Polynomial model

In this study, our primary aim is to assess and compare the efficacy of Support Vector Machines (SVM) employing various kernel functions: linear (LIN), polynomial (POL), Radial Basis Function (RBF), and sigmoid (SIG) in predicting the compressive strength of concrete.

14p viengfa 28-10-2024 1 1   Download

The study is a complement to the studies of the tensile strength of cement paste backfill gradually becoming complete. Evaluate the reliability of the proposed model and analyze the influence of the components on the tensile strength. At the same time, the study is also interested in the influence of the components.

9p viengfa 28-10-2024 3 1   Download

In this study, the extraction of chlorogenic acid from Vietnamese green coffee beans was optimized using the response surface methodology. A second-order polynomial model with three important variables (liquid-to-solid ratio, temperature, and extraction time) was used.

11p vibecca 01-10-2024 1 1   Download

Acoustic properties of foams, such as macroscopic transports and sound absorption, are significantly influenced by their local morphology. The present paper develops a polynomial chaos expansion (PCE)-based surrogate model for characterizing the microstructure-properties relationships of acoustic monodisperse foams.

14p vifilm 24-09-2024 2 1   Download

Model Predictive Control (MPC) refers to a class of algorithms that optimize the future behavior of the plant subject to operational constraints. The merits of the class algorithms include its ability to handle imposed hard constraints on the system and perform on-line optimization. This thesis investigates design and implementation of continuous time model predictive control using Laguerre polynomials and extends the design approaches proposed in to include intermittent predictive control, as well as to include the case of the nonlinear predictive control.

162p runthenight07 01-03-2023 9 4   Download

This paper proposes a servo controller design and fault detection algorithm for speed control of conveyor system (CS). Firstly, modeling for a CS is described. Secondly, the robust servo controller based on polynomial differential operator is applied to track the trapezoidal velocity profile reference input. Thirdly, a fault detection algorithm based on Extended Kalman Filter (EKF) is proposed.

5p sotritu 18-09-2021 30 2   Download

This paper presents a new hybrid double mixed stress (4f-HMS) model, for the static analysis of isotropic plane structures, in which it is assumed a physically and geometrically linear behaviour.

22p tohitohi 19-05-2020 14 0   Download

(BQ) The study sheds light on the powerful learning capability of ANFIS models and its superiority over the conventional polynomial models in terms of modelling complex non-linear machining processes

15p xuanphuongdhts 27-03-2017 41 2   Download

This is the second of two papers in which we prove the Tits alternative for Out(Fn ). Contents 1. Introduction and outline 2. Fn -trees 2.1. Real trees 2.2. Real Fn -trees 2.3. Very small trees 2.4. Spaces of real Fn -trees 2.5. Bounded cancellation constants 2.6. Real graphs 2.7. Models and normal forms for simplicial Fn -trees 2.8. Free factor systems 3. Unipotent polynomially growing outer automorphisms 3.1. Unipotent linear maps 3.2. Topological representatives 3.3. Relative train tracks and automorphisms of polynomial growth 3.4. Unipotent representatives and UPG automorphisms ...

60p noel_noel 17-01-2013 44 5   Download

This paper deals with some questions about the dynamics of diffeomorphisms of R2 . A “model family” which has played a significant historical role in dynamical systems and served as a focus for a great deal of research is the family introduced by H´non, which may be written as e fa,b (x, y) = (a − by − x2 , x) b = 0.

27p tuanloccuoi 04-01-2013 42 6   Download

Tuyển tập các báo cáo nghiên cứu khoa học về toán học trên tạp chí toán học quốc tế đề tài: Tutte polynomial, subgraphs, orientations and sandpile model: new connections via embeddings...

53p thulanh6 17-09-2011 49 3   Download

condense and summarize the data by fitting it to a “model” that depends on adjustable parameters. Sometimes the model is simply a convenient class of functions, such as polynomials or Gaussians, and the fit supplies the appropriate coefficients.

2p babyuni 17-08-2010 65 3   Download