, Tang Z, Shi W, Wang Z (2017) Study of short-term load forecasting in big data environment. In: Proceedings of the 2017 29th Chinese control and decision conference (CCDC), Chongqing, China, pp 6673\u20136678","DOI":"10.1109\/CCDC.2017.7978378"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-019-01299-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s12652-019-01299-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-019-01299-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,4,18]],"date-time":"2020-04-18T23:34:06Z","timestamp":1587252846000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s12652-019-01299-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,20]]},"references-count":50,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,1]]}},"alternative-id":["1299"],"URL":"https:\/\/doi.org\/10.1007\/s12652-019-01299-x","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"value":"1868-5137","type":"print"},{"value":"1868-5145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,20]]},"assertion":[{"value":"7 December 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 April 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 April 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}