Multiclass Sparse Bayesian Regression for fMRI-Based Prediction by Vincent Michel, Evelyn Eger, Christine Keribin, Bertrand Thirion

“…We detail these framework and validate our algorithm on simulated and real neuroimaging data sets, showing that it performs better than reference methods while yielding interpretable clusters of features.…”
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A data-driven, cloud-based approach for forest aboveground biomass mapping using GEDI and other earth observation data: an ecoregion-specific Investigation across the state of Alab... by Janaki Sandamali, Lana L. Narine

“…GEDI data preparation was performed locally, while the analysis was conducted within GEE using the Random Forest algorithm. …”
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Using artificial intelligence techniques and econometrics model for crypto-price prediction by Abhidha Verma, Jeewesh Jha

“…To achieve accurate predictions for Ethereum's price one day ahead, we develop a hybrid algorithm combining Genetic Algorithms (GA) and Artificial Neural Networks (ANN). …”
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Trajectory Planning for Point-to-Point Motion Using High-order Polynomials by Hossein Barghi Jond, Vasif V. Nabiyev, TuÄrul Ãavdar

“…Additionally, comparing outputs of Genetic Algorithm with the closed-form solutions for the problem show that closed-form expressions generate coefficients that are near optimal.…”
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An Iterative Error Correction Procedure for Single Sheet Testers Using FEM 3D Model by Robert Krobot, Martin Dadić

“…The proposed iterative correction procedure is based on the steepest descent algorithm, while the stopping criteria were based on the difference between simulated and measured global variables (power loss, induced voltage, and primary current). …”
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Consensus control of multiple electric springs considering non-critical load electricity fairness in islanded microgrid by Fagen Yin, Chun Wang

“…This strategy ensures the reactive power output ratio of each ES is equal and that there is consistency in the voltage deviation ratio of each NCL while achieving nodes voltage and system frequency stability.…”
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<i>Apis mellifera</i> Bee Verification with IoT and Graph Neural Network by Apolinar Velarde Martínez, Gilberto González Rodríguez, Juan Carlos Estrada Cabral

“…Two object-recognition techniques, namely the k-Nearest Neighbor Algorithm (kNN) and Graph Neural Network (GNN), were evaluated with an image dataset of 600 images from a single beehive. …”
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Cooperative trajectory optimization for multiple connected vehicles at an unsignalized intersection by Hao Yang, Xianyang Li, Duoyang Qiu, Xiaomeng Zhu

“…Through numerical simulation analysis of intersection scenarios including crossroad and roundabout, the results demonstrate that the proposed algorithm can achieve optimal trajectories for multi-vehicle cooperative motion while ensuring safe vehicle operation, which improves the efficiency of future intelligent traffic networks.…”
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Error-Constrained Fixed-Time Synchronized Trajectory Tracking Control for Unmanned Airships with Disturbances by Jie Chen, Jiace Yuan, Ruohan Li

“…First, to guarantee strict adherence to prescribed performance bounds, an error transformation function (ETF) is integrated into the control algorithm, which can ensure all tracking errors remain within specified constraints throughout the convergence process. …”
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Optimizing alternate replacement strategy of k-out-of-n: F systems with common-mode degradation: An application to railway grid. by Liying Wang, Mingjie Ding, Boshi Liu, Qingan Qiu

“…The degradation of each steel rail is modeled using a Gamma process, while the dependence structure of the system is characterized through a copula function. …”
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Cooperative Optimization Analysis of Variable-Speed and Fixed-Speed Pumped-Storage Units Under Large Disturbances in the Power System by Weidong Chen, Jianyuan Xu

“…From a multi-time-scale perspective, we first investigate the fast power support control strategy of variable-speed pumped-storage (VSPS) units during new energy cluster off-grid scenarios. Using a consensus algorithm, the VSPS acts as the primary unit, while the constant-speed unit provides long-term power support. …”
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Constructing Fair Destination-Oriented Directed Acyclic Graphs for Multipath Routing by Katarzyna Kalinowska-Górska, Fernando Solano Donado

“…Some of these techniques make use of the so-called Destination-Oriented Directed Acyclic Graphs (DODAGs) which are constructed on the networks, usually in a distributed way. However, while defining methods of forming DODAGs, the authors of multipath algorithms tend to overlook a possibly significant issue which could, in a way, define the quality of a given DODAG in the context of multipath routing, namely, providing an equitable distribution of the paths between the nodes in the newly created DODAG. …”
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Modification of Multilayer Perceptron Using Detection Rate Model for Prediction of Nominal Exchange Rate by Al-Khowarizmi Al-Khowarizmi, Romi Fadillah Rahmat, Michael J Watts, Akrim Akrim, Arif Ridho Lubis, Muhammad Basri

“…The results obtained with absolute error achieve an accuracy of 99.73% while the accuracy based on the detection rate achieves an accuracy of 99.49%. this can be seen in the case of the prediction of (Indonesian Rupiah) IDR exchange rate against United State Dollar (USD) with the MLP algorithm by testing using MAPE to achieve sensitivity with absolute error. …”
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Self-Adaptive MOEA Feature Selection for Classification of Bankruptcy Prediction Data by A. Gaspar-Cunha, G. Recio, L. Costa, C. Estébanez

“…The proposed methodology makes use of self-adaptation by applying the feature selection algorithm while simultaneously optimising the parameters of the classifier used. …”
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A Novel Flexible Model for the Extraction of Features from Brain Signals in the Time-Frequency Domain by R. Heideklang, G. Ivanova

“…Electrophysiological signals such as the EEG, MEG, or LFPs have been extensively studied over the last decades, and elaborate signal processing algorithms have been developed for their analysis. Many of these methods are based on time-frequency decomposition to account for the signals’ spectral properties while maintaining their temporal dynamics. …”
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A Coverage Hole Healing Strategy with Awareness of Data Delivery Time in Wireless Sensor Networks by Fu-Tian Lin, Tien-Wen Sung, Chu-Sing Yang

“…In this work, the proposed hole healing strategy aims to shorten the delivery hop count by a dynamic hole healing process in order to improve the data delivery time while maintaining the coverage ratio and topology connectivity. …”
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Illustration image style transfer method design based on improved cyclic consistent adversarial network. by Xiaojun Wang, Jing Jiang

“…Through a series of quantitative and qualitative experiments, high-quality style transfer is achieved, especially while retaining the original features of the illustration. …”
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A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks. by Inés P Mariño, Alexey Zaikin, Joaquín Míguez

“…The schemes we assess are the particle Metropolis-Hastings (PMH) algorithm, the nonlinear population Monte Carlo (NPMC) method and the approximate Bayesian computation sequential Monte Carlo (ABC-SMC) scheme. …”
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Fast Nonparametric Inference of Network Backbones for Weighted Graph Sparsification by Alec Kirkley

“…We then construct an efficient and provably optimal greedy algorithm to identify the backbone minimizing our objectives, whose run-time complexity is log-linear in the number of edges. …”
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RIM-Net: A Real-Imaginary-Magnitude Network for NLOS/LOS Identification in UWB Indoor Positioning Systems by Jiacheng Ni, Fang Li, Shuai Cao, Linsong Li

“…Furthermore, the optimization of the TOA algorithm validated the effectiveness of RIM-Net in localization, achieving an average performance improvement of 9.66%. …”
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