检索结果-内蒙古大学图书馆

ELEKTROTEHNISKI VESTNIK 2022年第1-2期89卷 46-52页

作者： Ravber, Miha Moravec, Matej Mernik, Marjan Univ Maribor Fak Elektrotehn Racunalnistvo Informat Koroska Cesta 46 Maribor 2000 Slovenia

The performance of the evolutionary algorithms is assessed by comparing them with the existing algorithms. comparison of the evolutionary algorithms in the literature plays a key role as it illustrates which algorithms are better. It is a common practice to simply take the results from the papers of the algorithms you are comparing your proposed algorithm to. However, it is not guaranteed that the experiments are performed in accordance with the guidelines for a fair comparison. Since a correct execution of an experiment is crucial to be able to state with a certainty the superiority of evolutionary algorithms, it is recommended that the experiment is repeated. This, however, can be a challenge if the source code of the algorithm is not available or it needs to be implemented in another programming language. Such approach can lead to misleading results due to the unintentional mistakes made in implementing the algorithm. Another factor that is often overlooked are the differences between the programming languages in which the algorithm is implemented. The problem is highlighted by analyzing and comparing the performance of the GWO algorithm implemented in six programming languages.

关键词： evolutionary algorithms grey wolf optimizer comparison of algorithms algorithms performance

来源：评论

学校读者我要写书评

暂无评论

comparison of Evolutionary algorithms for Estimation of Parameters of the Equivalent Circuit of an AC Motor 1

Comparison of Evolutionary Algorithms for Estimation of Para...

引用

1st IEEE Colombian Conference on Applications in Computational Intelligence (ColCACI)

作者： Ramos, Guillermo A. Lopez, Jesus A. Serv Nacl Aprendizaje SENA Cali Colombia Univ Autonoma Occidente Dept Automat & Elect Cali Colombia

ISBN: (纸本)9781538667408

This work shows the comparison among three evolutionary algorithms used to estimate the parameters of the equivalent circuit of a three-phase induction motor. With the parameters of the motor is possible to calculate its efficiency. Applying statistical methods, the number of runs needed to obtain a confidence level of 95% is calculated. With this value each algorithm is used to estimate the motor's parameters and, according to the results, is possible to find the best

关键词： Evolutionary algorithms Estimation of Parameters AC motor comparison of algorithms

来源：评论

学校读者我要写书评

暂无评论

MACHINE LEARNING FOR OCCUPATION CODING-A comparison STUDY

引用

JOURNAL OF SURVEY STATISTICS AND METHODOLOGY 2021年第5期9卷 1013-1034页

作者： Schierholz, Malte Schonlau, Matthias Inst Employment Res IAB Regensburger Str 104 D-90478 Nurnberg Germany Univ Waterloo 200 Univ Ave West Waterloo ON N2L 3G1 Canada

Asking people about their occupation is common practice in surveys and censuses around the world. The answers are typically recorded in textual form and subsequently assigned (coded) to categories, which have been defined in official occupational classifications. While this coding step is often done manually, substituting it with more automated workflows has been a longstanding goal, promising reduced data-processing costs and accelerated publication of key statistics. Although numerous researchers have developed different algorithms for automated occupation coding, the algorithms have rarely been compared with each other or tested on different data sets. We fill this gap by comparing some of the most promising algorithms found in the literature and testing them on five data sets from Germany. The first two algorithms we test exemplify a common practice in which answers are coded automatically according to a predefined list of job titles. Statistical learning algorithms-that is, regularized multinomial regression, tree boosting, or algorithms developed specifically for occupation coding (algorithms three to six)-can improve upon algorithms one and two, but only if a sufficient number of training observations from previous surveys is available. The best results are obtained by merging the list of job titles with coded answers from previous surveys before using this combined training data for statistical learning (algorithm 7). However, the differences between the algorithms are often small compared to the large variation found across different data sets, which we ascribe to systematic differences in the way the data were coded in the first place. Such differences complicate the application of statistical learning, which risks perpetuating questionable coding decisions from the training data to the future.

关键词： Coding comparison of algorithms Data processing Machine learning Occupation Statistical learning

来源：评论

学校读者我要写书评

暂无评论

Understanding the merits of winning data competition solutions for varied sets of objectives

引用

STATISTICAL ANALYSIS AND DATA MINING 2021年第6期14卷 556-574页

作者： Lu, Lu Anderson-Cook, Christine M. Zhang, Miaolu Univ S Florida Tampa FL USA Los Alamos Natl Lab Los Alamos NM USA

Data competitions provide an efficient cost-effective way to obtain diverse solutions for challenging problems across a wide variety of applications. The competition leaderboard, by necessity, must combine multiple objectives into a single scoring formula to determine winners and allocate prize money. However, after the competition concludes, the host may wish to choose a best solution for a particular scenario that focuses on only a subset of all the competition objectives. Through the use of Pareto fronts and graphical summaries, we describe how top solutions for a specific scenario can be identified and compared. The strategy uses intentional tie-handling, thresholds to eliminate undesirable solutions and Pareto fronts to identify objectively superior solutions for a subset of objectives. Then the strengths and weaknesses of different alternatives can be compared to find the ideal solution for the problem. The methods are illustrated with a real Topcoder data competition hosted by Los Alamos National Laboratory that used 16 different objectives to evaluate the quality of solutions for urban radiation search.

关键词： comparison of algorithms data competitions graphical summaries multi-objective optimization objective versus subjective Pareto fronts

来源：评论

学校读者我要写书评

暂无评论

Improved online algorithms for jumbled matching

引用

DISCRETE APPLIED MATHEMATICS 2020年 274卷 54-66页

作者： Ghuman, Sukhpal Singh Tarhio, Jorma Chhabra, Tamanna Sheridan Coll Fac Appl Sci & Technol 7899 McLaughlin Rd Brampton ON L6Y 5H9 Canada Aalto Univ Dept Comp Sci POB 15400 FI-00076 Aalto Finland Seneca Coll 70 Pond Rd Toronto ON M3J 3M6 Canada

We consider the problem of jumbled matching where the objective is to find all permuted occurrences of a pattern in a text. Besides exact matching we study approximate matching where each occurrence is allowed to contain at most k wrong or superfluous characters. We present online algorithms applying bit-parallelism to both types of jumbled matching. Two of our algorithms are filtration methods applying SIMD (Single Instruction Multiple Data) computation. Most of the other new algorithms are variations of earlier methods. We show by practical experiments that our algorithms are competitive with previous solutions. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Jumbled matching Abelian matching Approximate string matching SIMD computation comparison of algorithms Algorithm engineering

来源：评论

学校读者我要写书评

暂无评论

Performance comparison of Machine Learning Platforms

引用

INFORMS JOURNAL ON COMPUTING 2019年第2期31卷 207-225页

作者： Roy, Asim Qureshi, Shiban Pande, Kartikeya Nair, Divitha Gairola, Kartik Jain, Pooja Singh, Suraj Sharma, Kirti Jagadale, Akshay Lin, Yi-Yang Sharma, Shashank Gotety, Ramya Zhang, Yuexin Tang, Ji Mehta, Tejas Sindhanuru, Hemanth Okafor, Nonso Das, Santak Gopal, Chidambara N. Rudraraju, Srinivasa B. Kakarlapudia, Avinash, V Arizona State Univ Dept Informat Syst Tempe AZ 85287 USA

In this paper, we present a method for comparing and evaluating different collections of machine learning algorithms on the basis of a given performance measure (e.g., accuracy, area under the curve (AUC), F-score). Such a method can be used to compare standard machine learning platforms such as SAS, IBM SPSS, and Microsoft Azure ML. A recent trend in automation of machine learning is to exercise a collection of machine learning algorithms on a particular problem and then use the best performing algorithm. Thus, the proposed method can also be used to compare and evaluate different collections of algorithms for automation on a certain problem type and find the best collection. In the study reported here, we applied the method to compare six machine learning platforms - R, Python, SAS, IBM SPSS Modeler, Microsoft Azure ML, and Apache Spark ML. We compared the platforms on the basis of predictive performance on classification problems because a significant majority of the problems in machine learning are of that type. The general question that we addressed is the following: Are there platforms that are superior to others on some particular performance measure? For each platform, we used a collection of six classification algorithms from the following six families of algorithms - support vector machines, multilayer perceptrons, random forest (or variant), decision trees/ gradient boosted trees, Naive Bayes/Bayesian networks, and logistic regression. We compared their performance on the basis of classification accuracy, F-score, and AUC. We used F-score and AUC measures to compare platforms on two-class problems only. For testing the platforms, we used a mix of data sets from (1) the University of California, Irvine (UCI) library, (2) the Kaggle competition library, and (3) high-dimensional gene expression problems. We performed some hyperparameter tuning on algorithms wherever possible.

关键词： machine learning platforms classification algorithms comparison of algorithms comparison of platforms

来源：评论

学校读者我要写书评

暂无评论

Sensitivity analysis and comparison of algorithms in preventive maintenance and replacement scheduling optimization models

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2011年第1期61卷 64-75页

作者： Moghaddam, Kamran S. Usher, John S. Univ Louisville Dept Ind Engn Louisville KY 40292 USA

In this research, new optimization models are developed to determine the optimal preventive maintenance and replacement schedules in repairable and maintainable systems. The objective is to determine a plan of actions for each component in the system while minimizing the total cost and maximizing overall system reliability over the planning horizon. Experimental results of a sensitivity analysis on the optimization models are presented and evaluated. These experiments investigate the effect of the parameters on the structure of optimal preventive maintenance and replacement schedules in multi-component systems. Two factorial design experiments based on the cost associated with maintenance and replacement activities and reliability characteristic parameters are constructed and analyzed. In addition, a comprehensive experiment is designed to analyze and compare the efficiency and accuracy of the exact and metaheuristic algorithms. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Preventive maintenance and replacement scheduling Optimization models Multi-component systems Sensitivity analysis comparison of algorithms

来源：评论

学校读者我要写书评

暂无评论

Niche Modelling: a comparison between modelling methods best applied for Cnidaria niche dispersion studies

Niche Modelling: a comparison between modelling methods best...

引用

作者： Lima, Alessandra Vallim Universidade Estadual Paulista

Recently, ecological niche modelling has been receiving more attention in several areas in biology, due to the evolution of personal computers, and the increasing availability of data used in modelling. The results obtained can be used in preventive actions such as species management and invasive species distribution. Since its increasing popularity, several algorithms are available and undergoing tests regarding their performance towards different phylum. Marine invertebrates, more specifically cnidarians, present few studies on this field, and should receive closer attention in the next years due to worldwide increases in jellyfish population (blooms), and bleaching in almost every known shallow water coral reef. Because of this gap of information, we chose this still poor studied group to compare three algorithms. We used MAXENT, GARP and AquaMaps in its desktop form and selected them based on other studies comparing algorithms. Our aim was to, based on different organisms of the phylum Cnidaria, Lychnorhiza lucerna, Chrysaora lactea, Phyllorhiza punctata, Tamoya haplonema, Ceriantheomorphe brasiliensis and Mussismilia hispida, compare those algorithms and examine which one performed the best. Our results shown that MAXENT outperformed the other algorithms both regarding de Area Under the ROC Curve (AUC) and the map distribution. GARP show varying results with generalized maps and AquaMaps was the least accurate of them. Our results are similar to those found in other papers, thus meaning that MAXENT is the most reliable software when it comes to modelling these *** ultimas décadas, modelagem de nicho ecológico vem recebendo maior atenção em diversas áreas da biologia devido a evolução dos computadores pessoais e aumento dos dados disponíveis utilizados para a modelagem. Os resultados obtidos podem ser utilizados em ações preventivas, tais quais manejo de espécie e acompanhamento da distribuição de espécies invasoras. Desde o aumento dessa popularidade, d

关键词： Niche Modelling Cnidaria comparison of algorithms Comparação de algoritmos Modelagem de Nicho Dissertação de mestrado

来源：评论

学校读者我要写书评

暂无评论

The Results of a Complex Analysis of the Modified Pratt-Yaskorskiy Performance Metrics Based on the Two-Dimensional Markov-Renewal-Process 8th

The Results of a Complex Analysis of the Modified Pratt-Yask...

引用

8th International Conference on Computational Collective Intelligence (ICCCI)

作者： Geringer, Viktor Dubinin, Dmitry Kochegurov, Alexander Baden Wuerttemberg Cooperat State Univ Fac Engn Friedrichshafen Germany Tomsk State Univ Control Syst & Radioelect Lenin Ave 40 Tomsk 634050 Russia Natl Res Tomsk Polytech Univ Lenin Ave 30 Tomsk 634050 Russia

ISBN: (纸本)9783319452425;9783319452432

The paper presents the results of a quantitative estimation of the edge detection quality using modified Pratt-Yaskorskiy criterion, as well as generalization and adaptation of both approaches based on the generalized quality criterion as part of "CS sF" stochastic simulation software package. The reference images are approximated by the two-dimensional high rise renewal stream offering the stationarity properties with no aftereffects and ordinariness. The efficiency of the proposed metrics is considered for three edging algorithms (Marr-Hildreth, ISEF and Canny) at different levels of the additive normal noise. The estimated errors of the first and second kind are given, which allow referring to the efficiency of the proposed generalized quality criterion.

关键词： Stochastic computer simulation Research on models Reference image Edge detection Quality metrics Performance evaluation comparison of algorithms

来源：评论

学校读者我要写书评

暂无评论

Preventive maintenance and replacement optimization on CNC machine using multiobjective evolutionary algorithms

引用

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2015年第9-12期76卷 2131-2146页

作者： Moghaddam, Kamran S. Calif State Univ Fresno Dept Informat Syst & Decis Sci Craig Sch Business Fresno CA 93740 USA

In this paper, a multiobjective optimization model is formulated to determine the optimal preventive maintenance plans for a repairable multicomponent manufacturing system with increasing rate of occurrence of failure. The operational planning horizon is segmented into discrete and equally sized periods, and in each period, three possible maintenance actions (repair, replacement, or do nothing) have been considered for each component. The developed multiobjective nonlinear mixed-integer programming model is then utilized to find the Pareto-optimal preventive maintenance schedules for a computer numerical control (CNC) machine. In order to obtain the Pareto-optimal solutions, five multiobjective evolutionary algorithms are considered, and computational performance of the algorithms is evaluated using different metrics. It is found that three of these algorithms outperform the others in obtaining more and high-quality nondominated preventive maintenance and replacement schedules along with maintaining high level of diversity among generated solutions. Such a modeling approach and the comparison of algorithms would be useful for maintenance planners tasked with the problem of developing optimal maintenance plans for multicomponent manufacturing machines.

关键词： Preventive maintenance and replacement optimization CNC machine Multiobjective evolutionary algorithms comparison of algorithms

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：