Bölgesel veriler üzerinde yapilan kisa dönem su talep tahmini

Tugba Zeynep Yildiz; Tevfik Aytekin

doi:10.1109/SIU.2019.8806415

Bölgesel veriler üzerinde yapilan kisa dönem su talep tahmini

Tugba Zeynep Yildiz, Tevfik Aytekin

Araştırma sonucu: Kitap/Rapor/Konferans sürecindeki bölüm › Konferans katkısı › bilirkişi

Özet

Limited water resources and changing climatic conditions make water one of the critical natural resources. In order to manage this limited resource in the most effective way, real-time monitoring and automatic control systems are becoming increasingly popular. Water demand forecasting is one of the important subjects in these studies. Accurate water demand forecasting increases efficiency in the management of water networks and also allows for leak/fraud detection. In this work, we carry out short term water demand forecasting using water consumption data collected from water meters in a regional area. For forecasting, we first clean water consumption data, extract various features and apply machine learning methods for forecasting. After giving the experimental results we discuss future improvements.

Tercüme edilen katkı başlığı	Short term water demand forecasting using regional data
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	27th Signal Processing and Communications Applications Conference, SIU 2019
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)	9781728119045
DOI'lar	https://doi.org/10.1109/SIU.2019.8806415
Yayın durumu	Yayınlanan - Nis 2019
Harici olarak yayınlandı	Evet
Etkinlik	27th Signal Processing and Communications Applications Conference, SIU 2019 - Sivas, Turkey Süre: 24 Nis 2019 → 26 Nis 2019

Yayın serisi

Adı	27th Signal Processing and Communications Applications Conference, SIU 2019

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	27th Signal Processing and Communications Applications Conference, SIU 2019
Ülke/Bölge	Turkey
Şehir	Sivas
Periyot	24/04/19 → 26/04/19

Keywords

Feature extraction
Machine learning
Water demand forecasting

BM SKH

Bu sonuç, aşağıdaki Sürdürülebilir Kalkınma Hedefine/Hedeflerine katkıda bulunur

Belgeye Erişim

10.1109/SIU.2019.8806415

Diger dosyalar ve linkler

Link to publication in Scopus

Bundan alıntı yap

Zeynep Yildiz, T., & Aytekin, T. (2019). Bölgesel veriler üzerinde yapilan kisa dönem su talep tahmini. In 27th Signal Processing and Communications Applications Conference, SIU 2019 Makale 8806415 (27th Signal Processing and Communications Applications Conference, SIU 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU.2019.8806415

@inproceedings{061e7c1de002428c95c77125c6a0f912,

title = "B{\"o}lgesel veriler {\"u}zerinde yapilan kisa d{\"o}nem su talep tahmini",

abstract = "Limited water resources and changing climatic conditions make water one of the critical natural resources. In order to manage this limited resource in the most effective way, real-time monitoring and automatic control systems are becoming increasingly popular. Water demand forecasting is one of the important subjects in these studies. Accurate water demand forecasting increases efficiency in the management of water networks and also allows for leak/fraud detection. In this work, we carry out short term water demand forecasting using water consumption data collected from water meters in a regional area. For forecasting, we first clean water consumption data, extract various features and apply machine learning methods for forecasting. After giving the experimental results we discuss future improvements.",

keywords = "Feature extraction, Machine learning, Water demand forecasting",

author = "{Zeynep Yildiz}, Tugba and Tevfik Aytekin",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 27th Signal Processing and Communications Applications Conference, SIU 2019 ; Conference date: 24-04-2019 Through 26-04-2019",

year = "2019",

month = apr,

doi = "10.1109/SIU.2019.8806415",

language = "T{\"u}rk{\c c}e",

series = "27th Signal Processing and Communications Applications Conference, SIU 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "27th Signal Processing and Communications Applications Conference, SIU 2019",

}

Zeynep Yildiz, T & Aytekin, T 2019, Bölgesel veriler üzerinde yapilan kisa dönem su talep tahmini. in 27th Signal Processing and Communications Applications Conference, SIU 2019., 8806415, 27th Signal Processing and Communications Applications Conference, SIU 2019, Institute of Electrical and Electronics Engineers Inc., 27th Signal Processing and Communications Applications Conference, SIU 2019, Sivas, Turkey, 24/04/19. https://doi.org/10.1109/SIU.2019.8806415

Bölgesel veriler üzerinde yapilan kisa dönem su talep tahmini. / Zeynep Yildiz, Tugba; Aytekin, Tevfik.
27th Signal Processing and Communications Applications Conference, SIU 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8806415 (27th Signal Processing and Communications Applications Conference, SIU 2019).

Araştırma sonucu: Kitap/Rapor/Konferans sürecindeki bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Bölgesel veriler üzerinde yapilan kisa dönem su talep tahmini

AU - Zeynep Yildiz, Tugba

AU - Aytekin, Tevfik

PY - 2019/4

Y1 - 2019/4

N2 - Limited water resources and changing climatic conditions make water one of the critical natural resources. In order to manage this limited resource in the most effective way, real-time monitoring and automatic control systems are becoming increasingly popular. Water demand forecasting is one of the important subjects in these studies. Accurate water demand forecasting increases efficiency in the management of water networks and also allows for leak/fraud detection. In this work, we carry out short term water demand forecasting using water consumption data collected from water meters in a regional area. For forecasting, we first clean water consumption data, extract various features and apply machine learning methods for forecasting. After giving the experimental results we discuss future improvements.

AB - Limited water resources and changing climatic conditions make water one of the critical natural resources. In order to manage this limited resource in the most effective way, real-time monitoring and automatic control systems are becoming increasingly popular. Water demand forecasting is one of the important subjects in these studies. Accurate water demand forecasting increases efficiency in the management of water networks and also allows for leak/fraud detection. In this work, we carry out short term water demand forecasting using water consumption data collected from water meters in a regional area. For forecasting, we first clean water consumption data, extract various features and apply machine learning methods for forecasting. After giving the experimental results we discuss future improvements.

KW - Feature extraction

KW - Machine learning

KW - Water demand forecasting

UR - http://www.scopus.com/inward/record.url?scp=85071973162&partnerID=8YFLogxK

U2 - 10.1109/SIU.2019.8806415

DO - 10.1109/SIU.2019.8806415

M3 - Konferans katkısı

AN - SCOPUS:85071973162

T3 - 27th Signal Processing and Communications Applications Conference, SIU 2019

BT - 27th Signal Processing and Communications Applications Conference, SIU 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 27th Signal Processing and Communications Applications Conference, SIU 2019

Y2 - 24 April 2019 through 26 April 2019

ER -

Bölgesel veriler üzerinde yapilan kisa dönem su talep tahmini

Özet

Yayın serisi

???event.eventtypes.event.conference???

Keywords

BM SKH

Belgeye Erişim

Diger dosyalar ve linkler

Parmak izi

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