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RNN-GWR: A geographically weighted regression approach for frequently updated data

Neurocomputing (Amsterdam), 2020-07, Vol.399, p.258-270

2020

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Mining High-Average Utility Itemsets with Positive and Negative External Utilities

New generation computing, 2020-03, Vol.38 (1), p.153-186

2020

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An Efficient Tree Based Algorithm for Mining High Average-Utility Itemset

IEEE access, 2019-01, Vol.7, p.1-1

2019

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Multi fragment melting analysis system (MFMAS) for one-step identification of lactobacilli

Journal of microbiological methods, 2020-10, Vol.177, p.106045-106045, Article 106045

2020

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An overview of the activation functions used in deep learning algorithms

Journal of New Results in Science, 2021-12, Vol.10 (3), p.75-88

2021

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Modelling surface water-groundwater interactions at the Palas Basin (Turkey) using FREEWAT

Acque Sotterranee, 2017-09, Vol.6 (3)

2017

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RSigELU: A nonlinear activation function for deep neural networks

Expert systems with applications, 2021-07, Vol.174, p.114805, Article 114805

2021

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BULUT BİLİŞİM SİSTEMLERİNDE VERİNİN FARKLI BOYUTLARI ÜZERİNE DERLEME

Niğde Ömer Halisdemir Üniversitesi mühendislik bilimleri dergisi, 2017-07, Vol.6 (2), p.316-338

2017

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4D-GWR: geographically, altitudinal, and temporally weighted regression

Neural computing & applications, 2022-09, Vol.34 (17), p.14777-14791

2022

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Assessment of Multi Fragment Melting Analysis System (MFMAS) for the Identification of Food-Borne Yeasts

Current microbiology, 2018-06, Vol.75 (6), p.716-725

2018

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Partial spatio-temporal co-occurrence pattern mining

Knowledge and information systems, 2015-07, Vol.44 (1), p.27-49

Celik, Mete

2015

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KAF + RSigELU: a nonlinear and kernel-based activation function for deep neural networks

Neural computing & applications, 2022-08, Vol.34 (16), p.13909-13923

2022

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Diagnosis and classification of cancer using hybrid model based on ReliefF and convolutional neural network

Medical hypotheses, 2020-04, Vol.137, p.109577-109577, Article 109577

2020

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Convolutional neural network analysis of recurrence plots for high resolution melting classification

Computer methods and programs in biomedicine, 2021-08, Vol.207, p.106139-106139, Article 106139

2021

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Discovering socially similar users in social media datasets based on their socially important locations

Information processing & management, 2018-11, Vol.54 (6), p.1154-1168

2018

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A hybrid CNN-LSTM model for high resolution melting curve classification

Biomedical signal processing and control, 2022-01, Vol.71, p.103168, Article 103168

2022

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Discovering socially important locations of social media users

Expert systems with applications, 2017-11, Vol.86, p.113-124

2017

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Spatial AutoRegression (SAR) Model: Parameter Estimation Techniques

1. Aufl., 2012

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Discovery of hydrometeorological patterns

Elektrik : Turkish journal of electrical engineering & computer sciences, 2014, Vol.22, p.840-857

2014

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Reservoir volume forecasting using artificial intelligence-based models: Artificial Neural Networks, Support Vector Regression, and Long Short-Term Memory

Journal of hydrology (Amsterdam), 2023-01, Vol.616, p.128766, Article 128766

2023

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Hybrid models based on genetic algorithm and deep learning algorithms for nutritional Anemia disease classification

Biomedical signal processing and control, 2021-01, Vol.63, p.102231, Article 102231

2021

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Parametric RSigELU: a new trainable activation function for deep learning

Neural computing & applications, 2024-05, Vol.36 (13), p.7595-7607

2024

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Boyut İndirgeme Teknikleri ve LSTM Derin Öğrenme Ağı İle BIST100 Endeksi Fiyat Tahmini

European Journal of Science and Technology, 2022-03

2022

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A Hybrid Validity Index to Determine K Parameter Value of k-Means Algorithm for Time Series Clustering

International journal of information technology & decision making, 2021-11, Vol.20 (6), p.1615-1636

2021

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PCA-ICA-LSTM: A Hybrid Deep Learning Model Based on Dimension Reduction Methods to Predict S&P 500 Index Price

Computational economics, 2024-05

2024

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RNN-GWR: A geographically weighted regression approach for frequently updated data

Mining High-Average Utility Itemsets with Positive and Negative External Utilities

An Efficient Tree Based Algorithm for Mining High Average-Utility Itemset

Multi fragment melting analysis system (MFMAS) for one-step identification of lactobacilli

An overview of the activation functions used in deep learning algorithms

Modelling surface water-groundwater interactions at the Palas Basin (Turkey) using FREEWAT

RSigELU: A nonlinear activation function for deep neural networks

BULUT BİLİŞİM SİSTEMLERİNDE VERİNİN FARKLI BOYUTLARI ÜZERİNE DERLEME

4D-GWR: geographically, altitudinal, and temporally weighted regression

Assessment of Multi Fragment Melting Analysis System (MFMAS) for the Identification of Food-Borne Yeasts

Partial spatio-temporal co-occurrence pattern mining

KAF + RSigELU: a nonlinear and kernel-based activation function for deep neural networks

Diagnosis and classification of cancer using hybrid model based on ReliefF and convolutional neural network

Convolutional neural network analysis of recurrence plots for high resolution melting classification

Discovering socially similar users in social media datasets based on their socially important locations

A hybrid CNN-LSTM model for high resolution melting curve classification

Discovering socially important locations of social media users

Spatial AutoRegression (SAR) Model: Parameter Estimation Techniques

Discovery of hydrometeorological patterns

Reservoir volume forecasting using artificial intelligence-based models: Artificial Neural Networks, Support Vector Regression, and Long Short-Term Memory

Hybrid models based on genetic algorithm and deep learning algorithms for nutritional Anemia disease classification

Parametric RSigELU: a new trainable activation function for deep learning

Boyut İndirgeme Teknikleri ve LSTM Derin Öğrenme Ağı İle BIST100 Endeksi Fiyat Tahmini

A Hybrid Validity Index to Determine K Parameter Value of k-Means Algorithm for Time Series Clustering

PCA-ICA-LSTM: A Hybrid Deep Learning Model Based on Dimension Reduction Methods to Predict S&P 500 Index Price

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