Asosiy kontentga oʻtish
AkademScholar

Kashfiyot

Xizmatlar

Identifikatsiya

Ishlab chiquvchilar uchun

Ekotizim

Muassasalar

OsloMet – Oslo Metropolitan University

Nom variantlari: HiOA · Høgskolen i Oslo og Akershus · Oslo Metropolitan University · Oslo and Akershus University College of Applied Sciences · OsloMet – storbyuniversitetet

Davlat:
NO
ROR:
https://ror.org/04q12yn84
3
h-indeks
28
Iqtiboslar
16
Asarlar
16
Mualliflar
Vaqt boʻyicha

Vaqt boʻyicha tahlil

Iqtibos sharhi

Yillar boʻyicha nashrlar (ustun) va iqtiboslar (chiziq)

  • Nashrlar
  • Iqtiboslar
013450358102017201820202021202220232024202520262017: Nashrlar 1, Iqtiboslar 02018: Nashrlar 2, Iqtiboslar 02020: Nashrlar 2, Iqtiboslar 02021: Nashrlar 5, Iqtiboslar 22022: Nashrlar 1, Iqtiboslar 72023: Nashrlar 0, Iqtiboslar 22024: Nashrlar 0, Iqtiboslar 62025: Nashrlar 3, Iqtiboslar 52026: Nashrlar 2, Iqtiboslar 6

Iqtibos tarixi

0358102017201820202021202220232024202520262017: Iqtiboslar 02018: Iqtiboslar 02020: Iqtiboslar 02021: Iqtiboslar 22022: Iqtiboslar 72023: Iqtiboslar 22024: Iqtiboslar 62025: Iqtiboslar 52026: Iqtiboslar 6

Nashr tarixi

013452017201820202021202220232024202520262017: Nashrlar 12018: Nashrlar 22020: Nashrlar 22021: Nashrlar 52022: Nashrlar 12023: Nashrlar 02024: Nashrlar 02025: Nashrlar 32026: Nashrlar 2

h-indeks evolyutsiyasi

Yillar boʻyicha jamlangan h-indeks

013452017201820202021202220232024202520262017: h-indeks 02018: h-indeks 02020: h-indeks 02021: h-indeks 12022: h-indeks 22023: h-indeks 22024: h-indeks 22025: h-indeks 22026: h-indeks 3

Eng koʻp iqtibos qilingan asarlar

  1. Advanced Techniques for Electricity Consumption Prediction in Buildings Using Comparative Correlation Analysis, Data Normalization, and Long Short-Term Memory (Lstm) Networks: A Case Study of a U.S. Commercial Building20250 iqtibos
  2. Electricity Demand Forecasting for Cultural Institutions: A Comparative Study of Lstm and Cnn-Lstm Models with Three Data Normalization Techniques Using Weather and Price Data – Case Studies from Norwegian Museums20250 iqtibos
  3. Energy Demand Forecasting for Cultural Institutions: Comparative Analysis of ANNs, Ordinary LSTM, and Hybrid CNN-LSTM Models with Three Normalization Techniques Using Weather and Price Data – Case Studies from Norwegian Museums20250 iqtibos
  4. Dynamic Energy Demand Forecasting in a Norwegian Commercial Store Using Local Building Time-Series Data: CNN-LSTM and Transformer Architectures Compared20260 iqtibos
  5. A Systematic Review of Comparative Analysis of Machine Learning Models for Predicting Heating Demand and Electricity Usage with Weather Data in Buildings: Two Case Studies in Norway20260 iqtibos