{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T06:49:17Z","timestamp":1768978157976,"version":"3.49.0"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2019,5,13]],"date-time":"2019-05-13T00:00:00Z","timestamp":1557705600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,5,13]],"date-time":"2019-05-13T00:00:00Z","timestamp":1557705600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2020,6]]},"DOI":"10.1007\/s10586-019-02942-0","type":"journal-article","created":{"date-parts":[[2019,5,14]],"date-time":"2019-05-14T01:50:48Z","timestamp":1557798648000},"page":"509-535","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["A new outlier rejection methodology for supporting load forecasting in smart grids based on big data"],"prefix":"10.1007","volume":"23","author":[{"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":[[2019,5,13]]},"reference":[{"issue":"12","key":"2942_CR1","first-page":"332","volume":"2","author":"AS Rabie","year":"2015","unstructured":"Rabie, A.S., Abo-Al-Ez, K.: A new strategy of load forecasting technique for smart grids. Int. J. Modern Trends Eng. Res. (IJMTER) 2(12), 332\u2013341 (2015)","journal-title":"Int. J. Modern Trends Eng. Res. (IJMTER)"},{"issue":"3","key":"2942_CR2","doi-asserted-by":"publisher","first-page":"422","DOI":"10.1016\/j.aei.2016.05.005","volume":"30","author":"AR Saleh","year":"2016","unstructured":"Saleh, A.R., Abo-Al-Ezb, K.: A data mining based load forecasting strategy for smart electrical grids. Adv. Eng. Inform. 30(3), 422\u2013448 (2016)","journal-title":"Adv. Eng. Inform."},{"issue":"4","key":"2942_CR3","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, O.: Energy harvesting cognitive radio networking for iot-enabled smart grid. Mob. Netw. Appl. 23(4), 956\u2013966 (2018)","journal-title":"Mob. Netw. Appl."},{"issue":"7","key":"2942_CR4","first-page":"1362","volume":"3","author":"V Mahajan","year":"2016","unstructured":"Mahajan, V., Patil, P.: Internet of things based residential power load forecasting. Int. Res. J. Eng. Technol. (IRJET) 3(7), 1362\u20131364 (2016)","journal-title":"Int. Res. J. Eng. Technol. (IRJET)"},{"issue":"10","key":"2942_CR5","first-page":"1","volume":"2","author":"H Atlam","year":"2018","unstructured":"Atlam, H., Walters, R., Wills, G.: Fog computing and the internet of things: a review. Big Data Cognit. Comput. 2(10), 1\u201318 (2018)","journal-title":"Big Data Cognit. Comput."},{"key":"2942_CR6","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.: The internet of energy: smart sensor networks and big data management for smart grid. Procedia Comput. Sci. 56, 592\u2013597 (2015)","journal-title":"Procedia Comput. Sci."},{"key":"2942_CR7","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-019-02910-8","author":"Z Ghanbari","year":"2019","unstructured":"Ghanbari, Z., Navimipour, N., Hosseinzadeh, M., Darwesh, A.: Resource allocation mechanisms and approaches on the internet of things. Comput Clust (2019). \n                  https:\/\/doi.org\/10.1007\/s10586-019-02910-8","journal-title":"Comput Clust"},{"key":"2942_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-019-02921-5","author":"SC Yang","year":"2019","unstructured":"Yang, S.C., Liu, J., Liu, R., Chang, C.: On construction of an energy monitoring service using big data technology for the smart campus. Comput Clust (2019). \n                  https:\/\/doi.org\/10.1007\/s10586-019-02921-5","journal-title":"Comput Clust"},{"issue":"1","key":"2942_CR9","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1007\/s10586-018-2848-x","volume":"22","author":"SA Rabie","year":"2019","unstructured":"Rabie, S.A., Ali, H., Saleh, A.: A fog based load forecasting strategy for smart grids using big electrical data. Clust. Comput. 22(1), 241\u2013270 (2019)","journal-title":"Clust. Comput."},{"key":"2942_CR10","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-018-2337-2","author":"PS Madhusudhanan","year":"2018","unstructured":"Madhusudhanan, P.S., Karpagam, N., Mahesh, A., Suhi, P.: An hybrid metaheuristic approach for efficient feature selection. Comput Clust (2018). \n                  https:\/\/doi.org\/10.1007\/s10586-018-2337-2","journal-title":"Comput Clust"},{"key":"2942_CR11","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-018-2550-z","author":"R Manoj","year":"2018","unstructured":"Manoj, R., Praveena, M., Vijayakumar, K.: An ACO\u2013ANN based feature selection algorithm for big data. Clust. Comput. (2018). \n                  https:\/\/doi.org\/10.1007\/s10586-018-2550-z","journal-title":"Clust. Comput."},{"issue":"12","key":"2942_CR12","doi-asserted-by":"publisher","first-page":"2696","DOI":"10.1109\/TKDE.2017.2744619","volume":"29","author":"J Mao","year":"2017","unstructured":"Mao, J., Wang, T., Jin, C., Zhou, A.: Feature grouping-based outlier detection upon streaming trajectories. IEEE Trans. Knowl. Data Eng. 29(12), 2696\u20132709 (2017)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"6","key":"2942_CR13","doi-asserted-by":"publisher","first-page":"1580","DOI":"10.1109\/TSP.2016.2645515","volume":"65","author":"M Rahmani","year":"2017","unstructured":"Rahmani, M., Atia, G.: Randomized robust subspace recovery and outlier detection for high dimensional data matrices. IEEE Trans. Signal Process. 65(6), 1580\u20131594 (2017)","journal-title":"IEEE Trans. Signal Process."},{"issue":"13","key":"2942_CR14","first-page":"1","volume":"8","author":"RV Vasconcelos","year":"2017","unstructured":"Vasconcelos, R.V., Olivieri, B., Roriz, M., Endler, M., Junior, M.: Smartphone-based outlier detection: a complex event processing approach for driving behavior detection. J. Internet Serv. Appl. 8(13), 1\u201330 (2017)","journal-title":"J. Internet Serv. Appl."},{"key":"2942_CR15","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-018-1799-6","author":"G Venkatesh","year":"2018","unstructured":"Venkatesh, G., Arunesh, K.: Map Reduce for big data processing based on traffic aware partition and aggregation. Clust. Comput. (2018). \n                  https:\/\/doi.org\/10.1007\/s10586-018-1799-6","journal-title":"Clust. Comput."},{"key":"2942_CR16","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-017-1553-5","author":"M VeeraManickam","year":"2018","unstructured":"VeeraManickam, M., Mohanapriya, M., Pandey, B., Akhade, S., Kale, S., Patil, R., Vigneshwar, M.: Map-Reduce framework based cluster architecture for academic student\u2019s performance prediction using cumulative dragonfly based neural network. Clust. Comput. (2018). \n                  https:\/\/doi.org\/10.1007\/s10586-017-1553-5","journal-title":"Clust. Comput."},{"key":"2942_CR17","doi-asserted-by":"crossref","unstructured":"Tellis V, Souza D (2018) Detecting Anomalies in Data Stream Using Efficient Techniques: A Review. In: Proceedings of the 2018 International Conference on Control, Power, Communication and Computing Technologies (ICCPCCT), Kannur, India, pp. 296\u2013298","DOI":"10.1109\/ICCPCCT.2018.8574310"},{"key":"2942_CR18","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-018-2674-1","author":"CH Park","year":"2018","unstructured":"Park, C.H.: Outlier and anomaly pattern detection on data streams. J. Supercomput. (2018). \n                  https:\/\/doi.org\/10.1007\/s11227-018-2674-1","journal-title":"J. Supercomput."},{"issue":"23","key":"2942_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1002\/cpe.4466","volume":"30","author":"Z Shou","year":"2018","unstructured":"Shou, Z., Li, S.: Large dataset summarization with automatic parameter optimization and parallel processing for local outlier detection. Concurr. Comput. Pract. Exp. 30(23), 1\u201313 (2018)","journal-title":"Concurr. Comput. Pract. Exp."},{"key":"2942_CR20","doi-asserted-by":"crossref","unstructured":"Chomatek L, Duraj A (2019) Efficient Genetic Algorithm for Breast Cancer Diagnosis. In: Proceedings of the International Conference on Information Technologies in Biomedicine, ITIB 2018: Advances in Intelligent Systems and Computing, Springer, Cham, vol. 762, pp. 64\u201376","DOI":"10.1007\/978-3-319-91211-0_6"},{"key":"2942_CR21","doi-asserted-by":"publisher","DOI":"10.1002\/dac.3918","author":"B Saneja","year":"2019","unstructured":"Saneja, B., Rani, R.: A scalable correlation-based approach for outlier detection in wireless body sensor networks. Int. J. Commun Syst (2019). \n                  https:\/\/doi.org\/10.1002\/dac.3918","journal-title":"Int. J. Commun Syst"},{"key":"2942_CR22","doi-asserted-by":"crossref","unstructured":"Yan Y, Cao L, Rundensteiner E (2017) Distributed Top-N Local Outlier Detection in Big Data. In: Proceedings of the 2017 IEEE International Conference on Big Data (Big Data), Boston, MA, USA, pp. 827\u2013836","DOI":"10.1109\/BigData.2017.8257998"},{"issue":"1","key":"2942_CR23","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1111\/jbi.13122","volume":"45","author":"MW Liu","year":"2018","unstructured":"Liu, M.W., Newell, G.: Detecting outliers in species distribution data. J. Biogeogr. 45(1), 164\u2013176 (2018)","journal-title":"J. Biogeogr."},{"key":"2942_CR24","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/9702304","author":"X Liu","year":"2018","unstructured":"Liu, X., Zhou, Y., Chen, X.: Mining outlier data in mobile internet-based large real-time databases. Complex. Hindawi (2018). \n                  https:\/\/doi.org\/10.1155\/2018\/9702304","journal-title":"Complex. Hindawi"},{"key":"2942_CR25","doi-asserted-by":"crossref","unstructured":"Okay F, 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\u20136","DOI":"10.1109\/ISNCC.2016.7746062"},{"key":"2942_CR26","doi-asserted-by":"publisher","first-page":"6900","DOI":"10.1109\/ACCESS.2017.2778504","volume":"6","author":"W Yu","year":"2018","unstructured":"Yu, W., Liang, F., He, X., Hatcher, W., Lu, C., Lin, J., Yang, X.: A survey on the edge computing for the internet of things. IEEE Access IEEE 6, 6900\u20136919 (2018)","journal-title":"IEEE Access IEEE"},{"key":"2942_CR27","doi-asserted-by":"publisher","DOI":"10.1142\/S1793524519500396","author":"S Aiyad","year":"2019","unstructured":"Aiyad, S., Saleh, A., Labib, L.: A new distributed feature selection technique for classifying gene expression data. Int. J. Biomath. (2019). \n                  https:\/\/doi.org\/10.1142\/S1793524519500396","journal-title":"Int. J. Biomath."},{"issue":"2","key":"2942_CR28","doi-asserted-by":"publisher","first-page":"1958","DOI":"10.3182\/20080706-5-KR-1001.00333","volume":"41","author":"KL Posio","year":"2008","unstructured":"Posio, K.L., Ruuska, J., Ruha, P.: Outlier detection for 2D temperature data. IFAC Proc. 41(2), 1958\u20131963 (2008)","journal-title":"IFAC Proc."},{"issue":"6","key":"2942_CR29","first-page":"30","volume":"38","author":"P Raja","year":"2012","unstructured":"Raja, P., Bhaskara, V.: An effective genetic algorithm for outlier detection. Int. J. Comput. Appl. 38(6), 30\u201333 (2012)","journal-title":"Int. J. Comput. Appl."},{"issue":"2","key":"2942_CR30","first-page":"833","volume":"7","author":"M Afzal","year":"2016","unstructured":"Afzal, M., Ashraf, S.: Genetic algorithm for outlier detection. Int. J. Comput. Sci. Inf. Technol. (IJCSIT) 7(2), 833\u2013835 (2016)","journal-title":"Int. J. Comput. Sci. Inf. Technol. (IJCSIT)"},{"issue":"2","key":"2942_CR31","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1109\/SURV.2010.021510.00088","volume":"12","author":"Y Zhang","year":"2010","unstructured":"Zhang, Y., Meratnia, N., Havinga, P.: Outlier detection techniques for wireless sensor networks: a survey. IEEE Commun. Surv. Tutor. 12(2), 159\u2013170 (2010)","journal-title":"IEEE Commun. Surv. Tutor."},{"issue":"11","key":"2942_CR32","doi-asserted-by":"publisher","first-page":"1945","DOI":"10.1002\/sec.909","volume":"7","author":"N Yu","year":"2014","unstructured":"Yu, N., Zhang, L., Ren, Y.: A novel D-S based secure localization algorithm for wireless sensor networks. Sec. Commun. Netw. 7(11), 1945\u20131954 (2014)","journal-title":"Sec. Commun. Netw."},{"issue":"5","key":"2942_CR33","first-page":"3530","volume":"4","author":"L Revathi","year":"2015","unstructured":"Revathi, L., Appandiraj, A.: Hadoop based parallel framework for feature subset selection in big data. Int. J. Innov. Res. Sci. Eng. Technol. 4(5), 3530\u20133534 (2015)","journal-title":"Int. J. Innov. Res. Sci. Eng. Technol."},{"issue":"3","key":"2942_CR34","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.: Prediction of slope stability using naive Bayes classifier. KSCE J. Civil Eng. 22(3), 941\u2013950 (2018)","journal-title":"KSCE J. Civil Eng."},{"key":"2942_CR35","unstructured":"European Network on Intelligent Technologies for Smart Adaptive Systems. Available at: \n                  http:\/\/www.eunite.org\/\n                  \n                . The competition page is: \n                  http:\/\/neuron.tuke.sk\/competition\/"},{"issue":"3","key":"2942_CR36","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.: Short-term load forecasting based on big data technologies. CSEE J. Power Energy Syst. 1(3), 59\u201367 (2015)","journal-title":"CSEE J. Power Energy Syst."}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-019-02942-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10586-019-02942-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-019-02942-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,7,19]],"date-time":"2020-07-19T05:33:47Z","timestamp":1595136827000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10586-019-02942-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,13]]},"references-count":36,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,6]]}},"alternative-id":["2942"],"URL":"https:\/\/doi.org\/10.1007\/s10586-019-02942-0","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5,13]]},"assertion":[{"value":"21 September 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 March 2019","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 May 2019","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 May 2019","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}