1,720,959 research outputs found
Modeling Civil Engineering Problems Via Hybrid Versions Of Machine Learning And Metaheuristic Optimization Algorithms
No full textSpringer Science and Business Media Deutschland GmbHThe aim of this study is to develop hybrid solution models by integrating metaheuristic optimization algorithms and machine learning technique. These hybrid models are utilized to estimate bearing capacity of pile groups and lake levels, which are common challenges to calculate in the geotechnical and hydrology designs of civil engineering. To achieve this, Lake Beyşehir lake-water level observations and various pile group designs are used as a dataset, which is divided into two parts; 75 for training and 25 for testing. By employing improved hybrid models that combine metaheuristic algorithms such as harmony search, artificial bee colony, and particle swarm optimization with a machine learning technique called least squares support vector regression (LSSVR), optimal values of kernel parameters are obtained reliably and robustly. The results suggest that these hybrid models can be successfully applied to complex real-world problems, as evidenced by nine evaluation metrics, including mean absolute error (MAE), root mean squared error (RMSE), and determination coefficient (R2), which showed satisfactory and reasonable performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Forecasting Of Lake Level By Soft Computing Approaches
No full textSpringer Science and Business Media Deutschland GmbHTo ensure the sustainability and management of water resources, regularly monitoring the water levels in lakes, rivers, basins, dam reservoirs, etc. is a very important engineering task. Our freshwater resources are gradually decreasing due to the destruction of freshwater resources and climate change. For this reason, monitoring, modelling, and researching of freshwater resources, especially lakes, are increasingly important issue for nowadays. In this chapter, soft computing approaches are used to forecast of lake water levels at Beyşehir Lake, located in the central part of Turkey. To do this, three artificial neural network algorithms (Multilayer, Radial Basis and Generalized Regression), two heuristic algorithms (Model 5-Tree and Multivariate Adaptive Regression Spline), and a Support Vector Machines containing three different functions (Radial, Polynomial, and Linear) are used. In addition to being models used successfully in hydrological modelling of civil engineering, the changes in modelling performance with the number of iterations, kernel functions, optimization algorithms, and data input sets that constitute the internal dynamite of the techniques are investigated. The attained results show that through these multiple parameters, radial basis artificial neural networks are the most successful when compared with mean absolute error, root mean square error, coefficient of determination, Taylor diagrams and Violin plots. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Numerical design optimization of real size complex steel space frame structures using a novel adaptive cuckoo search method
No full textIn this study, real size complex steel space frame structures are numerically designed to achieve optimal design weight. For this aim, standard cuckoo search algorithm is rectified through a newly proposed adaptive method over two fundamental algorithmic parameters of alien egg probability detection (Pa) and step size control (alpha) to overcome incompetency of trapping into local optima. Besides, to strengthen exploitation phase of newly proposed algorithm, it is boosted with greedy selection (GS). So, novel algorithm has more promising exploration and exploitation capabilities. An 8-story, 1024-member and a 20-story, 1860-member real size complex steel space frame structures are selected as design examples. Also, initially to verify the supremacy of novel algorithm, a well-known welded beam is optimized as a benchmark structural design problem. Afterwards, the steel space frame structures are optimally designed via novel algorithm. Since ready steel section lists are utilized as selection pool for design variables, discrete programming problem is come into existence. The dead, live, snow, and wind design loads acting on frame structures are calculated in direction of ASCE 7-05 provisions. Furthermore, the structural design constraints are determined from LRFD-AISC specifications. Eventually, the newly proposed adaptive cuckoo search algorithm boosted with GS presents outstanding algorithmic performance.Turkiye Bilimsel ve Teknolojik Arastirma KurumuTurkiye Bilimsel ve Teknolojik Arastirma Kurum
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