Evaluation of Eight Decomposition-Hybrid Models for Short-Term Daily Reference Evapotranspiration Prediction by Yunfei Chen, Zuyu Liu, Ting Long, Xiuhua Liu, Yaowei Gao, Sibo Wang

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MODELING OF PROBLEMATIC SITUATIONS IN INTERSUBJECTIVE CONTROL THEORY by T. V. Moiseeva, N. Yu. Polyaeva

“…The theory of intersubjective management for finding a way out of problematic social situations is developed. Additionally, an algorithm for analysing the problem situation and finding a solution is presented, the “problem situation” is considered in terms of the meaning of the problem situation chain, a formal mathematical model of the problem situation is constructed and the application of the basic provisions of the theory of intersubjective control is described on an example.Conclusion. …”
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Sources of uncertainty in the SPITFIRE global fire model: development of LPJmL-SPITFIRE1.9 and directions for future improvements by L. Oberhagemann, L. Oberhagemann, M. Billing, W. von Bloh, M. Drüke, M. Drüke, M. Forrest, S. P. K. Bowring, J. Hetzer, J. Ribalaygua Batalla, K. Thonicke

“…We resolve these issues by correcting the implementation of the Rothermel model and implementing a new live grass moisture parametrization, in addition to several other improvements, including a multi-day fire spread algorithm, and evaluate these changes in the European domain. …”
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Improving maize water stress diagnosis accuracy by integrating multimodal UAVs data and leaf area index inversion model by Qi Liu, Xiaolong Hu, Yiqiang Zhang, Liangsheng Shi, Wei Yang, Yixuan Yang, Ruxin Zhang, Dongliang Zhang, Ze Miao, Yifan Wang, Zhongyi Qu

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An Assist-as-Needed Control Strategy Based on a Subjective Intention Decline Model by Hao Yan, Fangcao Zhang, Xingao Li, Chenchen Zhang, Yunjia Zhang, Yongfei Feng

“…The subjective intention decline module collects surface electromyography (sEMG) data during patient training and optimizes support vector machine (SVM) using quantum particle swarm optimization (QPSO) algorithms to establish a subjective intention decline model. …”
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A Judging Scheme for Large-Scale Innovative Class Competitions Based on Z-Score Pro Computational Model and BP Neural Network Model by Zhuoting Yu, Hongzhong Deng, Shuaiwen Tang

“…The model employs a genetic algorithm to maximize the overlap between experts while ensuring a balanced distribution of evaluation tasks, thus reducing the entropy generated by imbalances in the process. …”
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Application Study on CPSO-FLN Model in the Steam Turbine Heat Rate Forecast by Jian HU, Chao LIU

“…The cloud model based adaptive weight strategy is introduced into the particle swarm algorithm such that the weight of the particle swarm algorithm can be self-adaptively adjusted to improve the global optimization performance of the PSO algorithm by taking advantage of the randomness and stability of cloud droplets. …”
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Machine learning algorithms to predict feeding practices during diarrheal disease and its determinants among under-five children in East Africa by Tirualem Zeleke Yehuala, Nebebe Demis Baykemagn, Bewuketu Terefe

“…Python software was utilized for data processing and machine learning model building. We employed four ML algorithms, such as Random Forest (RF), Decision Tree (DT), XGB (Extreme Gradient Boosting), and Logistic Regression (LR). …”
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Mathematical Models for Management Information Systems on Digital Platforms: from Resource Management to Demand Forecasting by Viktor Godliuk

“…The article deals with mathematical models and algorithms used for information management systems of digital platforms. …”
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Comparative analysis of machine learning algorithms for predicting tibial intramedullary nail length from patient characteristics by Yujian Hui, Hengda Hu, Jinghua Xiang, Xingye Du

“…Abstract Objective This study aimed to evaluate the performance of five machine learning algorithms in predicting tibial intramedullary nail length using patient demographic data (gender, height, age, and weight), with the goal of developing a clinically relevant and accurate predictive model. …”
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An improved extreme learning machine algorithm for prospectivity mapping of copper deposits using multi-source remote sensing data: a case study in the North Altyn Tagh, Xinjiang,... by Boqi Yuan, Qinjun Wang, Wentao Xu, Chaokang He, Wenyue Xie

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YOLOv8-GDCI: Research on the Phytophthora Blight Detection Method of Different Parts of Chili Based on Improved YOLOv8 Model by Yulong Duan, Weiyu Han, Peng Guo, Xinhua Wei

“…In comparison with the YOLOv8n model, the YOLOv8-GDCI model demonstrates an improvement of 0.9% in precision, an increase of 1.8% in recall, and a remarkable enhancement of 1.7% in average precision. …”
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Enhancing <i>Panax notoginseng</i> Leaf Disease Classification with Inception-SSNet and Image Generation via Improved Diffusion Model by Ruoxi Wang, Xiaofan Zhang, Qiliang Yang, Lian Lei, Jiaping Liang, Ling Yang

“…The experimental results show that our proposed ECA-based diffusion model FID reaches 42.73, compared with the baseline model, which improved by 74.71%. …”
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On-Line Parameter Identification and SOC Estimation for Lithium-Ion Batteries Based on Improved Sage–Husa Adaptive EKF by Xuan Tang, Hai Huang, Xiongwu Zhong, Kunjun Wang, Fang Li, Youhang Zhou, Haifeng Dai

“…On this basis, the two resistor-capacitor equivalent circuit model is selected for estimating the SOC of the Li-ion battery by combining the extended Kalman filter (EKF) with the Sage–Husa adaptive algorithm. …”
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Machine Learning Performance Analysis for Bagging System Improvement: Key Factors, Model Optimization, and Loss Reduction in the Fertilizer Industry by Ari Primantara, Udisubakti Ciptomulyono, Berlian Al Kindhi

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Machine learning model design for high performance cloud computing &amp; load balancing resiliency: An innovative approach by Nilayam Kumar Kamila, Jaroslav Frnda, Subhendu Kumar Pani, Rashmi Das, Sardar M.N. Islam, P.K. Bharti, Kamalakanta Muduli

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Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials by Simin Nazari, Amira Abdelrasoul

“…Seven machine learning algorithms for predicting affinity energy are analyzed and compared, with random forest demonstrating superior predictive accuracy. …”
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Improving Forest Above-Ground Biomass Estimation Accuracy Using Multi-Source Remote Sensing and Optimized Least Absolute Shrinkage and Selection Operator Variable Selection Method by Er Wang, Tianbao Huang, Zhi Liu, Lei Bao, Binbing Guo, Zhibo Yu, Zihang Feng, Hongbin Luo, Guanglong Ou

“…Compared to the optimal SGBoost model with the Lasso variable selection method (R² of 0.69, RMSE of 18.63 Mg/ha), the VIF-Lasso method improves R² by 0.06 and reduces RMSE by 2.15 Mg/ha, while the Lasso-GA method improves R² by 0.04 and reduces RMSE by 1.93 Mg/ha. …”
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Dynamic Grouping Control of BESS for Remaining Useful Life Extension and Overall Energy Efficiency Improvement in Smoothing Wind Power Fluctuations by Yang Yu, Dongyang Chen, Yuwei Wu, Boxiao Wang, Yuhang Huo, Wentao Lu, Zengqiang Mi

“…Second, a model to optimize capacity allocation for three battery groups (BGs) in BESS is established considering LL and OEE, and it is solved by the designed improved beetle swarm antennae search algorithm. …”
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Nonlinear Hysteresis Parameter Identification of Piezoelectric Actuators Using an Improved Gray Wolf Optimizer with Logistic Chaos Initialization and a Levy Flight Variant by Yonggang Yan, Kangqiao Duan, Jianjun Cui, Shiwei Guo, Can Cui, Yongsheng Zhou, Junjie Huang, Geng Wang, Dengpan Zhang, Fumin Zhang

“…This paper proposes an improved Gray Wolf Optimization (GWO) algorithm for high-accuracy identification of hysteresis model parameters based on the Bouc–Wen (BW) differential equation. …”
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