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Bulanık çıkarım sistemlerinde kullanılan küme sayılarının K-ortalamalar ile belirlenmesi ve baraj hacmi modellenmesi: Kestel barajı örneği

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TLDR
In this article, the authors used an ANFIS model to estimate monthly volumes by using the data of 1986-2008 for Sandikli Kestel dam, where the number of clusters used for the inputs was obtained by the method of K-means.
Abstract
Correct planning of water resources is important for the efficient use of rapidly decreasing water resources in the future. Flow modeling and flow estimations in the planning of water resource are the basis of studies. In this study, it is aimed to estimate monthly volumes by using ANFIS model based on the data of 1986-2008 for Sandikli Kestel dam. In the system, the volume of the previous months, the volume of the incoming and outgoing volumes and the amount of evaporation were used as input variables. In ANFIS method, the number of clusters used for the inputs was obtained by the method of K-means. Different clusters formed by K-averages were modeled in ANFIS and the results were compared. The optimal number of clusters for each input value is determined. Models have been established in this way. As a result, it has been found that the models made according to the optimal number of clusters yield results with lower error percentage compared to randomly generated models.

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Journal ArticleDOI

Application of artificial neural networks to predict the heavy metal contamination in the Bartin River.

TL;DR: It can be inferred that the heavy metal contents can be estimated approximately with artificial intelligence models and relatively easy-to-measure parameters; it will be possible to detect heavy metals which are harmful to the viability of the rivers, both quickly and economically.

Zaman Serileri Kullanılarak Nehir Akım Tahmini ve Farklı Yöntemlerle Karşılaştırılması

TL;DR: Insan hayatinin devam ettirilmesi ve refah seviyesinin arttirilemasi icin su kaynaklari buyuk onem arz etmektedir as discussed by the authors.
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Uzun-Kısa Süreli Bellek Ağlarının Nehir Akım Tahmininde Farklı Optimizasyonlarla Karşılaştırılması Ve Tekil Spektrum Analizinin Etkisi

TL;DR: In this article, the performance effect of Single Spectrum Analysis (TSA) on Long Short Term Memory (LSTM) neural network was examined for estimating Aksu River flows.
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Nehir Akımlarının Derin Öğrenme ile Tahmini ve Akımların Demiryolları Güzergahına etkisi

TL;DR: In this article, Goksu Nehri uzerindeki D21A183 No’lu Asagicoplu koyu, Akdere AGI den elde edilen gunluk akim verileri uzerINDe, Derin Ogrenme Modeli olusturularak, modelin performansini analiz edilmistir.
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Anfis İle İlgili Yapılmış Çalışmaların İçerik Analizi İle Değerlendirilmesi: Tr Dizin

TL;DR: In this paper , TR Dizin kapsamında yer alan dergilerde yayınlanmış ANFIS ile ilgili yapılmıss çalışmalarının analizini veri normalizasyonu, verinin eğitim ve test için ayrılması ile performans ölçümünde kullanılan metrikler, olduğu tespit edilmiştir.
References
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Some methods for classification and analysis of multivariate observations

TL;DR: The k-means algorithm as mentioned in this paper partitions an N-dimensional population into k sets on the basis of a sample, which is a generalization of the ordinary sample mean, and it is shown to give partitions which are reasonably efficient in the sense of within-class variance.
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ANFIS: adaptive-network-based fuzzy inference system

TL;DR: The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy inference system) is presented, which is a fuzzy inference System implemented in the framework of adaptive networks.
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Survey of clustering algorithms

TL;DR: Clustering algorithms for data sets appearing in statistics, computer science, and machine learning are surveyed, and their applications in some benchmark data sets, the traveling salesman problem, and bioinformatics, a new field attracting intensive efforts are illustrated.
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Clustering algorithms: on learning, validation, performance, and applications to genomics.

TL;DR: The theoretical aspects of clustering are covered, including error and learning, followed by an overview of popular clustering algorithms and classical validation indices, which discuss the relative performance of these algorithms and indices and conclude with examples of the application of clusters to computational biology.
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Adaptive neuro fuzzy inference system approach for municipal water consumption modeling: An application to Izmir, Turkey

TL;DR: In this paper, an adaptive neuro fuzzy inference system (ANFIS) is used to forecast monthly water use from several socioeconomic and climatic factors including average monthly water bill, population, number of households, gross national product, monthly average temperature observed, monthly total rainfall, and monthly average humidity observed and inflation rate.