{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,3]],"date-time":"2025-05-03T03:40:02Z","timestamp":1746243602670,"version":"3.40.4"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319077758"},{"type":"electronic","value":"9783319077765"}],"license":[{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014]]},"DOI":"10.1007\/978-3-319-07776-5_49","type":"book-chapter","created":{"date-parts":[[2014,5,26]],"date-time":"2014-05-26T14:36:47Z","timestamp":1401115007000},"page":"475-484","source":"Crossref","is-referenced-by-count":2,"title":["Solar Irradiance Estimation Using the Echo State Network and the Flexible Neural Tree"],"prefix":"10.1007","author":[{"given":"Sebasti\u00e1n","family":"Basterrech","sequence":"first","affiliation":[]},{"given":"Tom\u00e1\u0161","family":"Buri\u00e1nek","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"issue":"02","key":"49_CR1","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1142\/S0129065704001905","volume":"14","author":"Y. Chen","year":"2004","unstructured":"Chen, Y., Yang, B., Dong, J.: Nonlinear System Modelling Via Optimal Design of Neural Trees. International Journal of Neural Systems\u00a014(02), 125\u2013137 (2004)","journal-title":"International Journal of Neural Systems"},{"issue":"3-4","key":"49_CR2","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1016\/j.ins.2004.10.005","volume":"174","author":"Y. Chen","year":"2005","unstructured":"Chen, Y., Yang, B., Dong, J., Abraham, A.: Time-series Forecasting using Flexible Neural Tree Model. Inf. Sci.\u00a0174(3-4), 219\u2013235 (2005)","journal-title":"Inf. Sci."},{"key":"49_CR3","unstructured":"Jaeger, H.: The \u201cecho state\u201d approach to analysing and training recurrent neural networks. Technical Report 148, German National Research Center for Information Technology (2001)"},{"issue":"4","key":"49_CR4","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1002\/int.20203","volume":"22","author":"Y. Chen","year":"2007","unstructured":"Chen, Y., Abraham, A., Yang, B.: Hybrid Flexible Neural Tree based intrusion detection systems. International Journal of Intelligent Systems\u00a022(4), 337\u2013352 (2007)","journal-title":"International Journal of Intelligent Systems"},{"issue":"1-3","key":"49_CR5","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1016\/j.neucom.2006.01.022","volume":"70","author":"Y. Chen","year":"2006","unstructured":"Chen, Y., Abraham, A., Yang, B.: Feature selection and classification using Flexible Neural Tree. Neurocomputing\u00a070(1-3), 305\u2013313 (2006)","journal-title":"Neurocomputing"},{"key":"49_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1007\/11427469_71","volume-title":"Advances in Neural Networks \u2013 ISNN 2005","author":"Y. Chen","year":"2005","unstructured":"Chen, Y., Abraham, A., Yang, J.: Feature selection and intrusion detection using hybrid flexible neural tree. In: Wang, J., Liao, X.-F., Yi, Z. (eds.) ISNN 2005. LNCS, vol.\u00a03498, pp. 439\u2013444. Springer, Heidelberg (2005)"},{"issue":"4","key":"49_CR7","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1002\/int.20203","volume":"22","author":"Y. Chen","year":"2007","unstructured":"Chen, Y., Abraham, A., Yang, B.: Hybrid flexible neural-tree-based intrusion detection systems. International Journal of Intelligent Systems\u00a022(4), 337\u2013352 (2007)","journal-title":"International Journal of Intelligent Systems"},{"key":"49_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/978-3-540-28647-9_36","volume-title":"Advances in Neural Networks \u2013 ISNN 2004","author":"Y. Chen","year":"2004","unstructured":"Chen, Y., Yang, B., Dong, J.: Evolving Flexible Neural Networks Using ANT Programming and PSO Algorithm. In: Yin, F.-L., Wang, J., Guo, C. (eds.) ISNN 2004. LNCS, vol.\u00a03173, pp. 211\u2013216. Springer, Heidelberg (2004)"},{"key":"49_CR9","doi-asserted-by":"crossref","unstructured":"Kennedy, J., Eberhart, R.: Particle Swarm Optimization. In: Proceedings of the IEEE International Conference on Neural Networks 1995, vol.\u00a04, pp. 1942\u20131948 (1995)","DOI":"10.1109\/ICNN.1995.488968"},{"key":"49_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1007\/BFb0040810","volume-title":"Evolutionary Programming VII","author":"Y. Shi","year":"1998","unstructured":"Shi, Y., Eberhart, R.C.: Parameter Selection in Particle Swarm Optimization. In: Porto, V.W., Waagen, D. (eds.) EP 1998. LNCS, vol.\u00a01447, pp. 591\u2013600. Springer, Heidelberg (1998)"},{"issue":"4","key":"49_CR11","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R. Storn","year":"1997","unstructured":"Storn, R., Price, K.: Differential Evolution \u2013 A Simple and Efficient Heuristic for global Optimization over Continuous Spaces. Journal of Global Optimization\u00a011(4), 341\u2013359 (1997)","journal-title":"Journal of Global Optimization"},{"key":"49_CR12","series-title":"Natural Computing Series","volume-title":"Differential Evolution: A Practical Approach to Global Optimization","author":"K. Price","year":"2005","unstructured":"Price, K., Storn, R.M., Lampinen, J.A.: Differential Evolution: A Practical Approach to Global Optimization. Natural Computing Series. Springer-Verlag New York, Inc., Secaucus (2005)"},{"key":"49_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"518","DOI":"10.1007\/11760191_76","volume-title":"Advances in Neural Networks - ISNN 2006","author":"Y. Chen","year":"2006","unstructured":"Chen, Y., Peng, L., Abraham, A.: Exchange rate forecasting using flexible neural trees. In: Wang, J., Yi, Z., \u017burada, J.M., Lu, B.-L., Yin, H. (eds.) ISNN 2006. LNCS, vol.\u00a03973, pp. 518\u2013523. Springer, Heidelberg (2006)"},{"key":"49_CR14","unstructured":"Shi, Y., Eberhart, R.: A modified Particle Swarm Optimizer. In: The 1998 IEEE International Conference on Evolutionary Computation Proceedings, IEEE World Congress on Computational Intelligence, pp. 69\u201373 (1998)"},{"key":"49_CR15","doi-asserted-by":"crossref","unstructured":"Maass, W., Natschl\u00e4ger, T., Markram, H.: Real-time computing without stable states: a new framework for a neural computation based on perturbations. Neural Computation, 2531\u20132560 (November 2002)","DOI":"10.1162\/089976602760407955"},{"key":"49_CR16","doi-asserted-by":"crossref","unstructured":"Luko\u0161evi\u010dius, M., Jaeger, H.: Reservoir computing approaches to recurrent neural network training. Computer Science Review, 127\u2013149 (2009)","DOI":"10.1016\/j.cosrev.2009.03.005"},{"key":"49_CR17","doi-asserted-by":"publisher","first-page":"1159","DOI":"10.1016\/j.neucom.2007.12.020","volume":"71","author":"B. Schrauwen","year":"2007","unstructured":"Schrauwen, B., Wardermann, M., Verstraeten, D., Steil, J.J., Stroobandt, D.: Improving Reservoirs using Intrinsic Plasticity. Neurocomputing\u00a071, 1159\u20131171 (2007)","journal-title":"Neurocomputing"},{"key":"49_CR18","unstructured":"Steil, J.J.: Backpropagation-Decorrelation: online recurrent learning with O(N) complexity. In: Proceedings of IJCNN 2004, vol.\u00a01 (2004)"},{"key":"49_CR19","doi-asserted-by":"crossref","unstructured":"Xue, Y., Yang, L., Haykin, S.: Decoupled Echo State Networks with lateral inhibition. Neural Networks\u00a0(3), 365\u2013376 (2007)","DOI":"10.1016\/j.neunet.2007.04.014"},{"key":"49_CR20","doi-asserted-by":"crossref","unstructured":"Jaeger, H., Luko\u0161evi\u010dius, M., Popovici, D., Siewert, U.: Optimization and applications of Echo State Networks with leaky-integrator neurons. Neural Networks\u00a0(3), 335\u2013352 (2007)","DOI":"10.1016\/j.neunet.2007.04.016"},{"key":"49_CR21","first-page":"757","volume":"19","author":"M. Gagliolo","year":"2007","unstructured":"Gagliolo, M., Schmidhuber, J., Wierstra, D., Gomez, F.: Training Recurrent Networks by Evolino. Neural Networks\u00a019, 757\u2013779 (2007)","journal-title":"Neural Networks"},{"key":"49_CR22","doi-asserted-by":"crossref","unstructured":"Basterrech, S., Rubino, G.: Echo State Queueing Network: a new Reservoir Computing learning tool. In: IEEE Consumer Comunications & Networking Conference (CCNC 2013) (January 2013)","DOI":"10.1109\/CCNC.2013.6488435"},{"key":"49_CR23","doi-asserted-by":"crossref","unstructured":"Verstraeten, D., Schrauwen, B., D\u2019Haene, M., Stroobandt, D.: An experimental unification of reservoir computing methods. Neural Networks\u00a0(3), 287\u2013289 (2007)","DOI":"10.1016\/j.neunet.2007.04.003"},{"key":"49_CR24","unstructured":"Maass, W., Natschl\u00e4ger, T., Markram, H.: Computational models for generic cortical microcircuits. In: Neuroscience Databases. A Practical Guide, Boston, Usa, pp. 121\u2013136. Kluwer Academic Publishers (June 2003)"},{"key":"49_CR25","doi-asserted-by":"crossref","unstructured":"Basterrech, S., Sn\u00e1\u0161el, V.: Initializing Reservoirs With Exhibitory And Inhibitory Signals Using Unsupervised Learning Techniques. In: International Symposium on Information and Communication Technology (SoICT), Danang, Viet Nam. ACM Digital Library (December 2013)","DOI":"10.1145\/2542050.2542087"},{"key":"49_CR26","doi-asserted-by":"crossref","unstructured":"Basterrech, S., Fyfe, C., Rubino, G.: Self-Organizing Maps and Scale-Invariant Maps in Echo State Networks. In: 2011 11th International Conference on IEEE Intelligent Systems Design and Applications (ISDA), pp. 94\u201399 (November 2011)","DOI":"10.1109\/ISDA.2011.6121637"},{"key":"49_CR27","doi-asserted-by":"crossref","unstructured":"Rodan, A., Ti\u0148o, P.: Minimum Complexity Echo State Network. IEEE Transactions on Neural Networks, 131\u2013144 (2011)","DOI":"10.1109\/TNN.2010.2089641"},{"key":"49_CR28","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1007\/978-3-642-35289-8_36","volume-title":"Neural Networks: Tricks of the Trade","author":"M. Luko\u0161evi\u010dius","year":"2012","unstructured":"Luko\u0161evi\u010dius, M.: A practical guide to applying echo state networks. In: Montavon, G., Orr, G.B., M\u00fcller, K.-R. (eds.) Neural Networks: Tricks of the Trade, 2nd edn. LNCS, vol.\u00a07700, pp. 659\u2013686. Springer, Heidelberg (2012)"},{"issue":"4","key":"49_CR29","doi-asserted-by":"crossref","first-page":"321","DOI":"10.14311\/NNW.2013.23.020","volume":"23","author":"L. Prokop","year":"2013","unstructured":"Prokop, L., Misak, S., Snasel, V., Platos, J., Kroemer, P.: Supervised learning of photovoltaic power plant output prediction models. Neural Networks World\u00a023(4), 321\u2013338 (2013)","journal-title":"Neural Networks World"},{"key":"49_CR30","doi-asserted-by":"crossref","unstructured":"Basterrech, S., Prokop, L., Buri\u00e1nek, T., Misak, S.: Optimal Design of Neural Tree for Solar Power Prediction. In: 15th Scientific Conference Electronic Power Engeneering, Brno, Czech Republic (May 2014)","DOI":"10.1109\/EPE.2014.6839522"},{"key":"49_CR31","doi-asserted-by":"crossref","unstructured":"Eberhart, R.C., Shi, Y.: Comparing inertia weights and constriction factors in particle swarm optimization. In: Proceedings of the 2000 Congress on Evolutionary Computation 2000, vol.\u00a01, pp. 84\u201388 (2000)","DOI":"10.1109\/CEC.2000.870279"},{"key":"49_CR32","doi-asserted-by":"crossref","unstructured":"Clerc, M.: The swarm and the queen: towards a deterministic and adaptive particle swarm optimization. In: Proceedings of the 1999 Congress on Evolutionary Computation, CEC 1999, vol.\u00a03, pp. 1951\u20131957 (1999)","DOI":"10.1109\/CEC.1999.785513"}],"container-title":["Advances in Intelligent Systems and Computing","Intelligent Data analysis and its Applications, Volume I"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-07776-5_49","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,3]],"date-time":"2025-05-03T03:22:21Z","timestamp":1746242541000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-07776-5_49"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"ISBN":["9783319077758","9783319077765"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-07776-5_49","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2014]]}}}