Study on Short Term Temperature Forecast Model in Jiangxi Province based on LightGBM Machine Learning Algorithm by Kanghui SUN, An XIAO, Houjie XIA

“…In order to achieve further improvement in the forecast accuracy of station temperatures and enhance the forecast capability for extreme temperatures， this study establishes a 24-hour national station daily maximum （minimum） temperature forecast model for Jiangxi Province based on the LightGBM machine-learning algorithm and the MOS forecast framework by using the surface observation data of 91 national stations in Jiangxi Province and the upper-air and surface forecast data of the ECMWF model from 2017 to 2019.The results of the 2020 evaluation show that the LightGBM model daily maximum （minimum） temperature forecast is consistent with the observed trend， and the annual average forecast is better than that of three numerical models， ECMWF， CMA-SH9 and CMA-GFS， two machine learning products， RF and SVM， and subjective revision products.In terms of the spatial and temporal distribution of forecast errors， the model's daily maximum （minimum） temperature forecast errors in winter and spring are slightly larger than those in summer and autumn； the daily maximum temperature forecast errors show the spatial distribution characteristics of "larger in the south and smaller in the north， and larger in the periphery than in the centre"， while the opposite is true for the daily minimum temperatures.In terms of important weather processes， the LightGBM model has the best prediction effect among the seven products in the high temperature process； in the strong cold air process， the LightGBM model is still better than the three numerical model products and the other two machine-learning models， but the prediction effect of the daily minimum temperature is not as good as that of the subjective revision products.After a simple empirical correction for the low-temperature forecast error in the strong cold air process， the model low-temperature forecast effect is close to that of the subjective revision product.The model significance analysis shows that the recent surface observation features also contribute to the model construction， and the results can be used as a reference for model improvement and temperature forecast product development.At present， the LightGBM model temperature forecast products have been applied to meteorological operations in Jiangxi Province.…”
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Auxiliary Model-Based Multiple Innovation Recursive Algorithm on Nonlinear Systems utilizing KeyTerm Separation Technique by Fang Qiu, Yan Ji

“…For further improving the parameter estimation accuracy, an auxiliary model-based multi-innovation extended least-squares algorithm is presented by using the multi-innovation identification theory. …”
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Language Models for Multilabel Document Classification of Surgical Concepts in Exploratory Laparotomy Operative Notes: Algorithm Development Study by Jeremy A Balch, Sasank S Desaraju, Victoria J Nolan, Divya Vellanki, Timothy R Buchanan, Lindsey M Brinkley, Yordan Penev, Ahmet Bilgili, Aashay Patel, Corinne E Chatham, David M Vanderbilt, Rayon Uddin, Azra Bihorac, Philip Efron, Tyler J Loftus, Protiva Rahman, Benjamin Shickel

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Predictive Model for Diagnosis of Gestational Diabetes in the Kurdistan Region by a Combination of Clustering and Classification Algorithms: An Ensemble Approach by Rasool Jader, Sadegh Aminifar

“…Intelligent systems designed by machine learning algorithms are remodelling all fields of our lives, including the healthcare system. …”
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A Unique Bifuzzy Manufacturing Service Composition Model Using an Extended Teaching-Learning-Based Optimization Algorithm by Yushu Yang, Jie Lin, Zijuan Hu

“…Next, we address the multi-objective optimization issue through the application of extended teaching-learning-based optimization (ETLBO) algorithm. The improvements of the ETLBO algorithm include utilizing the adaptive parameters and introducing a local search strategy combined with a genetic algorithm (GA). …”
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Integrated Modeling and Optimal Operation Strategy of Building Cooling System Combining the Standardized Thermal Resistance and Genetic Algorithm by Liang Tian, Bohong Lai, Tianzhen Yang, Xingce Wang, Junhong Hao, Kaicheng Liu

“…ABSTRACT Integrated modeling and operation optimization of building energy systems is significant for improving the energy utilization efficiency and reducing carbon emission. …”
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Research on adverse event classification algorithm of da Vinci surgical robot based on Bert-BiLSTM model by Tianchun Li, Wanting Zhu, Wenke Xia, Li Wang, Weiqi Li, Peiming Zhang

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Optimized stress-strain modeling of eco-friendly fiber-reinforced concrete members using meta-heuristic algorithms by Sawsan Akram Hassan, Mahir M. Hason, Ammar N. Hanoon, Ali A. Abdulhameed

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Revolutionizing proton exchange membrane fuel cell modeling through hybrid aquila optimizer and arithmetic algorithm optimization by Manish Kumar Singla, S. A. Muhammed Ali, Ramesh Kumar, Pradeep Jangir, Mohammad Khishe, G. Gulothungan, Haitham A. Mahmoud

“…For each datasheet, both Current–Voltage (I/V) and Power–Voltage (P/V) characteristics of the PEMFCs scenarios closely aligned with those observed in experimental data, affirming AOAAO’s superior accuracy, robustness, and time efficiency for real-time fuel cell modeling. In terms of computational efficiency, AOAAO runtime is significantly faster than all compared algorithms, demonstrating an efficiency improvement of approximately 98%.…”
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Estimating Nurse Workload Using a Predictive Model From Routine Hospital Data: Algorithm Development and Validation by Paul Meredith, Christina Saville, Chiara Dall’Ora, Tom Weeks, Sue Wierzbicki, Peter Griffiths

“…ObjectiveThe objective of this study is to explore whether an algorithm could estimate ward workload using existing routinely recorded data. …”
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Modeling and Solving the Knapsack Problem with a Multi-Objective Equilibrium Optimizer Algorithm Based on Weighted Congestion Distance by Ziqian Wang, Xin Huang, Yan Zhang, Danju Lv, Wei Li, Zhicheng Zhu, Jian’e Dong

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Quantum Algorithm for Solving the Wave Equation on a Hexagonal Grid by Roman Novak

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Methods and Algorithms for Decision-Making in Agro-Industrial Environmental Management by Olga Ivashchuk, Vyacheslav Fedorov, Zhanat Kenzhebayeva, Oleg Ivashchuk, Moldir Allaniyazova, Kaiyrbek Makulov, Gulnar Kaziyeva

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Towards Economic Sustainability: A Comprehensive Review of Artificial Intelligence and Machine Learning Techniques in Improving the Accuracy of Stock Market Movements by Atoosa Rezaei, Iheb Abdellatif, Amjad Umar

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Heat Pump Temperature Trajectory Planning Algorithm for Bus Voltage Sag Suppression by Yangyang ZHAO, Lan LIU, Wei ZHAO, Shuang ZENG, Anqi LIANG, Hanqiu WANG, Kai MA

“…The simulation results show that the proposed algorithm can significantly suppress the transient sag of DC bus voltage in the process of heat pump temperature regulation, which are well suited to the smooth control and improving stability of building’s DC microgrid system.…”
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Comprehensive improvement of energy efficiency and indoor environmental quality for university library atrium—A multi-objective fast optimization framework by Shen Xu, Yongzhong Chen, Jianlin Liu, Jian Kang, JinFeng Gao, Yuchen Qin, Wenjun Tan, Gaomei Li

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Usage of the optimal fuzzy system models on chloride diffusion of concrete by Shuai Sun

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Application of deep learning algorithm for judicious use of anti-VEGF in diabetic macular edema by Anwesa Mondal, Apurba Nandi, Subhasish Pramanik, Lakshmi Kanta Mondal

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Feedforward Factorial Hidden Markov Model by Zhongxing Peng, Wei Huang, Yinghui Zhu

“…In the direct FFHMM, alterations to one sub-hidden Markov model (HMM) do not affect the others, enabling individual improvements in HMM estimation. …”
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Enhanced LSTM-based AI model for accurate dissolved oxygen prediction in aquaculture systems by Ala Saleh Alluhaidan, Prabu P, Romana Aziz, Shakila Basheer

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