Deep Learning-Based Recurrence Prediction in HER2-Low Breast Cancer: Comparison of MRI-Alone, Clinicopathologic-Alone, and Combined Models by Seoyun Choi, Youngmi Lee, Minwoo Lee, Jung Hee Byon, Eun Jung Choi

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Construction of a risk prediction model for pulmonary infection in patients with spontaneous intracerebral hemorrhage during the recovery phase based on machine learning by Jixiang Xu, Yuan Li, Fumin Zhu, Fumin Zhu, Xiaoxiao Han, Liang Chen, Yinliang Qi, Yinliang Qi, Xiaomei Zhou, Xiaomei Zhou

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Comparing the Indices predictive of the thermal injury outcome by E A. Zhirkova, T. G. Spiridonova, A. V. Sachkov, A. O. Medvedev, E. I. Eliseenkova, I. G. Borisov, M. L. Rogal, S. S. Petrikov

“…While developing the algorithms for diagnosis and treatment of patients with thermal injury, an injury outcome prediction index with the best predictive properties should be used.Aim. …”
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A prototype-based rockburst types and risk prediction algorithm considering intra-class variance and inter-class distance of microseismic data by Xiufeng Zhang, Guoying Li, Yang Chen, Hao Wang, Haikuan Zhang, Haitao Li, Weisheng Du, Xiao Li, Xuewei Xu, Yuze He

“…Therefore, based on the quantitative study of the relationship between the performance of a deep learning prediction algorithm and a rockburst prediction vector, a rockburst risk and type prediction algorithm based on a convolutional neural network (CNN)-gated recurrent unit (GRU) model with prototype-based prediction is proposed. …”
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Active noise reduction system by Wojciech CIESIELKA

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Simultaneous Energy Optimization of Heating Systems by Multi-Zone Predictive Control—Application to a Residential Building by Rina Bitar, Nicolas Youssef, Julien Chamoin, Fadi Hage Chehade, Didier Defer

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Real power loss reduction by Rock Dove optimization and Fuligo Septica optimization algorithms by Kanagasabai L.

“…This paper aims to use the Rock Dove (RD) optimization algorithm and the Fuligo Septica optimization (FSO) algorithm for power loss reduction. …”
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Predictive Maintenance Algorithms, Artificial Intelligence Digital Twin Technologies, and Internet of Robotic Things in Big Data-Driven Industry 4.0 Manufacturing Systems by Marek Nagy, Marcel Figura, Katarina Valaskova, George Lăzăroiu

“…In Industry 4.0, predictive maintenance (PdM) is key to optimising production processes. …”
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Enhanced data-driven shear strength predictive modeling framework for RCDBs using explainable boosting-based ensemble learning algorithms coupled with Bayesian optimization by Imad Shakir Abbood, Noorhazlinda Abd Rahman, B.H. Abu Bakar

“…Despite over 70 years of investigation into the behavior of reinforced concrete deep beams (RCDBs), it remains challenging to accurately predict their shear strength (SS) due to the underlying intricate mechanism. …”
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Research on Simplified Design of Model Predictive Control by Qing Zhang, Chi Zhang, Qi Wang, Shiyun Dong, Aoqi Xiao

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Fuzzy Model Predictive Control for Unmanned Helicopter by Łukasz Kiciński, Sebastian Topczewski

“…The proposed solution involves the use of the Model Predictive Control framework enhanced with the Takagi–Sugeno inference algorithm. …”
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How can we predict transportation stock prices using artificial intelligence? Findings from experiments with Long Short-Term Memory based algorithms by Dinar Ajeng Kristiyanti, Willibrordus Bayu Nova Pramudya, Samuel Ady Sanjaya

“…It employs the Long Short-Term Memory (LSTM) algorithm, assessing different hyperparameter activation functions (linear, ReLU, sigmoid, tanh) and optimizers (ADAM, ADAGRAD, NADAM, RMSPROP, ADADELTA, SGD, ADAMAX) to refine prediction accuracy. …”
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Heuristic Binary Search for Modulated Predictive Control by Rafael FIgueiredo, Igor Oliani, Angelo Lunardi, Alfeu J. Sguarezi Filho

“…Predictive Control optimization often relies on exhaustive enumeration of voltage vectors within the finite control set. …”
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<strong>Hybrid neural network with genetic algorithms for predicting distribution pattern of <em>Tetranychus urticae</em> (Acari: Tetranychidae) in cucumbers field of Ramhormoz, Iran</strong> by Alireza Shabaninejad, Bahram Tafaghodinia, Nooshin Zandi Sohani

“…Purpose of this research is to predict and map the distribution of Tetranychus urticae Koch (Acari: Tetranychidae) using MLP neural networks combined with genetic algorithm in surface of farm. …”
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Enhanced permeability prediction in porous media using particle swarm optimization with multi-source integration by Zhiping Chen, Jia Zhang, Daren Zhang, Xiaolin Chang, Wei Zhou

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Enhanced probabilistic prediction of pavement deterioration using Bayesian neural networks and cuckoo search optimization by Feng Xiao, Biying Shi, Jie Gao, Huapeng Chen, Di Yang

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Research on Lithium-Ion Battery State of Health Prediction Based on XGBoost–ARIMA Joint Optimization by Chen Fei, Zhuo Lu, Weiwei Jiang, Liang Zhao, Fan Zhang

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Emergency Resource Dispatch Scheme for Ice Disasters Based on Pre-Disaster Prediction and Dynamic Scheduling by Runyi Pi, Yuxuan Liu, Nuoxi Huang, Jianyu Lian, Xin Chen, Chao Yang

“…To address the challenge of dispatching emergency resources for community residents under extreme ice disaster, this paper proposes an emergency resource dispatch strategy based on pre-disaster prediction and dynamic scheduling. First, the fast Newman algorithm is employed to cluster communities, optimizing the preprocessing of resource scheduling and reducing scheduling costs. …”
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Multi-step Prediction of Monthly Sediment Concentration Based on WPT-ARO-DBN/WPT-EPO-DBN Model by GAO Xuemei, CUI Dongwen

Subjects: “…prediction of monthly sediment concentration…”
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Early Fault Diagnosis and Prediction of Marine Large-Capacity Batteries Based on Real Data by Yifan Liu, Huabiao Jin, Xiangguo Yang, Telu Tang, Qijia Song, Yuelin Chen, Lin Liu, Shoude Jiang

“…Therefore, timely fault diagnosis and accurate fault prediction are crucial for the safe operation of ships. …”
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