{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,21]],"date-time":"2022-04-21T14:55:28Z","timestamp":1650552928294},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2007,5,5]],"date-time":"2007-05-05T00:00:00Z","timestamp":1178323200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2008,6]]},"DOI":"10.1007\/s00521-007-0116-8","type":"journal-article","created":{"date-parts":[[2007,5,4]],"date-time":"2007-05-04T13:02:42Z","timestamp":1178283762000},"page":"245-254","source":"Crossref","is-referenced-by-count":10,"title":["A hybrid approach for training recurrent neural networks: application to multi-step-ahead prediction of noisy and large data sets"],"prefix":"10.1007","volume":"17","author":[{"given":"S.","family":"Chtourou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M.","family":"Chtourou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"O.","family":"Hammami","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2007,5,5]]},"reference":[{"issue":"2","key":"116_CR1","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1109\/72.279183","volume":"5","author":"O Nerrand","year":"1994","unstructured":"Nerrand O, P.Roussel-Ragot, Urbani D, L.Personnaz, Dreyfus G (1994) Training recurrent neural networks: why and how? an illustration in dynamical process modeling. IEEE Trans Neural Netw 5(2):178\u2013184","journal-title":"IEEE Trans Neural Netw"},{"key":"116_CR2","doi-asserted-by":"crossref","unstructured":"Inoue H, Narihisa H (2000) Predicting chaotic time series by ensembles self-generating neural networks. International joint conference on neural network (IJCNN\u201900), p 2231","DOI":"10.1109\/IJCNN.2000.857902"},{"issue":"2","key":"116_CR3","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1109\/72.279188","volume":"5","author":"T Connor","year":"1994","unstructured":"Connor T, Douglas R (1994) Reccurent neural networks and robust time series prediction. IEEE Trans Neural Netw 5(2):240\u2013254","journal-title":"IEEE Trans Neural Netw"},{"issue":"2","key":"116_CR4","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1145\/990301.990304","volume":"4","author":"M Deshpande","year":"2004","unstructured":"Deshpande M, Karipys G (2004) Selective Markov models for predicting web pages accesses. ACM Trans Internet Technol 4(2):163\u2013184","journal-title":"ACM Trans Internet Technol"},{"key":"116_CR5","doi-asserted-by":"crossref","unstructured":"Tran N, Reed A (2001) ARIMA time series modeling and forecasting for adaptive I\/O prefetching. In: Proceedings of the international conference on supercomputing, pp 473\u2013485","DOI":"10.1145\/377792.377905"},{"key":"116_CR6","doi-asserted-by":"crossref","unstructured":"Ho SL, Xie M, Goh TN (2002) A comparative study of neural network and Box\u2013Jenkins ARIMA modeling in time series prediction. In: Proceedings of the 26th international conference on computers and industrial engineering 42(2\u20134):371\u2013375","DOI":"10.1016\/S0360-8352(02)00036-0"},{"key":"116_CR7","doi-asserted-by":"crossref","unstructured":"Owens AJ (2000) Empirical modeling of very large data sets using neural network. In: Proceedings of the IEEE-INNS-ENNS international joint conference on neural network, vol 6, pp 302\u2013307","DOI":"10.1109\/IJCNN.2000.859413"},{"key":"116_CR8","doi-asserted-by":"crossref","unstructured":"Principe JC, Wang L, Motter MA (1998) Local dynamic modelling with self-organizing maps and applications to nonlinear system identification and control. Proc IEEE 86(11)","DOI":"10.1109\/5.726789"},{"key":"116_CR9","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/0165-0114(95)00322-3","volume":"83","author":"K Cho","year":"1996","unstructured":"Cho K, Wang B (1996) Radial basis function based adaptive fuzzy systems and their application to system identification and prediction. Fuzzy Sets Syst 83:325\u2013339","journal-title":"Fuzzy Sets Syst"},{"issue":"2","key":"116_CR10","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1023\/A:1018741720065","volume":"10","author":"T Kohonen","year":"1999","unstructured":"Kohonen T (1999) Self-organizing maps and learning vector quantization for feature sequences. Neural Processing Lett 10(2):151\u2013159","journal-title":"Neural Processing Lett"},{"issue":"5","key":"116_CR11","doi-asserted-by":"crossref","first-page":"1163","DOI":"10.1109\/72.950144","volume":"12","author":"H Leung","year":"2001","unstructured":"Leung H, Lo T, Wang S (2001) Prediction of noisy chaotic time series using an optimal radial basis function neural network. IEEE Trans Neural Netw 12(5):1163\u20131172","journal-title":"IEEE Trans Neural Netw"},{"issue":"6","key":"116_CR12","doi-asserted-by":"crossref","first-page":"1329","DOI":"10.1109\/72.548162","volume":"7","author":"T Lin","year":"1996","unstructured":"Lin T, Horn G, Tino P, Lee Giles C (1996) Learning long-term dependencies in NARX recurrent neural networks. IEEE Trans Neural Netw 7(6):1329","journal-title":"IEEE Trans Neural Netw"},{"issue":"11","key":"116_CR13","doi-asserted-by":"crossref","first-page":"2719","DOI":"10.1109\/78.650098","volume":"45","author":"T Lin","year":"1997","unstructured":"Lin T, Giles CL, Horne B, Kung SY (1997) A delay damage model selection algorithm for NARX neural networks. IEEE Trans Signal Process 45(11):2719\u20132730","journal-title":"IEEE Trans Signal Process"},{"issue":"7","key":"116_CR14","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1016\/S0893-6080(00)00048-4","volume":"13","author":"AG Parlos","year":"2000","unstructured":"Parlos AG, Rais OT, Atiya AF (2000) Multi-step-ahead prediction using dynamic recurrent neural networks. Neural Netw 13(7):765\u2013786","journal-title":"Neural Netw"},{"issue":"1\/2","key":"116_CR15","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1023\/A:1010884214864","volume":"44","author":"C Lee Giles","year":"2001","unstructured":"Lee Giles C, Steve Lawrence, Tsoi AC (2001) Noisy time series prediction using a recurrent neural network and grammatical inference. Mach Learning 44(1\/2):161\u2013183","journal-title":"Mach Learning"},{"key":"116_CR16","doi-asserted-by":"crossref","unstructured":"Motter AM (2000) Predictive multiple model switching control with the self-organizing map. In: Proceedings of international joint conference in neural network, 4(4):IEEE-INNS-ENNS, 4317","DOI":"10.1109\/IJCNN.2000.860791"},{"key":"116_CR17","doi-asserted-by":"crossref","unstructured":"Wichard JD, Ogorzalek M (2004) Time series prediction with ensemble models. In: Proceedings of international joint conference in neural network, Busdapest","DOI":"10.1109\/IJCNN.2004.1380203"},{"key":"116_CR18","unstructured":"Chtourou S, Chtourou M, Hammami O (2006) Neural network based memory access prediction support for soc dynamic reconfiguration. In: Proceedings of the international joint conference on neural network, pp 5130\u20135136"},{"key":"116_CR19","doi-asserted-by":"crossref","unstructured":"Sherwood T, Sair S, Calder B (2003) Phase tracking and prediction. In: Proceedings of the 30th international symposium on computer architecture (ISCA), pp 336\u2013347","DOI":"10.1145\/871656.859657"},{"issue":"4","key":"116_CR20","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1145\/571637.571639","volume":"20","author":"DA Jimenez","year":"2002","unstructured":"Jimenez DA, Lin C (2002) Neural methods for dynamic branch prediction. ACM Trans Comput Syst 20(4):369\u2013397","journal-title":"ACM Trans Comput Syst"},{"key":"116_CR21","doi-asserted-by":"crossref","unstructured":"Sakr MF, Giles CL, Levitan SP, Horne BG, Maggini M, Chiarulli DM (1996) On-line prediction of multiprocessor memory access patterns. In: Proceedings of the IEEE international conference on neural networks, p 1564","DOI":"10.1109\/ICNN.1996.549133"},{"key":"116_CR22","unstructured":"Sakr MF, Levitan SP, Chiarulli DM, Horne BG, Giles CL (1997) Predicting multiprocessor memory access patterns with learning models. In: Fisher D (ed) Proceedings of the fourteenth international conference on machine learning. Morgan Kaufmann, San Francisco, pp 305\u2013312"},{"issue":"3","key":"116_CR23","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1109\/72.846741","volume":"11","author":"FA Atiya","year":"2000","unstructured":"Atiya FA, Parlos AG (2000) New results on recurrent network training: unifying the algorithms and accelerating convergence. IEEE Trans Neural Netw 11(3):697\u2013709","journal-title":"IEEE Trans Neural Netw"},{"key":"116_CR24","doi-asserted-by":"crossref","first-page":"955","DOI":"10.1016\/S0893-6080(03)00054-6","volume":"16","author":"SK Chalup","year":"2003","unstructured":"Chalup SK, Blair AD (2003) Incremental training of first order recurrent neural networks to predict a context-sensitive language. Neural Netw 16:955\u2013972","journal-title":"Neural Netw"},{"issue":"12","key":"116_CR25","doi-asserted-by":"crossref","first-page":"1876","DOI":"10.1109\/TCSI.2002.805733","volume":"49","author":"D Liu","year":"2002","unstructured":"Liu D, Chang T-S, Zhang Y (2002) A constructive algorithm for feedforward neural networks with incremental training. IEEE Trans Circuits Syst I Fundamental Theory Appl 49(12):1876\u20131879","journal-title":"IEEE Trans Circuits Syst I Fundamental Theory Appl"},{"key":"116_CR26","doi-asserted-by":"crossref","unstructured":"Dittenbach M, Merkl D, Rauber A (2000) The growing hierarchical self organizing map. In: Proceedings of the international joint conference on neural networks, pp 15\u201319","DOI":"10.1109\/IJCNN.2000.859366"},{"key":"116_CR27","unstructured":"Hammond J, MacClean D, Valova I (2006) A parallel implementation of a growing SOM promoting independent neural networks over distributed input space. In: Proceedings of the international joint conference on neural networks, pp 958\u2013965"},{"key":"116_CR28","unstructured":"http:\/\/rogue.colorado.edu\/Pin\/index.html"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-007-0116-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-007-0116-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-007-0116-8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,29]],"date-time":"2019-05-29T02:06:56Z","timestamp":1559095616000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-007-0116-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2007,5,5]]},"references-count":28,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2008,6]]}},"alternative-id":["116"],"URL":"https:\/\/doi.org\/10.1007\/s00521-007-0116-8","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2007,5,5]]}}}