Forecasting financial time series using a low complexity recurrent neural network and evolutionary learning approach by Ajit Kumar Rout, P.K. Dash, Rajashree Dash, Ranjeeta Bisoi

“…Further several evolutionary learning methods like the Particle Swarm Optimization (PSO) and modified version of its new variant (HMRPSO), and the Differential Evolution (DE) are adopted here to find the optimal weights for the recurrent computationally efficient functional link neural network (RCEFLANN) using a combination of linear and hyperbolic tangent basis functions. …”
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Driver Clustering Based on Individual Curve Path Selection Preference by Gergo Igneczi, Tamas Dobay, Erno Horvath, Krisztian Nyilas

“…However, human drivers often deviate from the center line. It has been shown that the driver’s choice to deviate from the center line can be modeled by a linear combination of preview curvature information. …”
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Adaptive neighbourhood for locally and globally tuned biogeography based optimization algorithm by Parimal Kumar Giri, Sagar S. De, Satchidananda Dehuri

“…Biogeography Based Optimization (BBO) is a population based metaheuristic algorithm using the idea of migration and mutation operation of species for solving complex optimization problems. BBO has demonstrated good performance on various unconstrained and constrained benchmark functions. …”
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NONLINEAR NYBERG CONSTRUCTION TRANSFORMS OVER ISOMORPHIC REPRESENTATIONS OF FIELDS GALOIS by A. V. Sokolov, O. N. Zhdanov

“…As a criterion of nonlinearity, we measure the distances from the component many-valued functions to the set of Vilenkin–Chrestenson functions that are considered to be the most linear. …”
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Fragmentation of Modern Artistic Narrative (English-Language Prose) by G. I. Lushnikova, T. Yu. Osadchaya

“…The novelty of the research is seen in the fact that the fragmentation of a literary text is studied at different levels — compositional, content-thematic, plot, ideological-figurative, genre, narrative, chronotopic. It has been proved that the forms of implementation of fragmentariness are quite diverse: irregular division of the text, heterogeneity of themes and ideas, lack of linear development of the plot, combination of elements of different genres, the presence of internal polystylism, the use of different types of narration and narrator, violation of the unity of the chronotope. …”
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Reverse convection potential saturation during northward IMF by V. Wilder, C. R. Clauer, J. B. H. Baker

“…Results show that the reverse convection cells do, in fact, exhibit non‐linear saturation behavior. The saturation potential is approximately 20 kV and is achieved when the electric coupling function reaches between 18 and 30 kV/RE.…”
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THE PREDICTION OF ENTERPRISES ACTIVITY INDICATORS TAKING INTO ACCOUNT THE INITIAL DATA UNCERTAINTY by Yu. Gagarin, S. Gagarina

“…To obtain point and interval estimates of the parameters of mathematical models that take into account errors in the values of the function and argument, the use methods of confluent analysis has been proposed. …”
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Sliding Mode Control of the Vehicle Speed System Based on LMIs by Hong-Liang Gao, Hong-Cong Zhang, Xiao-Ling Li

“…A sliding mode control method of the nonlinear system state observation based on linear matrix inequalities (LMIs) is proposed. In the proposed control method, Lyapunov function is used as the control function to track the position and speed of the vehicle speed system in real time. …”
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Robust Nonfragile H∞ Control of Lateral Semiactive Suspension of Rail Vehicles by Jianjun Meng, Ruxun Xu, Decang Li

“…Then the H∞ norm was used to reflect riding comfort; the sufficient conditions for the existence of robust nonfragile H∞ control were developed based on linear matrix inequality (LMI) approach. The design of a robust nonfragile H∞ control with gain perturbation was changed into an optimization issue with linear inequality constraint and a linear objective function. …”
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The use of shadow prices in capital rationing problem by B BAALOUDJ

“…This method of transferring funds has two advantages, an increase in the objective function without using external resources. …”
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Praca sprężystych skręcanych ortotropowych powłok walcowych po utracie stateczności by Tadeusz GALKIEWICZ

“…The shape of the bending function is assumed to be for the linear problem of the form of (3.1) and for the nonlinear problem of the form of (3.2). …”
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A GPR-Based Test Study on the Influencing Factors of the Dielectric Constant of Cement-Stabilized Macadam Bases by Xue Han, Shifei Cao, Hanhui He

“…There is a good logarithmic correlation between the dielectric constant and the compaction degree of CSMB, and quantitative functions have been established. There is a good linear relationship between the dielectric constant and the unconfined compressive strength of CSMB, and quantitative functions have been established. …”
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NMR Spectroscopy Study of the Effect of the Molecular Mass of Hypromellose Phthalate on Its Solubility by S. V. Moiseev, N. E. Kuz’mina, E. Yu. Severinova, N. D. Bunyatyan, V. A. Evteev

“…The dissolution profile of the test samples in an aqueous buffer solution (pH 5.59) was described by a linear function during the first hour. The slope characterising the dissolution rate varied from 10° to 36°.Conclusions. …”
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BREAST-RANKNet: a fuzzy rank-based ensemble of CNNs with residual learning for enhanced breast cancer detection from ultrasound and mammogram images by Sohaib Asif, Lingying Zhu, Dane Yan, Luman Xu, Zhengqiu Huang, Haimin Xu, Ruxuan Yan, Linghong Cai, Changfu Zheng, Jiamei Lin, Enyu Wang

“…Furthermore, we extract probabilities from these models and aggregate them using fuzzy rank-based fusion strategy, utilize three non-linear functions: an exponentially decaying function $$\left( {exp} \right)$$ exp , the $$tanh$$ tanh function, and the $$sigmoid$$ sigmoid function, allowing for adaptive integration based on model confidence. …”
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Numerical Solution of Problem for Non-Stationary Heat Conduction in Multi-Layer Bodies by R. I. Esman, V. A. Ustimovich

“…A mathematical model for non-stationary heat conduction of multi-layer bodies has been developed. Dirac’s δ-function is used to take into account phase and chemical transformations in one of the wall layers. …”
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Tracking and Disturbance Suppression of the Radio Telescope Servo System Based on the Equivalent-Input-Disturbance Approach by Lei Yang, Na Wang, Zhiyong Liu, Ning Li

“…Considering the nonminimum phase characteristics of the radio telescope system, the state observer gain is computed using the linear matrix inequality (LMI) method. The system stability is analyzed using the small gain theorem, and the linear quadratic regulator (LQR) control method is utilized to determine the state feedback gain. …”
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Exploring the Potential and Advancements of Circular RNA Therapeutics by Lei Wang, Lianqing Wang, Chunbo Dong, Jialong Liu, Guoxin Cui, Shan Gao, Zhida Liu

“…ABSTRACT Messenger RNA (mRNA) technology is revolutionizing the pharmaceutical industry owing to its superior safety profile, manufacturing capabilities, and potential applications in previously undruggable therapeutic targets. In addition to linear mRNA, such as conventional mRNA, self‐amplifying mRNA, and trans‐amplifying mRNA, circular mRNA has emerged as a promising candidate. …”
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Effect of doped wax on the rheological properties and chemical structure of ultraviolet aged bitumen by Mingyuan Chen, Jiuguang Geng, Leilei He, Huaxin Chen, Yongju Hu

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Semi-analytical solution of cohesive zone model for cement-based materials by Yong-Kang Hou, Shu-Jin Duan, Rui-Mei An, Xin-Yue Wang

“…This study used the boundary collocation method to obtain the linear elastic solution of stress function that satisfies the boundary conditions, on the basis of the Williams stress function. …”
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Prospects of application of artificial neural networks for forecasting of cargo transportation volume in transport systems by D. T. Yakupov, O. N. Rozhko

“…The neural network model consists of a hidden layer of neurons with a sigmoidal activation function and an output neuron with a linear activation function, the input values of the dynamic time series, and the predicted value is removed from the output. …”
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