Intelligent analysis algorithm for power engineering data based on improved BiLSTM by Yuanyuan Xu, Jiapeng Yang, Xin Cai

“…The improved BiLSTM power engineering data analysis algorithm significantly improves the accuracy and robustness of tasks such as power load forecasting and equipment fault diagnosis by introducing self attention mechanism and multi-dimensional feature fusion. …”
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LABOUR MARKET IN UKRAINE: AN EMPIRICAL DYNAMIC ANALYSIS USING ERROR CORRECTION MODEL by I. Lukyanenko, M. Oliskevych

“…The effectiveness of the state socio-economic regulation mechanisms requires profound analysis, modeling and forecasting of the processes of the labor market by means of modern flexible econometric tools, taking into account the short-term dynamics of economic processes and features that are characteristic of the unstable economic development of our country. …”
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ANALYSIS OF A SMALL SAMPLE OF EXPERIMENTAL DATA IN THE MANAGEMENT OF GAS CONSUMPTION IN THE REGION by A. M. Kumaritov, A. E. Dzgoev, R. B. Sharibov

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Analysis of granger causality between daily and monthly temperatures of water and air, as illustrated with the example of Noteć river by Renata Graf

“…The study presents the results obtained following the analysis of the so-called Granger causality between daily and monthly temperatures of air and water for the period 1987–2013 carried out for the Noteć river and its two main tributaries: Drawa and Gwda. …”
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A dual-phase financial strategy for sustainable customer loyalty: Integrating fixed deposits and voucher systems in Sri Lankan supermarket retail by A.K.G.N. Deshapriya, W.M.A. Weerakoon, H.Y.M.T.P. Wickramasinghe, T.M.C.E.K. Tennakoon, B.N. Jayasinghe, S.A.N. Hirunika, H.P.G.T. Dulshan, M.I.V. Perera, M.D.H.S. Maddage, D.D. Munasinghe, D.G.N.D. Jayarathna, M. M. V. Senanayake, G.V.D.P.P. Perera

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Advances and applications of empirical mode decomposition and its variants in hydrology: A review by CHEN Yunfei, LIU Zuyu, LIU Xiuhua, HE Junqi, ZHENG Ce, MA Yandong

Subjects: “…data mining; multi-spatiotemporal scale analysis; hydrological variability analysis; trend tests; hydrologic forecasting…”
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Renewable Electricity Management Cloud System for Smart Communities Using Advanced Machine Learning by Yukta Mehta, Vincent Lo, Vijen Mehta, Kunal Agrawal, Charan Teja Madabathula, Eugene Chang, Jerry Gao

Subjects: “…electricity shortage forecasting…”
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Textual Data Science for Logistics and Supply Chain Management by Horst Treiblmaier, Patrick Mair

Subjects: “…supply chain forecasting…”
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Educational Effectiveness of Using Big Data Based and Its Evaluation with Cluster Analysis and Qualification Framework in Financial Services and Management by Yujie Jiao, Ruiting Zhang, Ying Zhu

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Status and trend analysis of the production, export and import of wood and wood products in the G20 countries from 2004 to 2021 by Vinod Kumar Upadhyay, Ritesh Tailor, Rashmi Ramesh Shanbhag, Narasimha Murthy, Pradeep Kumar Kushwaha, Manish Ranjan

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Predicting indoor temperature of solar green house by machine learning algorithms: A comparative analysis and a practical approach by Wenhe Liu, Tao Han, Cong Wang, Feng Zhang, Zhanyang Xu

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A time series analysis of aquaculture milkfish production volume using the Box-Jenkins SARIMA Model: A case study from Davao Oriental, Philippines by Jimmy Jr C. Lape, Jerd M. Dela Gente

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Medical-Environmental Assessment and Forecasting of Socially Significant Pathology of the Population of the Republic of Dagestan by A. G. Gasangadzhieva, P. I. Gabibova, M. G. Daudova, I. V. Galkina, K. M. Giraev, Z. Ya. Magomedova

“…This was carried out through current and retrospective analysis of regional health indicators, medical-geographical and mathematical statistical analysis. …”
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Road Freight Demand Forecasting Using National Accounts’ Data—The Case of Cereals by Taha Karasu, Pekka Leviäkangas, David John Edwards

“…This paper investigates the potential of utilising historical agricultural production data for enhancing road freight transport forecasting, focusing on cereal production. This study applies a multiple linear regression analysis using national statistical accounts and secondary data. …”
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Modeling and Forecasting Time-Series Data with Multiple Seasonal Periods Using Periodograms by Solomon Buke Chudo, Gyorgy Terdik

“…The STL + ETS model exhibited an enhanced performance, surpassing both BATS and TBATS in energy forecasting. These findings improve our understanding of multiple seasonal patterns, assist us in selecting dominating periods, provide new practical forecasting approaches for time-series analysis, and inform professionals seeking superior forecasting solutions in various fields.…”
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Assimilation of Fengyun-4A Atmospheric Motion Vectors and Its Impact on China Meteorological Administration—Beijing System Forecasts by Yanhui Xie, Shuting Zhang, Xin Sun, Min Chen, Jiancheng Shi, Yu Xia, Ruixia Liu

“…For rainfall forecast with different thresholds, the score skills increased slightly after 6 h of the forecasts. …”
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Model of Financial Incentives for Innovation Activity in Industrial Sector: Development and Forecasting of Efficiency by S. A. Manshilin, A. F. Leshchinskaya

“…The authors apply the following methods: statistical analysis, correlation and regression analysis, forecasting, scenario analysis and construction of the trend of the GDP of the Russian Federation. …”
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Carbon emission forecasting in Zhejiang Province based on LASSO algorithm and grey model by HONG Jingke, DU Wei, SHAO Jin*, LAO Huimin

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Modeling and forecast of gas hydrate distribution in the Black Sea: main principles and approaches by Volodymyr Iemelianov, Olena Ivanik, Olena Ivanik, Tamara Kukovska, Natalia Fedoronchuk, Natalia Fedoronchuk, Ihor Shuraiev, Eduard Petrushenko, Kateryna Hadiatska

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Machine-learning-based analytics for risk forecasting of anaphylaxis during general anesthesia by Shuang Liu, Yasuyuki Suzuki, Toshihiro Yorozuya, Masaki Mogi

“…After data pre-processing, the performance of five classification methods: Logistic Regression Analysis, Support Vector Machine, Random Forest, Linear Discriminant Analysis, and Naïve Bayes), which were integrated with four feature selection methods (Recursive Feature Elimination, Chi-Squared Method, Correlation-based Feature Selection, and Information Gain Ratio), was evaluated using two-layer cross-validation. …”
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