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Most Cited

  • Review
  • Open Access
68 Citations
39,659 Views
59 Pages

Comprehensive Review of Power Electronic Converters in Electric Vehicle Applications

  • Rejaul Islam,
  • S M Sajjad Hossain Rafin and
  • Osama A. Mohammed

29 December 2022

Emerging electric vehicle (EV) technology requires high-voltage energy storage systems, efficient electric motors, electrified power trains, and power converters. If we consider forecasts for EV demand and driving applications, this article comprehen...

  • Article
  • Open Access
57 Citations
7,082 Views
16 Pages

A Day-Ahead Photovoltaic Power Prediction via Transfer Learning and Deep Neural Networks

  • Seyed Mahdi Miraftabzadeh,
  • Cristian Giovanni Colombo,
  • Michela Longo and
  • Federica Foiadelli

17 February 2023

Climate change and global warming drive many governments and scientists to investigate new renewable and green energy sources. Special attention is on solar panel technology, since solar energy is considered one of the primary renewable sources and s...

  • Article
  • Open Access
56 Citations
22,495 Views
14 Pages

Large Language Models: Their Success and Impact

  • Spyros Makridakis,
  • Fotios Petropoulos and
  • Yanfei Kang

25 August 2023

ChatGPT, a state-of-the-art large language model (LLM), is revolutionizing the AI field by exhibiting humanlike skills in a range of tasks that include understanding and answering natural language questions, translating languages, writing code, passi...

  • Article
  • Open Access
55 Citations
25,323 Views
14 Pages

29 January 2023

Traders and investors are interested in accurately predicting cryptocurrency prices to increase returns and minimize risk. However, due to their uncertainty, volatility, and dynamism, forecasting crypto prices is a challenging time series analysis ta...

  • Article
  • Open Access
37 Citations
8,954 Views
29 Pages

Performance Analysis of Statistical, Machine Learning and Deep Learning Models in Long-Term Forecasting of Solar Power Production

  • Ashish Sedai,
  • Rabin Dhakal,
  • Shishir Gautam,
  • Anibesh Dhamala,
  • Argenis Bilbao,
  • Qin Wang,
  • Adam Wigington and
  • Suhas Pol

22 February 2023

The Machine Learning/Deep Learning (ML/DL) forecasting model has helped stakeholders overcome uncertainties associated with renewable energy resources and time planning for probable near-term power fluctuations. Nevertheless, the effectiveness of lon...

  • Article
  • Open Access
33 Citations
7,306 Views
11 Pages

6 January 2023

Since May 2022, over 64,000 Monkeypox cases have been confirmed globally up until September 2022. The United States leads the world in cases, with over 25,000 cases nationally. This recent escalation of the Monkeypox outbreak has become a severe and...

  • Review
  • Open Access
32 Citations
5,158 Views
24 Pages

Data-Driven Methods for the State of Charge Estimation of Lithium-Ion Batteries: An Overview

  • Panagiotis Eleftheriadis,
  • Spyridon Giazitzis,
  • Sonia Leva and
  • Emanuele Ogliari

14 September 2023

In recent years, there has been a noticeable shift towards electric mobility and an increasing emphasis on integrating renewable energy sources. Consequently, batteries and their management have been prominent in this context. A vital aspect of the B...

  • Article
  • Open Access
30 Citations
15,267 Views
23 Pages

22 March 2023

The Russian invasion of Ukraine on 24 February 2022 accelerated agricultural commodity prices and raised food insecurities worldwide. Ukraine and Russia are the leading global suppliers of wheat, corn, barley and sunflower oil. For this purpose, we i...

  • Article
  • Open Access
28 Citations
6,121 Views
18 Pages

Day Ahead Electric Load Forecast: A Comprehensive LSTM-EMD Methodology and Several Diverse Case Studies

  • Michael Wood,
  • Emanuele Ogliari,
  • Alfredo Nespoli,
  • Travis Simpkins and
  • Sonia Leva

2 March 2023

Optimal behind-the-meter energy management often requires a day-ahead electric load forecast capable of learning non-linear and non-stationary patterns, due to the spatial disaggregation of loads and concept drift associated with time-varying physics...

  • Article
  • Open Access
25 Citations
9,193 Views
13 Pages

Forecasting the Traffic Flow by Using ARIMA and LSTM Models: Case of Muhima Junction

  • Vienna N. Katambire,
  • Richard Musabe,
  • Alfred Uwitonze and
  • Didacienne Mukanyiligira

14 November 2023

Traffic operation efficiency is greatly impacted by the increase in travel demand and the increase in vehicle ownership. The continued increase in traffic demand has rendered the importance of controlling traffic, especially at intersections. In gene...

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Forecasting - ISSN 2571-9394