CN112765802B - Method for evolving water wave waveform based on high-order water wave model - Google Patents

Method for evolving water wave waveform based on high-order water wave model Download PDF

Info

Publication number
CN112765802B
CN112765802B CN202110039498.2A CN202110039498A CN112765802B CN 112765802 B CN112765802 B CN 112765802B CN 202110039498 A CN202110039498 A CN 202110039498A CN 112765802 B CN112765802 B CN 112765802B
Authority
CN
China
Prior art keywords
water wave
wave
model
order
respect
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202110039498.2A
Other languages
Chinese (zh)
Other versions
CN112765802A (en
Inventor
姚若侠
赵琦
李岩
艾力米努尔·库尔班
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shaanxi Normal University
Original Assignee
Shaanxi Normal University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shaanxi Normal University filed Critical Shaanxi Normal University
Priority to CN202110039498.2A priority Critical patent/CN112765802B/en
Publication of CN112765802A publication Critical patent/CN112765802A/en
Application granted granted Critical
Publication of CN112765802B publication Critical patent/CN112765802B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00Details relating to the application field
    • G06F2113/08Fluids

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • Evolutionary Computation (AREA)
  • Geometry (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Aerodynamic Tests, Hydrodynamic Tests, Wind Tunnels, And Water Tanks (AREA)

Abstract

A method for evolving a water wave waveform based on a high-order water wave model comprises the steps of constructing the water wave model, carrying out logarithmic transformation, constructing a test function f, evolving the water wave model and determining parameters. The invention considers a complex actual water wave model, combines the waveform characteristics of periodic waves and solitary waves, evolves a high-order high-dimensional water wave model, obtains corresponding parameters and a corresponding symbolic representation form, and shows the physical characteristics of a new waveform corresponding to the model in the motion process and the propagation process. Through simulation experiments, the invention realizes the combination of theoretical analysis and practical problems, enriches the display of the interaction of long waves corresponding to the models, can be used for analyzing the physical characteristics of long-wave models in practical problems and expands the application range of the long waves.

Description

Method for evolving water wave waveform based on high-order water wave model
Technical collar city
The invention belongs to the technical field of waveform processing, and particularly relates to determination of an evolution water wave waveform of a high-order water wave model.
Background
In real life, research on a nonlinear high-dimensional high-order water wave model relates to a plurality of natural disciplines such as biology, hydraulics, physics, mechanics, computer disciplines and the like. In the research process, students find that a high-dimensional water wave model can be simulated according to the natural state of water waves, parameters of a high-order high-dimensional water wave model are determined through the evolution of a known wave pattern, a mathematical model of the water waves can be obtained according to parameter analysis, and actual problems are abstracted into the mathematical model which is favorable for research and analysis. The energy change and the propagation state of high-dimensional high-order water waves can be better observed through the research on the parameters of the mathematical model. Therefore, the research of high-dimensional high-order water wave models is gradually valued by scientists. Previous studies on this type of model were limited to periodic or soliton wave patterns alone. The periodic wave graph can well show the propagation process and physical properties of the periodic wave, but only can show the properties of the periodic wave, and the analysis of multiple angles cannot be achieved. Similarly, the graph of the solitary wavelets can only show the wave change and the propagation process when the solitary wavelets collide, has certain limitation, cannot analyze more complex waveforms, and cannot adapt to more complex natural conditions. For the wave pattern of the low-dimensional water wave model, the process of wave propagation is difficult to show due to low dimension, which is not beneficial to the research and analysis of waves.
Disclosure of Invention
The technical problem to be solved by the invention is to overcome the defects of the prior art and provide a method for evolving a water wave waveform based on a high-order water wave model, which is simple, high in operation speed and high in accuracy.
The technical scheme adopted for solving the technical problems comprises the following steps:
(1) Construction of water wave model
A2 + 1-dimensional 4-order nonlinear water wave model is constructed according to formula (1):
αu yt +βu xxxy +γu x u xy +δu y u xx =0 (1)
u=u(x,y,t)
where u is a long wave formed by a time variable t and a space variable x and a space variable y x Is the first order partial derivative of u with respect to x, u y Is the first order partial derivative of u with respect to y, u t Is the first-order partial derivative of u with respect to t, u xx Is the second order partial derivative of u with respect to x, u yy Is the second order partial derivative of u with respect to y, u tt Is the second order partial derivative of u with respect to t, u xxxx Is the fourth order partial derivative of u with respect to x, u yyyy Is the fourth order partial derivative, u, of y tttt Is the fourth order partial derivative of u with respect to t, α, β, γ, ε are rational numbers, the ratio of α to β, γ, ε is 1:1 to 5: -5 to-1: -5 to-1.
(2) Logarithmic transformation
The following logarithmic transformation is performed according to equation (2):
u=N(lnf) x (2)
f=f(x,y,t)
f is a differentiable function with respect to the variables x, y, t, and N is an even number.
(3) Construction of a checking function f
The test function f is constructed as equation (3):
Figure BDA0002895096940000021
ξ i =k i x+w i y+c i t,
wherein a is i Is amplitude, k i Is the wave velocity in the x direction, w i Wave velocity in the y direction, c i As the frequency of the wave, i e [1, 2, 3 ]],a i ,k i ,w i ,c i The value range of (A): a is i ∈[-10,10],k i 、w i 、c i ∈[-10,0)∪(0,10]。
(4) Evolution of water wave models
Obtaining an arbitrary function u with respect to the parameter a according to equation (2) i ,c i ,w i ,k i The symbol expression of (a):
Figure BDA0002895096940000022
the formula (4) is to simulate a water wave model by the determined interaction form of the periodic wave and the solitary wave, and find out when a non-blasting waveform exists by combining with the specific waveform display of the actual water wave generation and transmission.
(5) Determining parameters
Step (4), when the long-wave waveform appears in the non-blasting model, finding out the relation existing among partial parameters, assigning the parameters without the relation in a determined range, and obtaining a when the parameters are determined to be consistent with the actual long-wave waveform i ,k i ,w i ,c i Specific values of the parameters and the final form of equation (4).
In formula (1) of step (1) of constructing the water wave model of the present invention, the optimum ratio of α to β, γ, and ∈ is 1:1: -3: -3.
In the formula (2) of the logarithmic conversion step (2), N is an even number of-10 to 14.
In the formula (2) of the logarithmic transformation step (2) of the present invention, the value of N is preferably-2.
In formula (3) of step (3) of constructing the test function of the present invention, c i Value of 1,a 1 The value of 0,a 2 Value of 1,a 3 The value is-6.25, k 1 The value is 1,k 2 The value of k is 0.5 3 The value is 0.1,w 1 Value of 1,w 2 The value is 0.2,w 3 The value was 0.04.
The invention combines the period method and the soliton method to generate a new waveform, can better adapt to variable and complex practical application conditions, and can well research the high-dimensional long-wave model by a wide-field method and a direct planning method.
The invention provides a simulation method based on a high-dimensional water wave model, namely a field method and a direct fitting method, which are simpler and can be completed with the assistance of special simulation software aiming at analyzing various existing waveforms of the existing ships, oceans, climates and the like. Through the value taking of the discrete parameters, the physical characteristics of the new waveform corresponding to the model in the motion process and the propagation process are shown, and the combination of theoretical analysis and practical problems is realized. The invention enriches the display of the interaction of the long waves corresponding to the model and expands the application range of the long waves.
Drawings
FIG. 1 is a flowchart of example 1 of the present invention.
FIG. 2 is a three-dimensional view of a 2+1 dimensional 4-order water wave model modeled with a first set of parameters when t is-4.
FIG. 3 is a three-dimensional view of a 2+1 dimensional 4-order water wave model modeled with a first set of parameters when t is 0.
FIG. 4 is a three-dimensional view of a 2+1 dimensional 4-order water wave model modeled with a first set of parameters at t of 4.
Detailed Description
The present invention will be described in further detail with reference to the following drawings and examples, but the present invention is not limited to these examples.
Example 1
Taking the known BLMP long-wave model as an example, the method for evolving a water wave waveform based on the high-order water wave model of the present embodiment comprises the following steps (see fig. 1):
(1) Constructing a water wave model
A2 + 1-dimensional 4-order nonlinear water wave model is constructed according to formula (1):
αu yt +βu xxxy +γu x u xy +δu y u xx =0 (1)
u=u(x,y,t)
where u is a long wave formed by a time variable t and space variables x and y x Is the first order partial derivative of u with respect to x, u y Is the first order partial derivative of u with respect to y, u t Is the first order partial derivative of u with respect to t, u xx Is the second order partial derivative of u with respect to x, u yy Is the second order partial derivative of u with respect to y, u tt Is the second order partial derivative of u with respect to t, u xxxx Is the fourth order partial derivative of u with respect to x, u xyyy Is the fourth order partial derivative, u, of y tttt Is the fourth order partial derivative of u with respect to t, alpha, beta, gamma, epsilon are rational numbers, the ratio of alpha to beta, gamma, epsilon is 1:1 to 5: -5 to-1: -5 to-1, the ratio of α to β, γ, ε being 1:1: -3: -3.
(2) Logarithmic transformation
The following logarithmic transformation is performed according to equation (2):
u=N(lnf) x (2)
f=f(x,y,t)
wherein f is a differentiable function related to variables x, y, t, N is an even number, N takes on an even number of-10 to 14, and N takes on a value of-2 in this embodiment.
(3) Construction of a test function f
The test function f is constructed according to equation (3):
Figure BDA0002895096940000041
ξ i =k i x+w i y+c i t,
wherein a is i Is amplitude, k i Is the wave velocity in the x direction, w i Wave speed in the y direction, c i As the frequency of the wave, i e [1, 2, 3 ]],a i ∈[-10,10],k i 、w i 、c i ∈[-10,0)∪(0,10]The values of this embodiment are: c. C i Take 1,a 1 Take 0,a 2 Take 1,a 3 Take-6.25,k 1 Take 1,k 2 Take 0.5,k 3 Take 0.1,w 1 Take 1,w 2 Take 0.2,w 3 0.04 is taken.
(4) Evolution of water wave models
Obtaining a long wave u with respect to a parameter a according to equation (2) i ,c i ,w i ,k i The symbol expression of (c):
Figure BDA0002895096940000042
Figure BDA0002895096940000051
the formula (4) is to simulate a water wave model by the determined interaction form of the periodic wave and the solitary wave, and find out when a non-blasting waveform exists by combining with the specific waveform display of the actual water wave generation and transmission.
(5) Determining parameters
Finding out partial parameters when the non-blasting model has long-wave waveform in step (4)Existing relation, assigning the parameters without relation in the determined range, and obtaining a when determining that the wave form is consistent with the actual long wave form i ,k i ,w i ,c i The specific values of the parameters and the final form of equation (4) (see fig. 2, 3, 4).
Example 2
Taking a known long-wave model as an example, the method for evolving a water wave waveform based on a high-order water wave model of the embodiment comprises the following steps:
(1) Constructing a water wave model
Constructing a 2+ 1-dimensional 4-order nonlinear water wave model according to formula (1):
αu yt +βu xxxy +γu x u xy +δu y u xx =0 (1)
u=u(x,y,t)
where u is a long wave formed by a time variable t and a space variable x and a space variable y x Is the first order partial derivative of u with respect to x, u y Is the first order partial derivative of u with respect to y, u t Is the first order partial derivative of u with respect to t, u xx Is the second order partial derivative of u with respect to x, u yy Is the second order partial derivative of u with respect to y, u tt Is the second-order partial derivative of u with respect to t, u xxxx Is the fourth order partial derivative of u with respect to x, u yyyy Is the fourth order partial derivative, u, of y tttt Is the fourth order partial derivative of u with respect to t, alpha, beta, gamma, epsilon are rational numbers, the ratio of alpha to beta, gamma, epsilon is 1:1 to 5: -5 to-1: -5 to-1, the ratio of α to β, γ, ε being 1:1: -5: -5.
(2) Logarithmic transformation
The following logarithmic transformation is performed according to equation (2):
u=N(lnf) x (2)
f=f(x,y,t)
wherein f is a differentiable function related to variables x, y, t, N is an even number, N takes on an even number of-10 to 14, and N takes on a value of-10 in this embodiment.
(3) Construction of a test function f
The test function f is constructed according to equation (3):
Figure BDA0002895096940000061
ξ i =k i x+w i y+c i t,
wherein a is i Is amplitude, k i Is the wave velocity in the x direction, w i Wave speed in the y direction, c i As the frequency of the wave, i e [1, 2, 3 ]],a i ,k i ,w i ,c i The value range of (A): a is a i ∈[-10,10],k i 、w i 、c i ∈[-10,0)∪(0,10]A of the present embodiment i The value is 0.1,k i 、w i 、c i Is 10.
The other steps were the same as in example 1. To obtain a i ,k i ,w i ,c i Specific values of the parameters and the final form of equation (4).
Example 3
Taking a known long-wave model as an example, the method for evolving a water wave waveform based on a high-order water wave model of the embodiment comprises the following steps:
(1) Construction of water wave model
Constructing a 2+ 1-dimensional 4-order nonlinear water wave model according to formula (1):
αu yt +βu xxxy +γu x u xy +δu y u xx =0 (1)
u=u(x,y,t)
where u is a long wave formed by a time variable t and space variables x and y x Is the first order partial derivative of u with respect to x, u y Is the first order partial derivative of u with respect to y, u t Is the first order partial derivative of u with respect to t, u xx Is the second order partial derivative of u with respect to x, u yy Is the second order partial derivative of u with respect to y, u tt Is the second order partial derivative of u with respect to t, u xxxx Is the fourth order partial derivative of u with respect to x, u yyyy Is the fourth order partial derivative, u, of y tttt Is the fourth order partial derivative of u with respect to t, alpha, beta, gamma, epsilon are rational numbers, the ratio of alpha to beta, gamma, epsilon is 1:1 to 5: -5 to-1: -5 to-1, the ratio of α to β, γ, ε being 1:5: -1: -1.
(2) Logarithmic transformation
The following logarithmic transformation is performed according to equation (2):
u=N(lnf) x (2)
f=f(x,y,t)
where f is a differentiable function for variables x, y, and t, N is an even number between-10 and 14, and N in this embodiment is 14.
(3) Construction of a checking function f
The test function f is constructed according to equation (3):
Figure BDA0002895096940000071
ξ i =k i x+w i y+c i t, wherein a i Is amplitude, k i Is the wave velocity in the x direction, w i Wave velocity in the y direction, c i As the frequency of the wave, i e [1, 2, 3 ]],a i ,k i ,w i ,c i The value range of (A): a is i ∈[-10,10],k i 、w i 、c i ∈[-10,0)∪(0,10]A of the present embodiment i Has a value of 10,k i 、w i 、c i Is 0.1.
The other steps were the same as in example 1. To obtain a i ,k i ,w i ,c i Specific values of the parameters and the final form of equation (4).
In order to verify the beneficial effects of the invention, the inventor adopts the method for determining the optimal evolution waveform of the high-order water wave model in the embodiment 1 of the invention to carry out simulation experiments, and the experimental conditions are as follows:
the results of simulation experiments in example 1 are shown in fig. 2, 3, and 4, where fig. 2 is a three-dimensional view of u when the spatial variable t is-4, fig. 3 is a three-dimensional view of u when the spatial variable t is 0, and fig. 4 is a three-dimensional view of u when the spatial variable t is 4. As can be seen from fig. 2, when the space variable t takes-4, the two waves collide, the amplitude decreases, and the energy of the waves decreases. As can be seen from fig. 3, when the spatial variable t takes 0, the two waves still collide, and the propagation direction does not change. As can be seen from fig. 4, when the spatial variable t takes 4, the wave continues to propagate from the original position along the direction, and the energy does not change. Test results show that the long wave propagation process can be completely shown in the embodiment 1 of the invention, and the method in the embodiment 1 is proved to be good in simulation of the model.

Claims (4)

1. A method for evolving a water wave waveform based on a high-order water wave model is characterized by comprising the following steps:
(1) Constructing a water wave model
Constructing a 2+ 1-dimensional 4-order nonlinear water wave model according to formula (1):
αu yt +βu xxxy +γu x u xy +δu y u xx =0 (1)
u=u(x,y,t)
where u is a long wave formed by a time variable t and two space variables x and y x Is the first order partial derivative of u with respect to x, u y Is the first order partial derivative of u with respect to y, u t Is the first order partial derivative of u with respect to t, u xx Is the second-order partial derivative of u with respect to x, alpha, beta, gamma and delta are rational numbers, and the ratio of alpha to beta, gamma and delta is 1: 1-5: 5-1;
(2) Logarithmic transformation
The following logarithmic transformation is performed according to equation (2):
u=N(lnf) x (2)
f=f(x,y,t)
where f is a differentiable function with respect to the variables x, y, t, and N is an even number;
(3) Construction of a test function f
The test function f is constructed according to equation (3):
Figure FDA0003890039400000011
ξ i =k i x+w i y+c i t,
wherein a is i Is amplitude, k i Is the wave velocity in the x direction, w i Wave velocity in the y direction, c i The frequency of the wave, i is 1, 2, 3, a i ,k i ,w i ,c i The value range of (A): a is a i ∈[0,10],k i 、w i 、c i ∈(0,10];
(4) Evolution of water wave models
Obtaining an arbitrary function u with respect to the parameter a according to equation (2) i ,c i ,w i ,k i The symbol expression of (a):
Figure FDA0003890039400000012
Figure FDA0003890039400000021
the formula (4) is that a water wave model is simulated by the determined interaction form of periodic waves and solitary waves, and when non-blasting waveforms exist is found out by combining with the specific waveform display of actual water wave generation and transmission;
(5) Determining parameters
Finding out the relation among partial parameters when the non-blasting model has long wave form, assigning the parameters without relation in the determined range, and obtaining a when the parameters are consistent with the actual long wave form i ,k i ,w i ,c i Specific values of the parameters and the final form of equation (4).
2. The method for evolving a water wave waveform based on a higher-order water wave model as claimed in claim 1, wherein: in the formula (1) of the step (1) of constructing the water wave model, the ratio of alpha to beta, gamma and delta is 1: 3.
3. The method for evolving water wave waveforms based on higher-order water wave models of claim 1, wherein: in the formula (2) in the logarithmic transformation step (2), N takes an even number of-10 to 14.
4. The method for evolving water wave waveform based on higher-order water wave model according to claim 1 or 3, wherein: in the formula (2) of the logarithmic transformation step (2), N takes the value of-2.
CN202110039498.2A 2021-01-13 2021-01-13 Method for evolving water wave waveform based on high-order water wave model Active CN112765802B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110039498.2A CN112765802B (en) 2021-01-13 2021-01-13 Method for evolving water wave waveform based on high-order water wave model

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110039498.2A CN112765802B (en) 2021-01-13 2021-01-13 Method for evolving water wave waveform based on high-order water wave model

Publications (2)

Publication Number Publication Date
CN112765802A CN112765802A (en) 2021-05-07
CN112765802B true CN112765802B (en) 2022-11-29

Family

ID=75699979

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110039498.2A Active CN112765802B (en) 2021-01-13 2021-01-13 Method for evolving water wave waveform based on high-order water wave model

Country Status (1)

Country Link
CN (1) CN112765802B (en)

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003075205A (en) * 2001-09-03 2003-03-12 Taisei Corp Method of recording data
CN102034001A (en) * 2010-12-16 2011-04-27 南京大学 Design method for distributed hydrological model by using grid as analog unit
CN103698808A (en) * 2012-09-28 2014-04-02 中国石油天然气集团公司 Method for feature points separation and waveform reconstruction of waveform extreme value of seismic and logging data
CN108701219A (en) * 2017-03-14 2018-10-23 华为技术有限公司 The method and device of waveform signal processing
CN111025388A (en) * 2019-12-19 2020-04-17 河海大学 Multi-wave combined prestack waveform inversion method
CN111611720A (en) * 2020-05-28 2020-09-01 自然资源部第一海洋研究所 Wave field non-Gaussian state degree evaluation method suitable for real ocean

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7478021B2 (en) * 2005-03-07 2009-01-13 Northrop Grumman Corporation Method and means for generating high-order hermite functions for simulation of electromagnetic wave devices
AU2006235820B2 (en) * 2005-11-04 2008-10-23 Westerngeco Seismic Holdings Limited 3D pre-stack full waveform inversion
CN105319581B (en) * 2014-07-31 2018-01-16 中国石油化工股份有限公司 A kind of efficient time-domain full waveform inversion method

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003075205A (en) * 2001-09-03 2003-03-12 Taisei Corp Method of recording data
CN102034001A (en) * 2010-12-16 2011-04-27 南京大学 Design method for distributed hydrological model by using grid as analog unit
CN103698808A (en) * 2012-09-28 2014-04-02 中国石油天然气集团公司 Method for feature points separation and waveform reconstruction of waveform extreme value of seismic and logging data
CN108701219A (en) * 2017-03-14 2018-10-23 华为技术有限公司 The method and device of waveform signal processing
CN111025388A (en) * 2019-12-19 2020-04-17 河海大学 Multi-wave combined prestack waveform inversion method
CN111611720A (en) * 2020-05-28 2020-09-01 自然资源部第一海洋研究所 Wave field non-Gaussian state degree evaluation method suitable for real ocean

Non-Patent Citations (8)

* Cited by examiner, † Cited by third party
Title
An improved C-V model for breast MR images segmentation;Hong Fan et al.;《2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)》;20190124;全文 *
Hirota双线性导数方法求解KdV方程的双周期波解;梁聪刚等;《河北省科学院学报》;20150915(第03期);全文 *
一种实用的水波数值模拟方法;陈可洋;《工程地质计算机应用》;20100630(第02期);全文 *
一种改进的近断层脉冲型地震动模拟方法;杨福剑等;《震灾防御技术》;20190915(第03期);全文 *
一种非线性水波自由面模型及其海浪数值模拟;焦甲龙等;《华中科技大学学报(自然科学版)》;20150423(第04期);全文 *
时空分数阶Cahn - Hilliard 方程新的精确解;赖晓霞等;《渭南师范学院学报》;20170630;全文 *
液体超声驻波声场实验研究;胡淑芳等;《陕西师范大学学报(自然科学版)》;20100110(第01期);全文 *
黏性对深水波列非线性演化的影响;张本辉等;《中国航海》;20150930;全文 *

Also Published As

Publication number Publication date
CN112765802A (en) 2021-05-07

Similar Documents

Publication Publication Date Title
US7191161B1 (en) Method for constructing composite response surfaces by combining neural networks with polynominal interpolation or estimation techniques
Kuehn et al. Dynamical analysis of evolution equations in generalized models
Xu et al. Multi-direction chain and grid chaotic system based on Julia fractal
Liu et al. A class of novel discrete memristive chaotic map
CN109033025B (en) Floating structure time domain response analysis method based on state space model
CN112765802B (en) Method for evolving water wave waveform based on high-order water wave model
Hendrickx et al. Sequential design and rational metamodelling
Marinić-Kragić et al. 3D shape optimization of fan vanes for multiple operating regimes subject to efficiency and noise-related excellence criteria and constraints
Popov Numerical analysis of soliton solutions of the modified Korteweg-de Vries-sine-Gordon equation
Saka et al. Quintic B-spline collocation method for numerical solution of the RLW equation
CN113945997B (en) Method for improving ocean forecasting precision based on analysis of four-dimensional set variation
CN115130340A (en) Pipeline modeling method based on fractional Brownian motion
Gurenko et al. An Approach to Simulation of Stationary and Non-stationary Processes in the Harmonic Basis
Engblom A discrete spectral method for the chemical master equation
CN112885202B (en) Method for evolving wave model waveform process based on bilinear construction function method
Khalafi et al. On orthogonalization approach to construct a multiple input transfer function model
Kontoleon The Markovian binary tree: a model of the macroevolutionary process
CN115390135A (en) Elastic wave variable grid finite difference forward modeling method and equipment thereof
Mezhuyev et al. Development and application of the problem-oriented language FORTU for the design of non-standard mechanical constructions
CN112630823B (en) Three-dimensional elastic wave field numerical simulation method and system based on staggered grid low-rank finite difference
Tan Wiener-Hammerstein modeling of nonlinear effects in bilinear systems
Pediroda et al. Efficient stochastic optimization using chaos collocation method with modefrontier
Haddad et al. On reliability estimation p (X1< Y< X2) following Rayleigh-Pareto distribution in stress-strength model
Hamasalh et al. Optimized Trigonometric Spline Function with Conjugate GradientMethod for Solving FDEs
Rast Causal Discovery for Gene Regulatory Network Prediction

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant