1,720,953 research outputs found
Prediction of solar energy control system based on machine learning method
Get PDFAccurate solar energy generation prediction is critical for optimizing energy management
and promoting the shift to renewable energy sources. In this research, we use real-world
datasets from solar power plants to train several machine learning models to predict solar
energy generation. Solar power generating data, weather sensor data, and auxiliary
information are among the databases. We anticipate solar energy generation for various time
intervals using machine learning methods such as Linear Regression (LR), Random Forest
(RF), Decision Tree (DT), Gradient Boosting Regressor (GBR), AdaBoost Regressor
(ADBR), and K-Nearest Neighbours (KNN). Our approach entails training these models on
historical data and assessing their performance on test datasets. The findings of this study
suggest that machine learning models have promising prediction skills. The R-squared (R2)
values for the training and testing datasets demonstrate a good capacity to explain variation
in solar energy generation. The DT model, for example, achieved a flawless R2 score of
100% for training datasets and 99.999% for testing datasets. The GBR model came in
second, with R2 values of 99.997% for both training and testing. Furthermore, the Root
Mean Squared Error (RMSE) values for the GBR model ranged from 1.87 to 109.53 for the
KNN model, demonstrating varying degrees of prediction accuracy. In comparison to
previous research investigations, our suggested machine learning models regularly show
superior prediction accuracy, with R2 scores reaching 99.99% or higher, compared to the
best score of 94.50% in previous studies. This study not only advances solar energy prediction using machine learning, but it also highlights the potential of these models in
optimizing energy management systems.Doğru güneş enerjisi üretimi tahmini, enerji yönetimini optimize etmek ve yenilenebilir
enerji kaynaklarına geçişi teşvik etmek için kritik öneme sahiptir. Bu araştırmada, güneş
enerjisi üretimini tahmin etmek amacıyla çeşitli makine öğrenimi modellerini eğitmek için
güneş enerjisi santrallerinden gerçek dünya veri kümelerini kullanıyoruz. Veritabanları
arasında güneş enerjisi üreten veriler, hava durumu sensörü verileri ve yardımcı bilgiler yer
almaktadır. Doğrusal Regresyon (LR), Rastgele Orman (RF), Karar Ağacı (DT), Gradient
Boosting Regressor (GBR), AdaBoost Regressor (ADBR) ve K-Nearest gibi makine
öğrenme yöntemlerini kullanarak çeşitli zaman aralıklarında güneş enerjisi üretimini
öngörüyoruz. Komşular (KNN). Yaklaşımımız, bu modellerin geçmiş veriler üzerinde
eğitilmesini ve performanslarının test veri kümeleri üzerinde değerlendirilmesini gerektirir.
Bu çalışmanın bulguları, makine öğrenimi modellerinin umut verici tahmin becerilerine
sahip olduğunu göstermektedir. Eğitim ve test veri kümelerinin R-kare (R2) değerleri, güneş
enerjisi üretimindeki değişimi açıklamak için iyi bir kapasite göstermektedir. Örneğin DT
modeli, eğitim veri kümeleri için %100 ve veri kümelerini test etmek için %99,999'luk
kusursuz bir R2 puanı elde etti. GBR modeli, hem eğitim hem de test için %99,997'lik R2
değerleriyle ikinci sırada yer aldı. Ayrıca, GBR modeli için Ortalama Karekök Hata (RMSE)
değerleri, KNN modeli için 1,87 ile 109,53 arasında değişiyordu ve bu da tahmin
doğruluğunun değişen derecelerini gösteriyordu. Önceki araştırma araştırmalarıyla
karşılaştırıldığında, önerilen makine öğrenimi modellerimiz düzenli olarak üstün tahmin
doğruluğu göstermektedir; önceki çalışmalardaki en iyi puan olan %94,50'ye kıyasla R2 puanları %99,99 veya daha yükseğe ulaşmaktadır. Bu çalışma yalnızca makine öğrenimini
kullanarak güneş enerjisi tahminini geliştirmekle kalmıyor, aynı zamanda bu modellerin
enerji yönetimi sistemlerini optimize etme potansiyelini de vurguluyor
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Author Under Sail The Imagination of Jack London, 1893-1902
No full textIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
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