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J. Neur. Syst."],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:p>Multivariate workload prediction in cloud computing environments is a critical research problem. Effectively capturing inter-variable correlations and temporal patterns in multivariate time series is key to addressing this challenge. To address this issue, this paper proposes a convolutional model based on a Nonlinear Spiking Neural P System (ConvNSNP), which enhances the ability to process nonlinear data compared to conventional convolutional models. Building upon this, a hybrid forecasting model is developed by integrating ConvNSNP with a Bidirectional Long Short-Term Memory (BiLSTM) network. ConvNSNP is first employed to extract temporal and cross-variable dependencies from the multivariate time series, followed by BiLSTM to further strengthen long-term temporal modeling. Comprehensive experiments are conducted on three public cloud workload traces from Alibaba and Google. The proposed model is compared with a range of established deep learning approaches, including CNN, RNN, LSTM, TCN and hybrid models such as LSTNet, CNN-GRU and CNN-LSTM. Experimental results on three public datasets demonstrate that our proposed model achieves up to 9.9% improvement in RMSE and 11.6% improvement in MAE compared with the most effective baseline methods. The model also achieves favorable performance in terms of MAPE, further validating its effectiveness in multivariate workload prediction.<\/jats:p>","DOI":"10.1142\/s0129065725500716","type":"journal-article","created":{"date-parts":[[2025,9,12]],"date-time":"2025-09-12T08:24:21Z","timestamp":1757665461000},"source":"Crossref","is-referenced-by-count":0,"title":["A Multivariate Cloud Workload Prediction Method Integrating Convolutional Nonlinear Spiking Neural Model with Bidirectional Long Short-Term Memory"],"prefix":"10.1142","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-3368-7792","authenticated-orcid":false,"given":"Minglong","family":"He","sequence":"first","affiliation":[{"name":"School of Computer and Software Engineering, Xihua University, Chengdu 610039, P.\u00a0R.\u00a0China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-1377-7745","authenticated-orcid":false,"given":"Nan","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Computer and Software Engineering, Xihua University, Chengdu 610039, P.\u00a0R.\u00a0China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4736-0164","authenticated-orcid":false,"given":"Hong","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Computer and Software Engineering, Xihua University, Chengdu 610039, P.\u00a0R.\u00a0China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-5283-9954","authenticated-orcid":false,"given":"Zhicai","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer and Software Engineering, Xihua University, Chengdu 610039, P.\u00a0R.\u00a0China"}]}],"member":"219","published-online":{"date-parts":[[2025,9,27]]},"reference":[{"key":"S0129065725500716BIB001","doi-asserted-by":"publisher","DOI":"10.1109\/MITP.2009.22"},{"key":"S0129065725500716BIB002","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2022.04.012"},{"key":"S0129065725500716BIB003","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-021-04107-6"},{"key":"S0129065725500716BIB004","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-018-2510-7"},{"key":"S0129065725500716BIB005","doi-asserted-by":"publisher","DOI":"10.1057\/palgrave.jors.2600823"},{"key":"S0129065725500716BIB006","doi-asserted-by":"publisher","DOI":"10.1016\/0047-259X(85)90027-2"},{"key":"S0129065725500716BIB007","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2011.tm09771"},{"key":"S0129065725500716BIB008","doi-asserted-by":"publisher","DOI":"10.1109\/ICCCNT45670.2019.8944435"},{"key":"S0129065725500716BIB009","doi-asserted-by":"publisher","DOI":"10.1109\/TCC.2014.2350475"},{"key":"S0129065725500716BIB010","doi-asserted-by":"publisher","DOI":"10.1145\/2371536.2371562"},{"key":"S0129065725500716BIB011","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-022-24909-9"},{"key":"S0129065725500716BIB012","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2017.04.013"},{"key":"S0129065725500716BIB013","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-017-9593-z"},{"key":"S0129065725500716BIB014","doi-asserted-by":"publisher","DOI":"10.1016\/S0169-7439(03)00111-4"},{"key":"S0129065725500716BIB015","doi-asserted-by":"publisher","DOI":"10.1109\/COMPSAC.2013.21"},{"key":"S0129065725500716BIB016","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksuci.2021.04.011"},{"key":"S0129065725500716BIB017","doi-asserted-by":"publisher","DOI":"10.1089\/big.2020.0159"},{"key":"S0129065725500716BIB018","doi-asserted-by":"publisher","DOI":"10.1109\/IIKI.2016.39"},{"key":"S0129065725500716BIB019","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"S0129065725500716BIB020","unstructured":"J. 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