Safety Status Prediction Model of Transmission Tower Based on Improved Coati Optimization-Based Support Vector Machine by Xinxi Gong, Yaozhong Zhu, Yanhai Wang, Enyang Li, Yuhao Zhang, Zilong Zhang

“…Subsequently, we employ the improved coati optimization algorithm (ICOA) to refine the penalty parameters and kernel function of the support vector machine (SVM), thereby developing the safety state prediction model for the transmission tower. …”
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Domain general noise reduction for time series signals with Noisereduce by Tim Sainburg, Asaf Zorea

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Rough decision rules extraction and reduction based on granular computing by Hong-can YAN, Feng ZHANG, Bao-xiang LIU

“…Rule mining was an important research content of data mining,and it was also a hot research topic in the fields of decision support system,artificial intelligence,recommendation system,etc,where attribute reduction and minimal rule set extraction were the key links.Most importantly,the efficiency of extraction was determined by its application.The rough set model and granular computing theory were applied to the decision rule reduction.The decision table was granulated by granulation function,the grain of membership and the concept granular set construction algorithm gener-ated the initial concept granular set.Therefore,attribute reduction could be realized by the distinguish operator of concept granule,and decision rules extraction could be achieved by visualization of concept granule lattice.Experimental result shows that the method is easier to be applied to computer programming and it is more efficient and practical than the existing methods.…”
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Efficient colour filter array demosaicking with prior error reduction by M.S. Safna Asiq, WR Sam Emmanuel

“…The proposed work introduces an error efficient demosaicking algorithm. The efficient prior error reduction technique helps to obtain better results. …”
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Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm. by Xiaotong Bai, Yuefeng Zheng, Yang Lu, Yongtao Shi

“…Three sets of comparison experiments were conducted to demonstrate the superiority of this algorithm over the others. The experimental results show that the average classification accuracy of the TMKMCRIGWO algorithm is at least 0.1% higher than the other algorithms on 20 datasets, and the average value of the dimension reduction rate (DRR) reaches 24.76%. …”
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Edge Server Placement and Task Allocation for Maximum Delay Reduction by Koki Shibata, Sumiko Miyata

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Pressure Control in the Pump-Controlled Hydraulic Die Cushion Pressure-Building Phase Using Enhanced Model Predictive Control with Extended State Observer-Genetic Algorithm Optimization by Zhikui Dong, Song He, Yi Liao, Heng Wang, Mingxing Song, Jinpei Jiang, Gexin Chen

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Reduction of electric energy consumption for heating passenger railway carriages by A. А. Kuznetsov, S. S. Gorobei

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Intelligent Data Reduction for IoT: A Context-Driven Framework by Laercio Pioli, Douglas D. J. De Macedo, Daniel G. Costa, Mario A. R. Dantas

“…With these predictions based on existing datasets, a selector algorithm module is adopted to identify the most suitable data reduction approach for specific IoT applications. …”
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Residual-conditioned sparse transformer for photoacoustic image artifact reduction by Xiaoxue Wang, Jinzhuang Xu, Chenglong Zhang, Moritz Wildgruber, Wenjing Jiang, Lili Wang, Xiaopeng Ma

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Surfactants Adsorption onto Algerian Rock Reservoir for Enhanced Oil Recovery Applications: Prediction and Optimization Using Design of Experiments, Artificial Neural Networks, and Genetic Algorithm (GA) by Kahina Imene Benramdane, Mohamed El Moundhir Hadji, Mohamed Khodja, Nadjib Drouiche, Bruno Grassl, Seif El Islam Lebouachera

“…Before training, 32 different ANN configurations were evaluated by varying learning algorithms, adaptation functions, and transfer functions. …”
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A Novel Grey Prediction Model: A Hybrid Approach Based on Extension of the Fractional Order Discrete Grey Power Model with the Polynomial-Driven and PSO-GWO Algorithm by Baohua Yang, Xiangyu Zeng, Jinshuai Zhao

“…Background: This study addresses the challenge of predicting data sequences characterized by a mix of partial linearity and partial nonlinearity. …”
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Development and validation of a predictive nomogram for bilateral posterior condylar displacement using cone-beam computed tomography and machine-learning algorithms: a retrospective observational study by Huachao Sui, Mo Xiao, Xueqing Jiang, Jiaye Li, Feng Qiao, Bin Yin, Yuanyuan Wang, Ligeng Wu

“…Therefore, in this study, we aimed to develop and evaluate a predictive model for bilateral posterior condylar displacement. …”
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A Unmanned Aerial Vehicle-Based Image Information Acquisition Technique for the Middle and Lower Sections of Rice Plants and a Predictive Algorithm Model for Pest and Disease Detection by Xiaoyan Guo, Yuanzhen Ou, Konghong Deng, Xiaolong Fan, Ruitao Gao, Zhiyan Zhou

“…Aiming at the technical bottleneck of monitoring rice stalk, pest, and grass damage in the middle and lower parts of rice, this paper proposes a UAV-based image information acquisition method and disease prediction algorithm model, which provides an efficient and low-cost solution for the accurate early monitoring of rice diseases, and helps improve the scientific and intelligent level of agricultural disease prevention and control. …”
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Annotation-free deep learning algorithm trained on hematoxylin & eosin images predicts epithelial-to-mesenchymal transition phenotype and endocrine response in estrogen receptor-positive breast cancer by Kaimin Hu, Yinan Wu, Yajing Huang, Meiqi Zhou, Yanyan Wang, Xingru Huang

“…Our classifier achieved a predicting accuracy of 81.25%, and 88.7% slides labeled as endocrine resistant were predicted as the mesenchymal-phenotype, while 75.6% slides labeled as sensitive were predicted as the epithelial-phenotype. …”
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Modeling of Energy Management System for Fully Autonomous Vessels with Hybrid Renewable Energy Systems Using Nonlinear Model Predictive Control via Grey Wolf Optimization Algorithm by Harriet Laryea, Andrea Schiffauerova

“…The EMS combines nonlinear model predictive control (NMPC) with metaheuristic optimizers—Grey Wolf Optimization (GWO) and Genetic Algorithm (GA)—and is benchmarked against a conventional rule-based (RB) method. …”
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Validation of an artificial intelligence-based algorithm for predictive performance and risk stratification of sepsis using real-world data from hospitalised patients: a prospective observational study by Ji-Hyun Kim, Chi-Heum Cho, In-Cheol Kim, Kwang Joon Kim, KyungHyun Lee, Eun Yeong Ha, Sun Hyo Park, Gyeong Im Yu, Byung Eun Ahn, Yeeun Jeong, Joo-Yun Won, Taeyong Sim, Hochan Cho, Ki-Byung Lee

“…VitalCare-SEPsis Score (VC-SEPS) is a deep learning-based algorithm that predicts sepsis and monitors patient conditions based on electronic medical record data. …”
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Model-Order Reduction of Multistage Cascaded Models for Digital Predistortion by Raul Criado, Wantao Li, William Thompson, Gabriel Montoro, Kevin Chuang, Pere L. Gilabert

“…To reduce the computational complexity of these multistage CC behavioral models, a model-order reduction technique based on a greedy algorithm is proposed. …”
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A Dynamic Neural Network Optimization Model for Heavy Metal Content Prediction in Farmland Soil by Kun Cao, Cong Zhang, Liangliang Li, Shuaifeng Li

Subjects: “…soil heavy metal content prediction…”
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Practical Application of Complementary Regulation Strategy of Run-of-River Small Hydropower and Distributed Photovoltaic Based on Multi-Scale Copula-MPC Algorithm by Xianpin Zhu, Weibo Li, Shuai Cao, Wei Xu

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