{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T05:41:28Z","timestamp":1771047688599,"version":"3.50.1"},"reference-count":23,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2025,2,15]],"date-time":"2025-02-15T00:00:00Z","timestamp":1739577600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,2,15]],"date-time":"2025-02-15T00:00:00Z","timestamp":1739577600000},"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":["Appl Intell"],"published-print":{"date-parts":[[2025,5]]},"DOI":"10.1007\/s10489-025-06321-8","type":"journal-article","created":{"date-parts":[[2025,2,15]],"date-time":"2025-02-15T08:49:43Z","timestamp":1739609383000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Intelligent forecasting algorithm of power industry expansion based on time series and entropy weight method"],"prefix":"10.1007","volume":"55","author":[{"given":"Guoyao","family":"Wu","sequence":"first","affiliation":[]},{"given":"Zhiqiang","family":"Lan","sequence":"additional","affiliation":[]},{"given":"Xiaofang","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Xiaoying","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Linling","family":"Mao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,2,15]]},"reference":[{"issue":"2","key":"6321_CR1","doi-asserted-by":"publisher","first-page":"1376","DOI":"10.1016\/j.renene.2021.11.019","volume":"185","author":"C Lamnatou","year":"2022","unstructured":"Lamnatou C, Chemisana D, Cristofari C (2022) Smart grids and smart technologies in relation to photovoltaics, storage systems, buildings and the environment. Renew Energy 185(2):1376\u20131391","journal-title":"Renew Energy"},{"issue":"4","key":"6321_CR2","first-page":"107819.1","volume":"206","author":"LM Castro","year":"2022","unstructured":"Castro LM, Gonz\u00e1lez-Cabrera N (2022) Short-term generation capacity expansion planning considering multi-terminal vsc hvdc links using a linear programming framework improved by shift factors. Electr Power Syst Res 206(4):107819.1-107819.12","journal-title":"Electr Power Syst Res"},{"issue":"1","key":"6321_CR3","first-page":"116918.1","volume":"293","author":"BN Oreshkin","year":"2021","unstructured":"Oreshkin BN, Dudek G, Peka P, Turkina E (2021) N-beats neural network for mid-term electricity load forecasting. Appl Energy 293(1):116918.1-116918.13","journal-title":"Appl Energy"},{"issue":"11","key":"6321_CR4","first-page":"117540.1","volume":"302","author":"U Ahin","year":"2021","unstructured":"Ahin U, Ball S, Chen Y (2021) Forecasting seasonal electricity generation in european countries under covid-19-induced lockdown using fractional grey prediction models and machine learning methods. Appl Energy 302(11):117540.1-117540.24","journal-title":"Appl Energy"},{"issue":"4","key":"6321_CR5","first-page":"107729.1","volume":"205","author":"EF Bodal","year":"2022","unstructured":"Bodal EF, Botterud A, Korpas M (2022) Capacity expansion planning with stochastic rolling horizon dispatch. Electr Power Syst Res 205(4):107729.1-107729.10","journal-title":"Electr Power Syst Res"},{"issue":"8","key":"6321_CR6","doi-asserted-by":"publisher","first-page":"830","DOI":"10.1049\/cmu2.12384","volume":"16","author":"R Chinnaraji","year":"2022","unstructured":"Chinnaraji R, Ragupathy P (2022) Accurate electricity consumption prediction using enhanced long short-term memory. IET Commun 16(8):830\u2013844","journal-title":"IET Commun"},{"issue":"6","key":"6321_CR7","first-page":"104724.1","volume":"151","author":"A Aghaee","year":"2021","unstructured":"Aghaee A, Shamsipour P, Hood S, Haugaard R (2021) A convolutional neural network for semi-automated lineament detection and vectorisation of remote sensing data using probabilistic clustering: a method and a challenge. Comput Geosci 151(6):104724.1-104724.15","journal-title":"Comput Geosci"},{"issue":"12","key":"6321_CR8","doi-asserted-by":"publisher","first-page":"8243","DOI":"10.1109\/TII.2021.3065718","volume":"17","author":"SMJ Jalali","year":"2021","unstructured":"Jalali SMJ, Ahmadian S, Khosravi A, Shafie-Khah M, Catalao JPS (2021) A novel evolutionary-based deep convolutional neural network model for intelligent load forecasting. IEEE Trans Industr Inf 17(12):8243\u20138253","journal-title":"IEEE Trans Industr Inf"},{"issue":"5","key":"6321_CR9","doi-asserted-by":"publisher","first-page":"851","DOI":"10.1049\/gtd2.12332","volume":"16","author":"F Keynia","year":"2022","unstructured":"Keynia F, Memarzadeh G (2022) A new financial loss\/gain wind power forecasting method based on deep machine learning algorithm by using energy storage system. IET Gener Transm Distrib 16(5):851\u2013868","journal-title":"IET Gener Transm Distrib"},{"issue":"1","key":"6321_CR10","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.ijar.2021.03.002","volume":"133","author":"MC Pegalajar","year":"2021","unstructured":"Pegalajar MC, Ruiz LGB, Cuellar MP, Rueda R (2021) Analysis and enhanced prediction of the spanish electricity network through big data and machine learning techniques. Int J Approx Reason 133(1):48\u201359","journal-title":"Int J Approx Reason"},{"issue":"9","key":"6321_CR11","first-page":"117173.1","volume":"297","author":"X Serrano-Guerrero","year":"2021","unstructured":"Serrano-Guerrero X, Briceo-Le\u00f3n M, Clairand JM, Escriv\u00e1-Escriv\u00e1 G (2021) A new interval prediction methodology for short-term electric load forecasting based on pattern recognition. Applied Energy 297(9):117173.1-117173.13","journal-title":"Applied Energy"},{"issue":"4","key":"6321_CR12","first-page":"106995.1","volume":"192","author":"G Memarzadeh","year":"2021","unstructured":"Memarzadeh G, Keynia F (2021) Short-term electricity load and price forecasting by a new optimal lstm-nn based prediction algorithm. Electr Power Syst Res 192(4):106995.1-106995.14","journal-title":"Electr Power Syst Res"},{"issue":"7","key":"6321_CR13","doi-asserted-by":"publisher","first-page":"6699","DOI":"10.1109\/TITS.2021.3060959","volume":"23","author":"J Monteil","year":"2021","unstructured":"Monteil J, Dekusar A, Gambella C, Lassoued Y, Mevissen M (2021) On model selection for scalable time series forecasting in transport networks. IEEE Trans Intell Transp Syst 23(7):6699\u20136708","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"1","key":"6321_CR14","doi-asserted-by":"publisher","first-page":"564","DOI":"10.1016\/j.renene.2021.11.112","volume":"184","author":"Z Li","year":"2022","unstructured":"Li Z, Luo Z, Wang Y, Fan G, Zhang J (2022) Suitability evaluation system for the shallow geothermal energy implementation in region by entropy weight method and topsis method. Renew Energy 184(1):564\u2013576","journal-title":"Renew Energy"},{"issue":"1","key":"6321_CR15","first-page":"108687.1","volume":"246","author":"H Yang","year":"2022","unstructured":"Yang H, Li P, Li H (2022) An oil imports dependence forecasting system based on fuzzy time series and multi-objective optimization algorithm: case for China. Knowl-Based Syst 246(1):108687.1-108687.14","journal-title":"Knowl-Based Syst"},{"issue":"04","key":"6321_CR16","first-page":"307","volume":"39","author":"BT Liu","year":"2022","unstructured":"Liu BT, Chen W, Yin ZG, Sun P (2022) Research on time series prediction method based on MCP regularized SWESN. Comput Simul 39(04):307\u2013311","journal-title":"Comput Simul"},{"issue":"2","key":"6321_CR17","first-page":"101252.1","volume":"44","author":"D Chakraborty","year":"2021","unstructured":"Chakraborty D, Sanyal SK (2021) Time-series data optimized ar\/arma model for frugal spectrum estimation in cognitive radio. Phys Commun 44(2):101252.1-101252.19","journal-title":"Phys Commun"},{"issue":"2","key":"6321_CR18","doi-asserted-by":"publisher","first-page":"4021269.1","DOI":"10.1061\/(ASCE)GM.1943-5622.0002253","volume":"22","author":"F Siddiqui","year":"2022","unstructured":"Siddiqui F, Sargent P, Montague G (2022) Data-based modeling approaches for short-term prediction of embankment settlement using magnetic extensometer time-series data. Int J Geomech 22(2):4021269.1-4021269.17","journal-title":"Int J Geomech"},{"issue":"10","key":"6321_CR19","first-page":"1","volume":"2021","author":"J Zhang","year":"2021","unstructured":"Zhang J (2021) A study on mental health assessments of college students based on triangular fuzzy function and entropy weight method. Math Probl Eng 2021(10):1\u20138","journal-title":"Math Probl Eng"},{"issue":"2","key":"6321_CR20","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1016\/j.renene.2021.12.100","volume":"185","author":"W Zhang","year":"2022","unstructured":"Zhang W, Lin Z, Liu X (2022) Short-term offshore wind power forecasting - a hybrid model based on discrete wavelet transform (DWT), seasonal autoregressive integrated moving average (SARIMA), and deep-learning-based long short-term memory (LSTM). Renew Energy 185(2):611\u2013628","journal-title":"Renew Energy"},{"key":"6321_CR21","doi-asserted-by":"publisher","first-page":"109077","DOI":"10.1016\/j.cie.2023.109077","volume":"177","author":"HA Kuo","year":"2023","unstructured":"Kuo HA, Chien CF (2023) Semiconductor capacity expansion based on forecast evolution and mini-max regret strategy for smart production under demand uncertainty. Comput Ind Eng 177:109077","journal-title":"Comput Ind Eng"},{"issue":"7","key":"6321_CR22","doi-asserted-by":"publisher","first-page":"3024","DOI":"10.3390\/en16073024","volume":"16","author":"G Dudek","year":"2023","unstructured":"Dudek G, Piotrowski P, Baczy\u0144ski D (2023) Intelligent forecasting and optimization in electrical power systems: advances in models and applications. Energies 16(7):3024","journal-title":"Energies"},{"issue":"1","key":"6321_CR23","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1002\/ese3.856","volume":"10","author":"C Shi","year":"2022","unstructured":"Shi C, Feng X, Jin Z (2022) Sustainable development of China\u2019s smart energy industry based on artificial intelligence and low-carbon economy. Energy Sci Eng 10(1):243\u2013252","journal-title":"Energy Sci Eng"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-025-06321-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-025-06321-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-025-06321-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T19:37:39Z","timestamp":1758310659000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-025-06321-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,15]]},"references-count":23,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2025,5]]}},"alternative-id":["6321"],"URL":"https:\/\/doi.org\/10.1007\/s10489-025-06321-8","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,15]]},"assertion":[{"value":"28 January 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 February 2025","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"The authors have no relevant financial or non-financial interests to disclose.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"457"}}