Powell's optimal identification of material constants of thin-walled box girders based on Fibonacci series search method

A dynamic Bayesian error function of material constants of the structure is developed for thin-walled curve box girders. Combined with the automatic search scheme with an optimal step length for the one-dimensional Fibonacci series, Powell＇s optimization theory is used to perform the stochastic identification of material constants of the thin-walled curve box. Then, the steps in the parameter identification are presented. Powell＇s identification procedure for material constants of the thin-walled curve box is compiled, in which the mechanical analysis of the thin-walled curve box is completed based on the finite curve strip element （FCSE） method. Some classical examples show that Powell＇s identification is numerically stable and convergent, indicating that the present method and the compiled procedure are correct and reliable. During the parameter iterative processes, Powell＇s theory is irrelevant with the calculation of the FCSE partial differentiation, which proves the high computation efficiency of the studied methods. The stochastic performances of the system parameters and responses axe simultaneously considered in the dynamic Bayesian error function. The one-dimensional optimization problem of the optimal step length is solved by adopting the Fibonacci series search method without the need of determining the region, in which the optimized step length lies.

QPSO算法和Powell法结合的多分辨率医学图像配准

图像配准一直是图像研究领域的热点话题,互信息的配准方法由于其精度高、鲁棒性强等特点,成为图像配准中的常用方法。但其目标函数存在局部极值问题。针对这个问题,提出一种量子行为的粒子群优化算法(QPSO)和Powell法相结合的多分辨率搜索优化算法。QPSO参数个数少,其每一个迭代步的取样空间能覆盖整个解空间,能保证算法的全局收敛,因此可以有效地解决Powell算法的缺点。该算法将量子行为的粒子群优化算法(QPSO)与Powell法结合起来对二维的MRI图像进行配准。实验结果表明,该方法能够有效地克服互信息函数的局部极值问题,并提高了配准精度和速度。

Powell dynamic identification of displacement parameters of indeterminate thin-walled curve box based on FCSE theory

The FCSE controlling equation of pinned thinwalled curve box was derived and the indeterminate problem of continuous thin-walled curve box with diaphragm was solved based on flexibility theory. With Bayesian statistical theory,dynamic Bayesian error function of displacement parameters of indeterminate curve box was founded. The corresponding formulas of dynamic Bayesian expectation and variance were deduced. Combined with one-dimensional Fibonacci automatic search scheme of optimal step size,the Powell optimization theory was utilized to research the stochastic identification of displacement parameters of indeterminate thin-walled curve box. Then the identification steps were presented in detail and the corresponding calculation procedure was compiled. Through some classic examples,it is obtained that stochastic performances of systematic parameters and systematic responses are simultaneously deliberated in dynamic Bayesian error function. The one-dimensional optimization problem of the optimal step size is solved by adopting Fibonacci search method. And the Powell identification of displacement parameters of indeterminate thin-walled curve box has satisfied numerical stability and convergence,which demonstrates that the presented method and the compiled procedure are correct and reliable.During parameters鈥？iterative processes,the Powell theory is irrelevant with the calculation of finite curve strip element（FCSE） partial differentiation,which proves high computation effciency of the studied method.

Euler’s First-Order Explicit Method–Peridynamic Differential Operator for Solving Population Balance Equations of the Crystallization Process

Using Euler’s first-order explicit(EE)method and the peridynamic differential operator(PDDO)to discretize the time and internal crystal-size derivatives,respectively,the Euler’s first-order explicit method–peridynamic differential operator(EE–PDDO)was obtained for solving the one-dimensional population balance equation in crystallization.Four different conditions during crystallization were studied:size-independent growth,sizedependent growth in a batch process,nucleation and size-independent growth,and nucleation and size-dependent growth in a continuous process.The high accuracy of the EE–PDDO method was confirmed by comparing it with the numerical results obtained using the second-order upwind and HR-van methods.The method is characterized by non-oscillation and high accuracy,especially in the discontinuous and sharp crystal size distribution.The stability of the EE–PDDO method,choice of weight function in the PDDO method,and optimal time step are also discussed.

Energy Stable Nodal DG Methods for Maxwell’s Equations of Mixed-Order Form in Nonlinear Optical Media

In this work,we develop energy stable numerical methods to simulate electromagnetic waves propagating in optical media where the media responses include the linear Lorentz dispersion,the instantaneous nonlinear cubic Kerr response,and the nonlinear delayed Raman molecular vibrational response.Unlike the first-order PDE-ODE governing equations considered previously in Bokil et al.(J Comput Phys 350:420–452,2017)and Lyu et al.(J Sci Comput 89:1–42,2021),a model of mixed-order form is adopted here that consists of the first-order PDE part for Maxwell’s equations coupled with the second-order ODE part(i.e.,the auxiliary differential equations)modeling the linear and nonlinear dispersion in the material.The main contribution is a new numerical strategy to treat the Kerr and Raman nonlinearities to achieve provable energy stability property within a second-order temporal discretization.A nodal discontinuous Galerkin(DG)method is further applied in space for efficiently handling nonlinear terms at the algebraic level,while preserving the energy stability and achieving high-order accuracy.Indeed with d_(E)as the number of the components of the electric field,only a d_(E)×d_(E)nonlinear algebraic system needs to be solved at each interpolation node,and more importantly,all these small nonlinear systems are completely decoupled over one time step,rendering very high parallel efficiency.We evaluate the proposed schemes by comparing them with the methods in Bokil et al.(2017)and Lyu et al.(2021)(implemented in nodal form)regarding the accuracy,computational efficiency,and energy stability,by a parallel scalability study,and also through the simulations of the soliton-like wave propagation in one dimension,as well as the spatial-soliton propagation and two-beam interactions modeled by the two-dimensional transverse electric(TE)mode of the equations.

Sargent改进的Powell方法在桥梁沉降基础预测中的应用

Sargent改进的Powell方法是曲线拟合中的一种重要方法。本文利用这种方法针对蕴藻浜特大桥沉降中的实测数据给出了五种模型下的沉降预测,这些模型包括双曲线斜率倒数模型、Vander Veen指数模型、宇都一马指数模型、龚帕兹模型、以及波松曲线模型,并发现这种方法对波松旋回模型和灰色系统模型适用性不强。

The forecasting efficiency under different selected regions by Pattern Informatics Method and seismic potential estimation in the North-South Seismic Zone

In 2022,four earthquakes with M_(S)≥6.0 including the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes occurred in the North-South Seismic Zone(NSSZ),which demonstrated high and strong seismicity.Pattern Informatics(PI)method,as an effective long and medium term earthquake forecasting method,has been applied to the strong earthquake forecasting in Chinese mainland and results have shown the positive performance.The earthquake catalog with magnitude above M_(S)3.0 since 1970 provided by China Earthquake Networks Center was employed in this study and the Receiver Operating Characteristic(ROC)method was applied to test the forecasting efficiency of the PI method in each selected region related to the North-South Seismic Zone systematically.Based on this,we selected the area with the best ROC testing result and analyzed the evolution process of the PI hotspot map reflecting the small seismic activity pattern prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes.A“forward”forecast for the area was carried out to assess seismic risk.The study shows the following.1)PI forecasting has higher forecasting efficiency in the selected study region where the difference of seismicity in any place of the region is smaller.2)In areas with smaller differences of seismicity,the activity pattern of small earthquakes prior to the Menyuan M_(S)6.9 and Luding M_(S)6.8 earthquakes can be obtained by analyzing the spatio-temporal evolution process of the PI hotspot map.3)The hotspot evolution in and around the southern Tazang fault in the study area is similar to that prior to the strong earthquakes,which suggests the possible seismic hazard in the future.This study could provide some ideas to the seismic hazard assessment in other regions with high seismicity,such as Japan,Californi,Turkey,and Indonesia.

Research on the Application of Montessori Education Method in Cognitive Training of Patients with Alzheimer’s Disease

Objective:To study the application of the Montessori education method in cognitive training in patients with Alzheimer’s disease(AD).Methods:40 cases of senile dementia patients who were admitted to our hospital from January 2022 to January 2023 were selected and randomly divided into an intervention group and a control group according to the single and double number table method,with 20 cases in each group.The intervention group used the Montessori education method,the principle of which was to implement individualized health interventions based on the individual conditions of the patients,for a period of 6 months;the control group was given conventional treatment and nursing of the disease.The Mini-Mental State Examination(MMSE)was used to compare the effects of the two groups of patients before and after health intervention and conduct statistical analysis.Results:The score of the intervention group was higher than that of the control group,and there was a statistical difference between the two(P<0.05).Conclusion:Implementing the Montessori education method for diagnosed Alzheimer’s patients can effectively improve their cognitive function and delay the progress of further dementia.

Solid Waste Management:A MADM Approach Using Fuzzy Parameterized Possibility Single-Valued Neutrosophic Hypersoft Expert Settings

The dramatic rise in the number of people living in cities has made many environmental and social problems worse.The search for a productive method for disposing of solid waste is the most notable of these problems.Many scholars have referred to it as a fuzzy multi-attribute or multi-criteria decision-making problem using various fuzzy set-like approaches because of the inclusion of criteria and anticipated ambiguity.The goal of the current study is to use an innovative methodology to address the expected uncertainties in the problem of solid waste site selection.The characteristics(or sub-attributes)that decision-makers select and the degree of approximation they accept for various options can both be indicators of these uncertainties.To tackle these problems,a novel mathematical structure known as the fuzzy parameterized possibility single valued neutrosophic hypersoft expert set(ρˆ-set),which is initially described,is integrated with a modified version of Sanchez’s method.Following this,an intelligent algorithm is suggested.The steps of the suggested algorithm are explained with an example that explains itself.The compatibility of solid waste management sites and systems is discussed,and rankings are established along with detailed justifications for their viability.This study’s strengths lie in its application of fuzzy parameterization and possibility grading to effectively handle the uncertainties embodied in the parameters’nature and alternative approximations,respectively.It uses specific mathematical formulations to compute the fuzzy parameterized degrees and possibility grades that are missing from the prior literature.It is simpler for the decisionmakers to look at each option separately because the decision is uncertain.Comparing the computed results,it is discovered that they are consistent and dependable because of their preferred properties.

Critical care nurses and their clinical reasoning for customizing monitor alarms:a mixed-method study

Objective:To explore the clinical rationale of critical care nurses for personalizing monitor alarms.One of the most crucial jobs assigned to critical care nurses is monitoring patients'physiological indicators and carrying out the necessary associated interventions.Successful use of equipment in the nursing practice environment will be improved by a thorough understanding of the nurse's approach to alarm configuration.Methods:A mixed-method design integrating quantitative and qualitative components was used.The sample of this study recruited a convenience sample of 60 nurses who have worked in critical care areas.This study took place at Lebanese American University Medical Center Rizk Hospital,utilizing a semi-structured interview with participants.Results:The study demonstrated the high incidence of nuisance alarms and the desensitization of critical care nurses to vital ones.According to the nurses,frequent false alarms and a shortage of staff are the 2 main causes of alarm desensitization.Age was significantly associated with the perception of Smart alarms,according to the data(P=0.03).Four interconnected themes and subcategories that reflect the clinical reasoning process for alarm customization were developed as a result of the study's qualitative component:(1)unit alarm environment;(2)nursing style;(3)motivation to customize;and(4)clinical and technological customization.Conclusions:According to this study,nurses believe that alarms are valuable.However,a qualitative analysis of the experiences revealed that customization has been severely limited since the healthcare team depends on nurses to complete these tasks independently.Additionally,a staffing shortage and lack of technical training at the start of placement have also hindered customization.

改进的人工鱼群算法和Powell法结合的医学图像配准

针对目前基于互信息图像配准的局部极值问题,提出了一种改进的人工鱼群算法和Powell算法结合的多分辨率医学图像配准算法.该算法采用新的相似性测度方法即归一化模糊加权互信息和归一化局部能量加权匹配度,利用多分辨率策略采用HPV插值,并采用改进的人工鱼群算法结合Powell算法完成医学图像的配准.采用改进的人工鱼群算法在图像的最低分辨率上进行全局优化,以全局最优值为初始值,结合Powell算法完成图像配准.这不仅基本解决了互信息函数和Powell算法的局部极值问题,还减少了数据的处理量,加快了配准速度.实验结果表明,文中算法与其他经典的配准算法相比,提高了配准的精确度和性能.

融合高斯变异和Powell法的花朵授粉优化算法

花朵授粉算法(flower pollination algorithm,FPA)是最近提出的一种新型群智能优化算法,由于其较好地解决了全局搜索和局部搜索的平衡性问题,且具有参数少,易实现等特点,已得到广泛应用和研究,但现有研究对其参数的研究较少,同时该算法也存在演化后期收敛速度慢且易陷入局部极小等缺陷,使其应用范围受到制约。为了提升FPA算法的整体性能,对其控制步长的缩放因子的取值进行了修正;提出了把高斯变异和Powell法融入到花朵授粉算法中的混合算法GMPFPA(flower pollination algorithm combination with Gauss mutation and Powell search method)。改进算法首先利用高斯变异对全局搜索进行扰动,增强种群的多样性,提高全局探测能力,然后引入局部寻优能力强大的Powell法提升其局部开发能力。通过12个高维经典测试函数对比实验,验证了改进算法的有效性和优越性。

蚁群算法和Powell法结合的多分辨率三维图像配准

基于互信息的配准方法具有精度高,鲁棒性强的特点,成为近年来图像配准研究的热点。但基于互信息的目标函数存在许多局部极值,为配准的优化过程带来了很大的困难。该文提出了一种蚁群算法和Powell法相结合的多分辨率搜索优化算法。该算法以互信息作为相似性测度,采用基于小波变换的多分辨率策略,将蚁群算法与Powell法结合起来对三维的CT,MR图像进行了配准。实验结果表明,这种方法能够有效地克服互信息函数的局部极值,大大地提高了配准精度,达到亚像素级。

求解连续空间优化问题的Powell蚁群算法

针对连续空间函数优化问题,提出了Powell蚁群算法.该算法把Powell方法嵌入蚁群算法的局部搜索,提高蚁群算法的搜索精度和收敛效率.全局搜索过程中,把传统蚁群算法中的信息素更新和蚂蚁的转移规则拓展到连续空间中,定义了相应的求解算法.通过对二维多极值非线性函数的寻优实例进行仿真,并与Powell方法的求解结果进行比较,证明该方法的有效性.

一种改进的Powell共轭方向算法

对Ｐｏｗｅｌｌ共轭方向优化算法提出一种改进策略。在采用改进算法逐次产生搜索方向时，搜索方向组不会变得近似线性相关，使搜索过程不至于被限制到变量空间的某个仿射子空间上。仿真实例表明，改进算法对于非二次函数的优化比Ｐｏｗｅｌｌ原改进算法更为有效的。

基于Powell局部搜索策略的全局优化布谷鸟算法

为了解决布谷鸟搜索算法后期收敛速度慢、求解精度不高、易陷入局部最优等缺陷,提出了一种基于Powell局部搜索策略的全局优化布谷鸟搜索算法。算法将布谷鸟全局搜索能力与Powell方法的局部寻优性能有机地结合,并根据适应度值逐步构建精英种群候选解池在迭代后期牵引Powell搜索的局部优化,在保证求解速度、尽可能找到全局极值点的同时提高算法的求解精度。对52个典型测试函数实验结果表明,该算法相比于传统的布谷鸟搜索算法不仅寻优精度和寻优率有所提高,并且适应能力强、鲁棒性好,与最新提出的其他改进算法相比也具有一定的竞争优势。

Powell机械优化方法的改进

Powell优化方法是最经典最实用的,可称为基于寻优方向组的新方向取舍法。根据共轭方向的特点,主要进行了几点改进:沿最后一个基本方向寻优,并将其最优点作为第一轮寻优的初始点;必须沿新方向寻优并将其收入基本寻优方向组;与共轭性相关的寻优方向采用较小的终止条件值,其他方向只要更新当前点即可;根据与新方向的点乘积确定离开基本寻优方向组的旧方向。无论从计算量还是从存储量衡量,新算法都优于经典算法。文中给出了新算法的算法步骤和程序流程图,分析了算法特点,提供了C语言计算机程序,保证了研究结果的可重复性。二次二维目标函数和Rosenbrock目标函数的算例表明,新算法具有较好的寻优效果。对于多维优化问题,新算法更具优势。提出的算法可称为方向组不降维的构造共轭方向法。

Powell搜索法和惯性权重非线性调整局部收缩微粒群算法的混合算法

提出一种求解无约束最优化问题的新的混合算法Powell搜索法和惯性权重非线性调整局部收缩微粒群算法的混合算法.该算法不需要计算梯度,容易应用于实际问题中.通过对微粒群算法的修正,使混合算法具有更加精确和快速的收敛性.首先利用20个基准测试函数进行仿真计算比较,计算结果表明,新混合算法在求解质量和收敛速率上都优于其他算法(PSO,GPSO和NM-PSO算法).其次,将新混合算法和最新的各种协同PSO算法进行分析比较.结果表明,新混合算法在解的搜索质量、效率和关于初始点的鲁棒性方面都远优于其他算法.

基于Fibonacci序列寻优理论薄壁弯箱材料常数的Powell优化识别

对于薄壁弯箱结构,推导了材料常数的动态Bayes误差函数,提出步长的一维Fibonacci序列自动寻优方案后,利用Powell优化理论研究了薄壁弯箱材料常数的动态识别方法,同时给出了具体的计算步骤,并研制了相应的计算程序.算例分析表明,Powell理论用于弯箱材料常数识别时表现出良好的数值稳定性和收敛性,在迭代过程中,Powell理论不涉及有限元偏导数处理,与以往材料常数的梯度优化方法相比,计算效率较高;建立的动态Bayes误差函数能同时计入系统参数的随机性和系统响应的随机性;提出的Fibonacci序列寻优方案无需通过试算确定最优步长所在区间,有效地解决最优步长的一维自动寻优问题.

一个关于无约束最优化的Powell搜索法和微粒群算法的混合算法

该文提出一种求解无约束最优化问题新的混合算法——Powell搜索法和微粒群算法的混合算法.主要目的是通过加入混合策略证明标准微粒群算法是能够被改进的.仿真结果证明了新算法是求解无约束最优化问题的一个高效的算法.