Development and optimization of an electrohydrodynamic dehydrator using ANN-GA for improved energy performance by Chakrit Suvanjumrat, Klar Kongsarai, Piyamon Phong-arom, Namnguen Chumphong, Machimontorn Promtong, Jetsadaporn Priyadumkol

“…Furthermore, an integrated ANN–genetic algorithm (ANN-GA) approach was established to optimize the drying parameters, aiming to maximize drying kinetics and minimize SEC. …”
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A convolutional neural network driven suspension control strategy to enhance sustainability of high-speed trains by Duo Zhang, Hong-Wei Li, Fang-Ru Zhou, Yin-Ying Tang, Qi-Yuan Peng

“…Subsequently, a convolutional neural network is constructed based on the simulation data to predict the energy consumption and riding comfort under complex operation scenarios. …”
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Identifying the Peak Flowering Dates of Winter Rapeseed with a NBYVI Index Using Sentinel-1/2 by Fazhe Wu, Peng Lu, Shengbo Chen, Yucheng Xu, Zibo Wang, Rui Dai, Shuya Zhang

“…The study uses phenological characteristics and the random forest classification algorithm to create a map of winter rapeseed in parts of the middle and lower reaches of the Yangtze River Basin, achieving a Kappa coefficient of 90.57%. …”
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Detection and Optimization of Photovoltaic Arrays’ Tilt Angles Using Remote Sensing Data by Niko Lukač, Sebastijan Seme, Klemen Sredenšek, Gorazd Štumberger, Domen Mongus, Borut Žalik, Marko Bizjak

“…Consequently, numerous approaches have been developed over the past few years that utilize remote sensing data to predict or map solar potential. However, they primarily address hypothetical scenarios, and few focus on improving existing installations. …”
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Multiphysics Feature-Based State-of-Energy Estimation for LiFePO4 Batteries Using Bidirectional Long Short-Term Memory and Particle Swarm-Optimized Kalman Filter by Zhengpu Wu, Xu He, Haisen Chen, Lu Lv, Jiuchun Jiang, Lujun Wang

“…State-of-energy (SOE) estimation helps to enhance the safety of battery operation and predict vehicle range. However, the voltage plateau of the LiFePO4 (LFP) battery presents a significant challenge for SOE estimation. …”
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Advancing Leaf Nutritional Characterization of Blueberry Varieties Adapted to Warm Climates Enhanced by Proximal Sensing by Sérgio H. G. Silva, Marcelo C. Berardo, Lucas R. Rosado, Renata Andrade, Anita F. S. Teixeira, Mariene H. Duarte, Fernanda A. Bócoli, Marco A. C. Carneiro, Nilton Curi

“…The three varieties were accurately differentiated by pXRF results (accuracy: 87%; kappa: 0.80). Predictions of nutrient contents based on dry leaves analyzed by pXRF outperformed those based on fresh leaves. …”
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Selecting patients with sickle cell disease for gene addition or gene editing‐based therapeutic approaches: Report on behalf of a joint EHA Specialized Working Group and EBMT Hemog... by Lucia de Franceschi, Franco Locatelli, David Rees, Christian Chabannon, Jean‐Hugues Dalle, Stefano Rivella, Achille Iolascon, Stephan Lobitz, Miguel R. Abboud, Josu de la Fuente, Pagona Flevari, Emanuele Angelucci, Mariane de Montalembert

“…The course of the disease is highly variable, making it difficult to predict severity and response to therapy. Allogeneic hematopoietic stem cell transplantation potentially provides a cure with a relatively low rate of complications, but few patients have an HLA‐identical sibling. …”
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Numerical analysis of geometrical configuration effects on near-field shockwave propagation in CL-20 based underwater explosives by Ji-ping Chen, Jun Wang, Xian-pi Zhang, Yan-jie Zhao, Xing-xing Wu, Fang-zhou Zhu, Jun Yu

“…The numerical methodology employs an advanced compressible multiphase flow simulation framework incorporating high-order weighted essentially non-oscillatory schemes, complemented by rigorous validation procedures involving comparative analyses against benchmark experimental data and analytical predictions from gas dynamics theory. The computational framework implements algorithmic initiation modeling for detonation processes, coupled with a front-tracking methodology employing the modified ghost fluid method to resolve discontinuities at immiscible phase boundaries. …”
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Machine learning-driven design of rare metal doped niobium alloys with enhanced strength and ductility by Zhenqiang Xiong, Zhaokun Song, Jianwei Li, Heran Wang, Xiaoxin Zhang, Bin Liang, Dong Wang

“…The model was integrated with the Non-dominated Sorting Genetic Algorithm (NSGA-III) to design alloys with superior comprehensive properties. …”
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Assessing Urban Land Parcel Dynamics Driven by Bus Rapid Transit (BRT) as an Exclusive Transit Route by Rana Tahir Mehmood, Muhammad Zaly Shah, Mehdi Moeinaddini, Muhammad Mashhood Arif, Ramine Chuhdary, Mufeeza Tahira

“…This study applies the C5.0 decision tree algorithm, a non-parametric model that creates a decision tree with leaf nodes that predict the relationship. …”
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SFPFMformer: Short-Term Power Load Forecasting for Proxy Electricity Purchase Based on Feature Optimization and Multiscale Decomposition by Chengfei Qi, Yanli Feng, Junling Wan, Xinying Mao, Peisen Yuan

“…We conducted extensive experiment on real datasets, and the experimental results show that in 4 h prediction, the RMSE, MAE, and MAPE of our model are 1128.69, 803.91, and 2.63%, respectively. …”
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Rooting depth projections of global plant functional types and driving factors analysis based on a hybrid modeling framework by Qinggong Han, Bo Liu, Yunuo Liu, Jielin Zhang, Yongxia Ding, Shouzhang Peng

“…In this study, we developed a hybrid model that combines random forest algorithm with ecosystem data simulated by LPJ-GUESS model and environmental variables to predict global rooting depth, based on 1,184 integrated rooting depth observations. …”
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A Correlation Analysis-Based Structural Load Estimation Method for RC Beams Using Machine Vision and Numerical Simulation by Chun Zhang, Yinjie Zhao, Guangyu Wu, Han Wu, Hongli Ding, Jian Yu, Ruoqing Wan

“…Subsequently, a deep neural network (DNN) is trained as a FEM surrogate model to quickly predict the structural strain response by considering material uncertainties. …”
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A Rule-Based Agent for Unmanned Systems with TDGG and VGD for Online Air Target Intention Recognition by Li Chen, Jing Yang, Yuzhen Zhou, Yanxiang Ling, Jialong Zhang

“…Then, a rule-based agent for unmanned systems for online intention recognition is proposed, with no training, no tagging, and no big data support, which is not only for intention recognition and parameter prediction, but also for formation identification of air targets. …”
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Modelling current and future forest fire susceptibility in north-eastern Germany by K. H. Horn, K. H. Horn, S. Vulova, S. Vulova, H. Li, B. Kleinschmit

“…We applied a random forest (RF) machine learning (ML) algorithm to model current and future FFS in the federal state of Brandenburg (Germany) using topographic, climatic, anthropogenic, soil, and vegetation predictors. …”
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Preoperative predictors of thrombosis in children with congenital heart disease by V. A. Lastovka, R. F. Tepaev, O. B. Gordeeva, A. R. Bidzhiev, A. A. Chotchaeva

“…The literature describes in detail the disturbances in the hemostasis system observed after cardiac surgeries performed in conditions of artificial circulation, but there are no indicators that could predict the risk of thrombosis in children. The use of parameters of plasma hemostasis as predictors of thrombosis in the algorithm for diagnosing hemocoagulation disorders in children of the first year of life undergoing surgery for congenital heart defects has been substantiated. …”
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Aircraft Routing and Crew Pairing Solutions: Robust Integrated Model Based on Multi-Agent Reinforcement Learning by Chengjin Ding, Yuzhen Guo, Jianlin Jiang, Wenbin Wei, Weiwei Wu

“…The problem is formulated as a sequential decision-making process and solved via a novel multi-agent reinforcement learning algorithm. Numerical results demonstrate that the novel method outperforms prior methods in the literature in terms of solving speed and can also enhance planning robustness. …”
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Measurement of snowpack density, grain size, and black carbon concentration using time-domain diffuse optics by Connor Andrew Henley, Colin Richard Meyer, Jacob Ian Chalif, Joseph Lee Hollmann, Ramesh Raskar

“…We develop an algorithm that retrieves these properties from measurements at two wavelengths. …”
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Deep learning-based framework for Mycobacterium tuberculosis bacterial growth detection for antimicrobial susceptibility testing by Hoang-Anh T. Vo, Sang Nguyen, Ai-Quynh T. Tran, Han Nguyen, Hai Bich Ho, Philip W. Fowler, Timothy M. Walker, Thuy Thi Nguyen

“…Automated Mycobacterial Growth Detection Algorithm (AMyGDA) is a software package that uses image processing techniques to read plates, but struggles with plates that exhibit low growth or images of low quality. …”
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Resource Optimization Method Based on Spatio-Temporal Modeling in a Complex Cluster Environment for Electric Vehicle Charging Scenarios by Hongwei Wang, Wei Liu, Chenghui Wang, Kao Guo, Zihao Wang

“…To address this, a novel self-organizing prediction method for spatio-temporal resource allocation is proposed. …”
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