{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T03:35:24Z","timestamp":1743132924821,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":23,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819770007"},{"type":"electronic","value":"9789819770014"}],"license":[{"start":{"date-parts":[[2024,9,22]],"date-time":"2024-09-22T00:00:00Z","timestamp":1726963200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,9,22]],"date-time":"2024-09-22T00:00:00Z","timestamp":1726963200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-97-7001-4_17","type":"book-chapter","created":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T18:01:43Z","timestamp":1726941703000},"page":"234-245","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Fast and Accurate Reconstruction Method for Boiler Temperature Field Based on Inverse Distance Weight and Long Short-Term Memory"],"prefix":"10.1007","author":[{"given":"Rizhong","family":"Huang","sequence":"first","affiliation":[]},{"given":"Menghua","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yichen","family":"Li","sequence":"additional","affiliation":[]},{"given":"Ke","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Weijie","family":"Huang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,9,22]]},"reference":[{"key":"17_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.fuel.2021.121727","volume":"306","author":"Y Jiang","year":"2021","unstructured":"Jiang, Y., Lee, B.H., Oh, D.H.: Optimization of operating conditions to achieve combustion stability and reduce NOx emission at half-load for a 550-MW tangentially fired pulverized coal boiler. Fuel 306, 121727 (2021)","journal-title":"Fuel"},{"key":"17_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2023.129568","volume":"286","author":"W Xue","year":"2024","unstructured":"Xue, W., Tang, Z., Cao, S.: A novel online method incorporating computational fluid dynamics simulations and neural networks for reconstructing temperature field distributions in coal-fired boilers. Energy 286, 129568 (2024)","journal-title":"Energy"},{"issue":"06","key":"17_CR3","first-page":"6","volume":"23","author":"Z Chen","year":"2017","unstructured":"Chen, Z., Xian, Q., Yin, S.: Numerical simulation of temperature field and influence factors of three leaves rotarykiln for ceramsite. China Powder Sci. Technol. 23(06), 6\u201310 (2017)","journal-title":"China Powder Sci. Technol."},{"issue":"04","key":"17_CR4","first-page":"93","volume":"27","author":"X Zhang","year":"2021","unstructured":"Zhang, X., Liu, B., Liu, Z.: Influence of temperature field on particle distribution in feeder pipeline with CFD simulation. China Powder Sci. Technol. 27(04), 93\u2013103 (2021)","journal-title":"China Powder Sci. Technol."},{"key":"17_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2023.107205","volume":"138","author":"M John","year":"2024","unstructured":"John, M., Walton, K., Kinder, D.: Ultrasonic measurement of temperature distributions in extreme environments: electrical power plants testing in utility-scale steam generators. Ultrasonics 138, 107205 (2024)","journal-title":"Ultrasonics"},{"key":"17_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2024.111283","volume":"212","author":"M Zhang","year":"2024","unstructured":"Zhang, M., Jing, X., Zhou, Z.: Rapid and restricted swing control via adaptive output feedback for 5-DOF tower crane systems. Mech. Syst. Signal Process. 212, 111283 (2024)","journal-title":"Mech. Syst. Signal Process."},{"key":"17_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2019.116733","volume":"194","author":"F Hong","year":"2020","unstructured":"Hong, F., Long, D., Chen, J.: Modeling for the bed temperature 2D-interval prediction of CFB boilers based on long-short term memory network. Energy 194, 116733 (2020)","journal-title":"Energy"},{"key":"17_CR8","first-page":"651","volume":"482","author":"N Li","year":"2012","unstructured":"Li, N., Ye, F.: Temperature field numerical simulation analysis of 1000MW ultra supercritical boiler\u2019s starting water separator. Adv. Mater. Res. 482, 651\u2013654 (2012)","journal-title":"Adv. Mater. Res."},{"key":"17_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TIM.2021.3123218","volume":"70","author":"H Wang","year":"2021","unstructured":"Wang, H., Zhou, X., Yang, Q.: A reconstruction method of boiler furnace temperature distribution based on acoustic measurement. IEEE Trans. Instrum. Meas. 70, 1\u201313 (2021)","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"17","key":"17_CR10","doi-asserted-by":"publisher","first-page":"2024","DOI":"10.1177\/1045389X20983893","volume":"32","author":"Y Sun","year":"2021","unstructured":"Sun, Y., Zhang, C., Ji, H.: A temperature field reconstruction method for spacecraft leading edge structure with optimized sensor array. J. Intell. Mater. Syst. Struct. 32(17), 2024\u20132038 (2021)","journal-title":"J. Intell. Mater. Syst. Struct."},{"issue":"2","key":"17_CR11","doi-asserted-by":"publisher","first-page":"247","DOI":"10.3844\/ajeassp.2019.247.258","volume":"12","author":"A Zahraei","year":"2019","unstructured":"Zahraei, A., Eslamian, S., Rizi, A.S.: Mapping of temperature trend slope in Iran\u2019s Zayanderud river basin: a comparison of interpolation methods. Am. J. Eng. Appl. Sci. 12(2), 247\u2013258 (2019)","journal-title":"Am. J. Eng. Appl. Sci."},{"key":"17_CR12","doi-asserted-by":"crossref","unstructured":"Wang, L., Song, M., Liu, S.: An effective algorithm for offshore air temperature prediction with LSTM neural network and wavelet decomposition and reconstruction. J. Phys.: Conf. Ser. 2414(1), 012016 (2022). IOP Publishing","DOI":"10.1088\/1742-6596\/2414\/1\/012016"},{"key":"17_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.firesaf.2023.103887","volume":"140","author":"S Kim","year":"2023","unstructured":"Kim, S., Park, S., Shin, J.: Deep-learning-based data loss reconstruction for spatiotemporal temperature in piloti structures: enhancing applicability with limited datasets. Fire Saf. J. 140, 103887 (2023)","journal-title":"Fire Saf. J."},{"key":"17_CR14","doi-asserted-by":"crossref","unstructured":"Cai, T., Deng, Z., Park, Y.: Acquisition of kHz-frequency two-dimensional surface temperature field using phosphor thermometry and proper orthogonal decomposition assisted long short-term memory neural networks. Int. J. Heat Mass Transfer. 165, 120662 (2021)","DOI":"10.1016\/j.ijheatmasstransfer.2020.120662"},{"key":"17_CR15","doi-asserted-by":"crossref","unstructured":"Chiriac, C.: Optimal use of inverse distance weighting method for temperature prediction. In: 2020 12th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), pp. 1\u20137. IEEE (2020)","DOI":"10.1109\/ECAI50035.2020.9223141"},{"issue":"6088","key":"17_CR16","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1038\/323533a0","volume":"323","author":"DE Rumelhart","year":"1986","unstructured":"Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning representations by back-propagating errors. Nature 323(6088), 533\u2013536 (1986)","journal-title":"Nature"},{"issue":"4","key":"17_CR17","doi-asserted-by":"publisher","first-page":"1152","DOI":"10.1109\/TCE.2023.3255831","volume":"69","author":"Y Han","year":"2023","unstructured":"Han, Y., Zhang, H., Shi, J., Ma, J., Xu, X.: Inspiration transfer for intelligent design: a generative adversarial network with fashion attributes disentanglement. IEEE Trans. Consum. Electron. 69(4), 1152\u20131163 (2023)","journal-title":"IEEE Trans. Consum. Electron."},{"issue":"8","key":"17_CR18","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"key":"17_CR19","doi-asserted-by":"crossref","unstructured":"Pratiwi, H., Windarto, A.P., Susliansyah, S.: Sigmoid activation function in selecting the best model of artificial neural networks. J. Phys.: Conf. Ser. 1471(1), 012010 (2020). IOP Publishing","DOI":"10.1088\/1742-6596\/1471\/1\/012010"},{"key":"17_CR20","doi-asserted-by":"crossref","unstructured":"Szanda\u0142a, T.: Review and comparison of commonly used activation functions for deep neural networks. In: Bio-inspired Neurocomputing, pp. 203\u2013224 (2021)","DOI":"10.1007\/978-981-15-5495-7_11"},{"issue":"2","key":"17_CR21","first-page":"47","volume":"16","author":"G Hren","year":"2023","unstructured":"Hren, G.: Visualisation of 4D thermal maps. J. Energy Technol. 16(2), 47\u201356 (2023)","journal-title":"J. Energy Technol."},{"issue":"6","key":"17_CR22","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6501\/acc2d8","volume":"34","author":"AP Vedurmudi","year":"2023","unstructured":"Vedurmudi, A.P., Janzen, K., Nagler, M.: Uncertainty-aware temperature interpolation for measurement rooms using ordinary Kriging. Meas. Sci. Technol. 34(6), 064007 (2023)","journal-title":"Meas. Sci. Technol."},{"key":"17_CR23","doi-asserted-by":"crossref","unstructured":"Ozbek, A., Sekertekin, A., Bilgili, M.: Prediction of Atmospheric Air Temperature Using Long Short-Term Memory (LSTM) Recurrent Neural Network. SSRN. 3980616 (2021)","DOI":"10.2139\/ssrn.3980616"}],"container-title":["Communications in Computer and Information Science","Neural Computing for Advanced Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-7001-4_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,21]],"date-time":"2024-09-21T18:02:30Z","timestamp":1726941750000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-7001-4_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,22]]},"ISBN":["9789819770007","9789819770014"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-7001-4_17","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2024,9,22]]},"assertion":[{"value":"22 September 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NCAA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Computing for Advanced Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Guilin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 July 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 July 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ncaa2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aaci.org.hk\/ncaa2024\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}