检索结果-内蒙古大学图书馆

The use of GA-RxODE (genetics algorithms and Running simulations from Ordinary Differential Equations-based model) method to optimize bioequivalence studies

引用

PHARMACOLOGY RESEARCH & PERSPECTIVES 2021年第5期9卷 e00824页

作者： Nuske, Ezequiel Omar Morozov, Mikhail Alejandro Serra, Hector Univ Buenos Aires Sch Med Dept Pharmacol Buenos Aires DF Argentina

Bioequivalence (BE) studies are prerequisite in generic products approval. Normally, they are quite simple in design and expensive in execution, and sometimes suffer ethical questioning. genetics algorithms and Running simulations from Ordinary Differential Equations-based model (GA-RxODE) is a multipurpose method used in pharmacokinetic (PK) optimization. It can be used to complete concentration-time (C-T) missing data. In this investigation, GA-RxODE was applied in BE field. For this purpose, three BE studies were selected as a source data comprising formulations of metformin, alprazolam and clonazepam. From them, five blood samples values per volunteer-round from specific preset times were chosen as if BE study was carried out with five instead of the classic 10-20 samples. With the five values of each volunteer a complete C-T curve was simulated by GA-RxODE and certain PK estimation parameters (as maximum concentration, C-max, and area under C-T curve from zero to infinite, AUC(inf)) were elicited. Finally, with these modeled parameters, a BE analysis was performed according to certain regulatory agencies guidances. Some results, expressed as geometric mean ratios of compared formulations and their 90% confidence intervals (CI90), were as follows: Metformin C-max = 0.954 (0.878-1.035), AUC(inf) = 0.949 (0.881-1.022);Alprazolam C-max = 1.063 (0.924-1.222), AUC(inf) = 1.036 (0.857-1.249), Clonazepam C-max = 0.927 (0.831-1.034), and AUC(inf) = 1.021 (0.931-1.119). All CI90 were inside the 0.8-1.25 BE range. In summary, the simulated data were bioequivalent and non-significantly different from original studies' data. This raises the opportunity to perform more economic BE studies to build reliable PK estimation parameters from a few samples per volunteer.

关键词： bioequivalence studies generic drugs genetics algorithms NLME models pharmacokinetic

来源：评论

学校读者我要写书评

暂无评论

Dot Matrices and genetics algorithms for MSA 13

Dot Matrices and Genetics Algorithms for MSA

引用

Simulation Multiconference

作者： John Tsiligaridis Fabian Ochoa Math and Computer Science Department

ISBN: (纸本)9781627482769

Multiple Sequence Alignment (MSA) is among the best important tasks in computational biology. Genetic algorithms are stochastic approaches for efficient and robust search. With the increasing rate of determination of sequences, the emphasis in biological sequence comparison has turned to the simultaneous alignment of several sequences. The consistency of align able sequence fragments for a set of sequences can be implemented by using dot matrices. A set of algorithms has been developed (a) to discover the consistency and have MSA using dot matrices (CDM), (b) to construct the MSA algorithm (CSAA) based on an extension of CDM, (c) to create a MSA algorithm based on the divide and conquer method and the use of a Genetic Algorithm (DCGA). CDM with its internal phase can minimize the number of pair wise comparisons in MSA giving better performance. CDM is also efficient in finding conserved motifs (short sequence segments that are important in protein structure) among very distantly related sequences and using also CSAA that can be used for the MSA. Finally, the DCGA framework that contains CDM or CSAA and Genetic Algorithm (GA) provides better performance than the GA. Simulation experiments are produced.

关键词： Multiple sequence alignment Dot matrix genetics algorithms MAJOR SYSTEM ACQUISITION CDM Certified emission reductions Sequence Alignment divide and conquer methods matrices Genetic Algorithm (GA)

来源：评论

学校读者我要写书评

暂无评论

Reconstruction of dynamic systems using genetic algorithms with dynamic search limits

引用

ENGINEERING WITH COMPUTERS 2025年 1-19页

作者： Rodriguez-Abreo, Omar Aragon, Jose L. Quiroz-Juarez, Mario A. Univ Nacl Autonoma Mexico Ctr Fis Aplicada & Tecnol Avanzada Blvd Juriquilla 3001 Queretaro 76230 Mexico

Mathematical modeling is a powerful tool for describing, predicting, and understanding complex phenomena exhibited by real-world systems. However, identifying the equations that govern a system's dynamics from experimental data remains a significant challenge without a definitive solution. In this study, evolutionary computing techniques are presented to estimate the governing equations of a dynamical system using time-series data. The main approach is to propose a candidate functions with unknown coefficients, and subsequently perform a parametric estimation using genetic algorithms. Some of the main contributions of the present study are an adequate modification of the genetic algorithm to remove terms with minimal contributions, and a mechanism to escape local optima during the search. To evaluate the proposed method, we applied it to three dynamical systems: a linear model, a nonlinear model, and the Lorenz system. Our results demonstrate a reconstruction with an integral square error below 0.22 and a coefficient of determination R2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R<^>2$$\end{document} of 0.99 for all systems, indicating successful reconstruction of the governing dynamic equations.

关键词： Dynamical systems genetics algorithms System identification Dynamic model Optimization

来源：评论

学校读者我要写书评

暂无评论

Analysis of the Correct Execution of Free Squats for Injury Prevention: A Genetic Algorithm Approach

Analysis of the Correct Execution of Free Squats for Inj...

引用

International Conference on Advanced Research in Technologies, Information, Innovation and Sustainability, ARTIIS 2024

作者： Guzmán-Alfaro, Sebastian Ríos-Ríos, José I. Celaya-Padilla, José M. Galván-Tejada, Carlos E. Félix-Castañeda, Angeles O. Soto-Murillo, Manuel A. de Avila-Armenta, Eduardo Mayorga-Ruiz, Pedro E. Acuña-Correa, Andrea Unidad Académica de Ingeniería Eléctrica Universidad Autónoma de Zacatecas Zacatecas98000 Mexico

ISBN: (纸本)9783031834349

The lack of training to maximize the patient’s physical performance, especially in weightlifting, can cause various types of musculoskeletal injuries. The biomechanical analysis through motion sensors and machine learning algorithms of an exercise as widely used in any sports discipline as the free squat can be a very helpful tool for both beginners and high-performance athletes. This methodology, using Xsens DOT© motion sensors which internally contain a gyroscope, records the exercise. With the necessary knowledge, the data is processed using feature extraction with statistical moments, allowing for the classification of the exercise execution with prior knowledge in sports and basic anatomy. Additionally, genetic algorithms are used to select the best variables to create a logistic classification model, achieving good performance. The proposed model obtained an accuracy of 0.7885 in a blind evaluation and an area under the receiver operating characteristic curve (AUC) of 0.74. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Biomechanical analysis Free Squat genetics algorithms

来源：评论

学校读者我要写书评

暂无评论

A genetic-based machine learning system to discover the diagnostic rules for female urinary incontinence

引用

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 1998年第3期55卷 217-228页

作者： Laurikkala, J Juhola, M Tampere Univ Dept Comp Sci FIN-33101 Tampere Finland

A machine learning system named Galactica has been developed which uses a genetic algorithm to discover the rules for an expert system from databases. Galactica devised accurate diagnostic rules for female urinary incontinence from difficult heterogeneous data. The percentages of correctly classified stress, mixed and sensory urge incontinence testing cases were 89, 86 and 87%, respectively. However, these rules were rather general, consisting of 4-6 out of 13 conditions available in the data. Diagnostic rules for stress and mixed incontinence extracted from straightforward homogeneous data were highly accurate, classifying 100% of testing cases correctly as well as being specific, having from 10 to 11 conditions. More specific, but less accurate, rules were found from heterogeneous data with a biased fitness function. All of the rules were correct, i.e. every condition in the rules had the expected value specified by the expert. Although, Galactica achieved a slightly better classification than the discriminant analysis, it is argued that the genetic approach is better than the statistical one, due to symbolic rules being comprehensible, whereas understanding. a complex mathematical model requires statistical expertise. (C) 1998 Elsevier Science Ireland Ltd. All rights reserved.

关键词： genetics algorithms genetic-based machine learning machine learning female urinary incontinence medical expert systems discriminant analysis

来源：评论

学校读者我要写书评

暂无评论

Time scheduling and optimization of industrial robotized tasks based on genetic algorithms

引用

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2015年 34卷 140-150页

作者： Baizid, Khelifa Yousnadj, Ali Meddahi, Amal Chellali, Ryad Iqbal, Jamshed Univ Cassino & Southern Lazio Dept Elect & Informat Engn Cassino Italy Polytech Mil Sch Lab Struct Mech Algiers 16111 Algeria Ist Italiano Tecnol PAVIS I-16163 Genoa Italy COMSATS Inst Informat Technol Dept Elect Engn Islamabad Pakistan

Today's industrial manipulators are more and more demanding in terms of productivity. This goal could be achieved by increasing speed of the robot manipulator and/or by optimizing the trajectories followed by manipulators while performing manufacturing, assembling, welding or similar tasks. Focusing on the second aspect, this research proposes a method based on genetic algorithms by exploiting CAD (computer aided design) capabilities to optimize and simulate cycle time in performing classical manufacturing tasks. The goal is to determine the shortest distance traveled by the robot manipulator in the coordinate space for every pair of successive points. In addition, our optimization procedure considers supplementary factors such as inverse kinematic model (IKM) and relative position/orientation of the manipulator w.r.t task points. All these factors were statistically assessed to determine both individual and cross influences in finding the optimal solution. The proposed approach has been validated on a real life setup, involving a 6-DOFs (degrees of freedom) industrial robot manipulator when performing a spot welding task on a car body. The obtained results are promising and show the effectiveness of the proposed strategy. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Task time optimization genetics algorithms Industrial manipulators

来源：评论

学校读者我要写书评

暂无评论

Genetic algorithms applied to translational strategy in metabolic-dysfunction associated steatohepatitis (MASH). Learning from mouse models

引用

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024年 255卷 108346页

作者： Martinez-Arranz, Ibon Alonso, Cristina Mayo, Rebeca Minchole, Itziar Mato, Jose M. Lee, Dae-Jin OWL Metab Rubio Metab Derio Bizkaia Spain Univ Basque Country UPV EHU Dept Math Bilbao Spain CIBERehd BRTA CIC bioGUNE Derio Bizkaia Spain IE Univ Sch Sci & Technol Madrid Spain

Background & aims: We previously identified subsets of patients with metabolic (dysfunction)-associated steatotic liver disease (MASLD) with different metabolic phenotypes. Here, we aimed to refine this classification based on genetic algorithms implemented in a Python package. The use of these genetic algorithms can help scientists to solve problems which cannot be solved with other methods. We present this package and its capabilities with specific problems. The name, PyGenMet, comes from its main goal, solving problems in Python with Genetic algorithms and Metabolomics data. Methods: We collected serum from methionine adenosyltransferase 1a knockout (Mat1a-KO) mice, which have chronically low level of hepatic S-adenosylmethionine (SAMe) and the metabolomes of all samples were determined. We also analyzed serum metabolomes of 541 patients with biopsy proven MASLD (182 with simple steatosis and 359 with metabolic (dysfunction)-associated steatohepatitis or MASH) and compared them with the serum metabolomes of this specific MASLD mouse model using Genetic algorithms in order to select patients with a specific phenotype. Results: By applying genetic algorithms, we have found a subgroup of patients with a lipid profile similar to that observed in the mouse model. When analyzing the two groups of patients, we have seen that patients with a lipid profile reflecting the mouse model characteristics show significant differences in lipoproteins, especially in LDL4, LDL-5, and LDL-6 associated with atherogenic risk. Conclusion: The results show that the application of genetic algorithms to subclassify patients with MASLD (or other metabolic disease) give consistent results and are a good approximation for the treatment of large volumes of data such as those from omics sciences and patient classification.

关键词： Python genetics algorithms MASLD MASH Subtypes Murine model

来源：评论

学校读者我要写书评

暂无评论

Optimization of large electric power distribution using a parallel genetic algorithm with dandelion strategy

引用

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2018年第5期26卷 2648-2660页

作者： Sabattin, Jorge Fuertes, Guillermo Alfar, Miguel Quezada, Luis Vargas, Manuel Autnoma Chile Univ Fac Engn Dept Ind Engn Providencia Chile Bernardo O Higgins Univ Fac Engn Sci & Technol Santiago Chile Univ Santiago Fac Engn Dept Ind Engn Santiago Chile San Sebastin Univ Fac Engn & Technol Santiago Chile

The study of electrical distribution of primary networks design is oriented to reduce the construction costs and the energy losses by transmission. The topology for the implementation of distribution networks may vary according to the geographical characteristics of the final users and requires specialized optimization solutions with metaheuristics to improve the energy performance of the electrical power systems. A parallel genetic algorithm (PGA) is proposed to optimize a tree-based topology for large-scale electric power distribution networks. The proposed PGA uses the dandelion code, which allows obtaining tree-feasible solutions within each iteration of the PGA. This cannot be achieved with other metaheuristic approaches directly. Eight cores are used simultaneously. We achieve a 22.05% improvement when compared to the tree-feasible solutions obtained with its sequential version. Moreover, the computational time required by the PGA is on average 23 times lower than the sequential version. Finally, we find feasible solutions for instances of the problem with up to 50,000 nodes.

关键词： genetics algorithms parallel algorithms power distribution power system planning

来源：评论

学校读者我要写书评

暂无评论

Investigation of the mechanical behavior of trapezoidal roofing sheets using genetic algorithms

引用

EXPERT SYSTEMS WITH APPLICATIONS 2010年第2期37卷 939-948页

作者： Mezzomo, G. P. Iturrioz, I. Grigoletti, G. Gomes, H. M. Univ Fed Rio Grande do Sul Postgrad Program Mech Engn Porto Alegre RS Brazil

The steel profiled sheets are all economical alternative for roofing and siding in industrial stores, hangars and other kinds of pavilions, since these structural components are able to close large openings without too much increasing of the load over the cladding system structures Trapezoidal sheets are specifically a good alternative to close this kind of structures The opening span that this kind of sheet is able to cover can be determined through the serviceability displacement limit state. Since the steel sheet cross-sectional elements have little thickness, the local buckling collapse modes Must be considered In this calculus. With this study. we attempt to evaluate the best alternatives for trapezoidal-shaped cross-sections of steel sheets to be used in roof cladding. subjected to bending moments. The sheets analysis has been carried out by using three-dimensional shell finite element models combined with optimization routines based on genetic algorithms procedures The first profile to be obtained has been the one that has showed the lowest displacement and the highest critical elastic buckling load. at the same time maximizing the roof covering area Finally, as a result of a sensitivity analysis, it has been possible to state some useful criteria for the trapezoidal steel roofing sheets design by modifying the weights of the proposed optimization objectives (C) 2009 Elsevier Ltd All rights reserved.

关键词： Trapezoidal roofing sheets Optimization genetics algorithms

来源：评论

学校读者我要写书评

暂无评论

A Multi-objective Approach for Optimized Monitoring of Voltage Sags in Distribution Systems

引用

JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS 2018年第3期29卷 371-380页

作者： Carneiro, Savio Mota Lira Rabelo, Ricardo de Andrade Galvao Castelo Branco, Hermes Manoel Univ Fed Piaui Dept Comp Sci Teresina Piaui Brazil Univ Estadual Piaui Dept Elect Engn Teresina Piaui Brazil

Voltage sags are among the most relevant power quality disturbances. Furthermore, they also have high occurrence rates. Their stochastic nature makes monitoring difficult and causes significant losses to power utilities and customers. This paper presents an approach to overcome the problem of allocating power quality monitors. To do so, our approach accounts for topological coverage, unmonitored voltage sags, and the total cost of required equipment. We used NSGA-II to build our approach due to its efficiency in dealing with combinatorial problems. We also used the Monte Carlo simulation method to model the time series in our approach due to the random nature of power quality disturbances. To evaluate our approach, we simulated the IEEE 13-, 34- and 37-bus distribution systems using the DigSILENT Power Factory 15.1 software. The evaluation results show that our approach supported cost reduction associated with the installation of power quality monitors, both in terms of identifying adequate number and position of the performance monitors.

关键词： genetics algorithms Monitors allocation Monte Carlo method Power quality

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：