Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement by D. Neudecker, T. E. Cutler, M. Devlin, P. Brain, N. Gibson, M. J. Grosskopf, M. W. Herman, J. Hutchinson, T. Kawano, A. Khatiwada, N. Kleedtke, E. Leal-Cidoncha, R. C. Little, A. E. Lovell, A. Stamatopoulos, E. C. Thompson, S. A. Vander Wiel, E. Williamson

“…In this field, fundamental-physics driven data, called differential, look at one nuclear physics observable at a time. …”
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Intelligent Optimized Combined Model Based on GARCH and SVM for Forecasting Electricity Price of New South Wales, Australia by Yi Yang, Yao Dong, Yanhua Chen, Caihong Li

“…However, the fluctuation of electricity price depends on other commodities and there is a very complicated randomization in its evolution process. Therefore, in recent years, although large number of forecasting methods have been proposed and researched in this domain, it is very difficult to forecast electricity price with only one traditional model for different behaviors of electricity price. …”
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Application of Heuristic Methods for Polymer Synthesis Process Optimization by Eldar Miftakhov, Svetlana Mustafina, Andrey Akimov

“…A numerical algorithm has been developed for solving the problem of finding optimal conditions for the synthesis of polymers using heuristic optimization methods, and its effectiveness has been evaluated in the investigation of the copolymerization process of butadiene with styrene, proceeding via a free-radical mechanism. …”
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Introducing Iterative Model Calibration (IMC) v1.0: a generalizable framework for numerical model calibration with a CAESAR-Lisflood case study by C. Banerjee, K. Nguyen, C. Fookes, G. Hancock, T. Coulthard

“…Moreover, the utility of machine-learning-based and data-driven approaches is curtailed by the requirement for the numerical model to be differentiable for optimization purposes, which challenges their generalizability across different models. …”
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Jump around: Selecting Markov Chain Monte Carlo parameters and diagnostics for improved food web model quality and ecosystem representation by Gemma Gerber, Ursula M. Scharler

“…Therefore, we used several established MCMC convergence diagnostics to (1) quantify how algorithm parameters affect ensemble flow values and if these differences propagate to ecological indicators and (2) evaluate algorithm quality and compare to current evaluation and ecosystem modelling methods. …”
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A numerical framework for simulating fluid-structure interaction phenomena by A. De Rosis, S. de Miranda, C. Burrafato, F. Ubertini

“…The Immersed Boundary method is used to account for the presence of an immersed solid in the lattice fluid background and to handle fluid-structure interface conditions, while a Volume-of-Fluid-based method is adopted to take trace of the evolution of the free surface. These ingredients are combined through a partitioned staggered explicit strategy, according to an efficient and accurate algorithm recently developed by the authors. …”
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Stochastic Production Planning with Regime-Switching: Sensitivity Analysis, Optimal Control, and Numerical Implementation by Dragos-Patru Covei

“…The production and inventory cost optimization problem is formulated as a quadratic cost functional, with the solution characterized by a regime-dependent system of elliptic partial differential equations (PDEs). Numerical solutions to the PDE system are computed using a monotone iteration algorithm, enabling quantitative analysis. …”
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Robotic Hand–Eye Calibration Method Using Arbitrary Targets Based on Refined Two-Step Registration by Zining Song, Chenglong Sun, Yunquan Sun, Lizhe Qi

“…To optimize the structure and workflow of the 3D measurement robot system, reduce the dependence on specific calibration targets or high-precision calibration objects, and improve the versatility of the system’s self-calibration, this paper proposes a robot hand–eye calibration algorithm based on irregular targets. By collecting the 3D structural information of an object in space at different positions, a random sampling consistency evaluation based on the fast point feature histogram (FPFH) is adopted, and the iterative closest point (ICP) registration algorithm with the introduction of a probability model and covariance optimization is combined to iteratively solve the spatial relationship between point clouds, and the hand–eye calibration equation group is constructed through spatial relationship analysis to solve the camera’s hand–eye matrix. …”
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Smart Odour Sensing for Automated Monitoring of Bread Products by Carmen Bax, Bianca di Diodoro, Alessandro Ticozzi, Nicolò Dellarosa, Flavio Corazza, Giacomo Langfelder, Laura Capelli

“…This work proposes an electronic nose (e-nose) system based on resistive gas sensors to predict the cooking evolution of different types of bread. The e-nose includes six metal-oxide semiconductor (MOS) gas sensors, a low-noise electronic system for signal conditioning and data acquisition, and a classification algorithm for real-time detection of the cooking stage. …”
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The analysis of rural revitalization serviceplatform in smart city under back propagation neural network. by Gongyi Jiang, Weijun Gao, Meng Xu, Mingjia Tong

“…Additionally, the Grey Relation Analysis (GRA) algorithm is used to classify rural revitalization efforts across different cities. …”
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The Significance of MAPK Signaling Pathway in the Diagnosis and Subtype Classification of Intervertebral Disc Degeneration by Yong Liu, Xueyan Chen, Jingwen Chen, Chao Song, Zhangchao Wei, Zongchao Liu, Fei Liu

“…Additionally, we applied PPI networks, LASSO analysis, the RF algorithm, and the SVM‐RFE algorithm to identify core MAPK‐related genes. …”
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Exploring nanoparticle dynamics in binary chemical reactions within magnetized porous media: a computational analysis by Saleem Nasir, Abdallah Berrouk, Asim Aamir

“…The present work investigates the applicability of back-propagation artificial neural networks in conjunction with the Levenberg-Marquardt algorithm for evaluating heat transmission in hybrid nanofluids. …”
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Research on Management Model Based on Deep Learning by Yuting Zhao

“…Different opportunities and different organizations are offered by different management models. …”
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The Macroalgae Ecological Quality Index (MEQI) in the Basin of Mexico: a proposal of aquatic bioindicators for peri-urban rivers by Javier Carmona-Jiménez, Victor Hugo Salinas-Camarillo, Angela Caro-Borrero

“…The proposal included three steps: i) characterization of trophic level and hydromorphological quality (HQ) in 49 sites collected between 2012 and 2016 with different conservation degrees; ii) calculation of the indicator value of 20 taxa and the algorithm proposal; and iii) validation of the algorithm in 26 new sites and its correlation with water quality and HQ. …”
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Self-Optimization of Coverage and Capacity in LTE Networks Based on Central Control and Decentralized Fuzzy Q-Learning by Jingyu Li, Jie Zeng, Xin Su, Wei Luo, Jing Wang

“…This paper proposes a central control mechanism that utilizes the fuzzy Q-learning algorithm in a decentralized fashion for this task. …”
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QoS-Aware Fault Detection in Wireless Sensor Networks by Alessandra De Paola, Giuseppe Lo Re, Fabrizio Milazzo, Marco Ortolani

“…Our approach has been tested on a synthetic dataset in order to evaluate its behavior with respect to different values of QoS constraints. …”
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Finding near-optimal groups of epidemic spreaders in a complex network. by Geoffrey Moores, Paulo Shakarian, Brian Macdonald, Nicholas Howard

“…We perform an experimental evaluation on samples from several different network structures which demonstrate that our algorithm maximizes combinatorial local centrality and consistently chooses the most effective set of nodes to spread infection under the SIR model, relative to selecting the top nodes using many common centrality measures. …”
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A prior information-based multi-population multi-objective optimization for estimating 18F-FDG PET/CT pharmacokinetics of hepatocellular carcinoma by Yiwei Xiong, Siming Li, Jianfeng He, Shaobo Wang

“…The single-individual Levenberg–Marquardt (LM) algorithm, single-population algorithms (Particle Swarm Optimization (PSO), Differential Evolution (DE), and Genetic Algorithm (GA)) and p-MPMO optimization algorithms (p-MPMOPSO, p-MPMODE, and p-MPMOGA) were used to estimate the parameters. …”
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Self-Adjusting Look-Ahead Distance of Precision Path Tracking for High-Clearance Sprayers in Field Navigation by Xu Wang, Bo Zhang, Xintong Du, Huailin Chen, Tianwen Zhu, Chundu Wu

“…By developing a kinematic model of the pure pursuit algorithm for agricultural machinery, an evaluation function is then employed to estimate the pose of the machinery and identify the corresponding optimal look-ahead distance within the designated area. …”
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Compensation for vibration signal power variance when changing equipment speed mode by D. A. Kechik

“…Vibration power dependencies on the main shaft speed have been estimated in different frequency ranges. The paper proposes an algorithm compensating variations of instantaneous power of vibration signal where equipment operation speed varies. …”
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