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Forecasting, Volume 7, Issue 3

September 2025 - 22 articles

Cover Story: NCD-Pred introduces the first multichannel forecasting system using Neighborhood-Constrained Variational Mode Decomposition (NCVMD) combined with neural networks. The approach decomposes multichannel signals into band-limited intrinsic mode functions (IMFs), prioritizing informative main channels over auxiliary ones while aligning corresponding IMF central frequencies. This frequency synchronization enables cooperative mode forecasting where LSTM networks predict individual components that are recombined for final predictions. Evaluated on weakly cross-correlated power load data from vessels, NCD-Pred outperforms benchmark mode-level forecasting methods, demonstrating practical utility in real signal processing applications where traditional correlation-based approaches may struggle. View this paper
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Articles (22)

  • Article
  • Open Access
975 Views
15 Pages

22 September 2025

In this study, an aircraft icing diagnosis and forecasting method is constructed and hindcast for 25 collected spring icing cases over Eastern China based on two commonly used aircraft icing diagnostic methods (hereinafter referred to as the IC index...

  • Article
  • Open Access
1,335 Views
16 Pages

Short-Term Prediction in an Emergency Healthcare Unit: Comparison Between ARIMA, ANN, and Logistic Map Models

  • Andres Eberhard Friedl Ackermann,
  • Virginia Fani,
  • Romeo Bandinelli and
  • Miguel Afonso Sellitto

18 September 2025

Emergency departments worldwide face challenges in managing fluctuating patient demand, which is often inadequately addressed by traditional forecasting methods due to the inherent nonlinearities of data. The purpose of this study is to propose a sho...

  • Article
  • Open Access
1,516 Views
36 Pages

Identification of Investment-Ready SMEs: A Machine Learning Framework to Enhance Equity Access and Economic Growth

  • Periklis Gogas,
  • Theophilos Papadimitriou,
  • Panagiotis Goumenidis,
  • Andreas Kontos and
  • Nikolaos Giannakis

16 September 2025

Small and medium-sized enterprises (SMEs) are critical contributors to economic growth, innovation, and employment. However, they often struggle in securing external financing. This financial gap mainly arises from perceived risks and information asy...

  • Article
  • Open Access
1 Citations
1,237 Views
36 Pages

SGR-Net: A Synergistic Attention Network for Robust Stock Market Forecasting

  • Rasmi Ranjan Khansama,
  • Rojalina Priyadarshini,
  • Surendra Kumar Nanda,
  • Rabindra Kumar Barik and
  • Manob Jyoti Saikia

14 September 2025

Owing to the high volatility, non-stationarity, and complexity of financial time-series data, stock market trend prediction remains a crucial but difficult endeavor. To address this, we present a novel Multi-Perspective Fused Attention model (SGR-Net...

  • Article
  • Open Access
1 Citations
2,266 Views
25 Pages

12 September 2025

The aim of this paper is the analysis and selection of stock trading systems that combine different models with data of a different nature, such as financial and microeconomic information. Specifically, based on previous work by the authors and with...

  • Article
  • Open Access
4,036 Views
19 Pages

10 September 2025

Accurate and efficient cryptocurrency price prediction is vital for investors in the volatile crypto market. This study comprehensively evaluates nine models—including baseline, zero-shot, and deep learning architectures—on 21 major crypt...

  • Article
  • Open Access
988 Views
27 Pages

2 September 2025

This study presents a gradient-informed proxy initialization framework designed to improve training efficiency and predictive performance in deep learning models for time-series forecasting. The method extends the Laor Initialization approach by intr...

  • Article
  • Open Access
1,499 Views
25 Pages

Improving Dry-Bulb Air Temperature Prediction Using a Hybrid Model Integrating Genetic Algorithms with a Fourier–Bessel Series Expansion-Based LSTM Model

  • Hussein Alabdally,
  • Mumtaz Ali,
  • Mohammad Diykh,
  • Ravinesh C. Deo,
  • Anwar Ali Aldhafeeri,
  • Shahab Abdulla and
  • Aitazaz Ahsan Farooque

The dry-bulb temperature is a critical parameter in weather forecasting, agriculture, energy management, and climate research. This work proposes a new hybrid prediction model (FBSE-GA-LSTM) that integrates the Fourier–Bessel series expansion (...

  • Article
  • Open Access
1 Citations
1,808 Views
29 Pages

The accurate short-term forecasting (PV) of power is crucial for grid stability control, energy trading optimization, and renewable energy integration in smart grids. However, PV generation is extremely variable and non-linear due to environmental fl...

  • Article
  • Open Access
819 Views
19 Pages

NCD-Pred: Forecasting Multichannel Shipboard Electrical Power Demand Using Neighborhood-Constrained VMD

  • Paolo Fazzini,
  • Giuseppe La Tona,
  • Marco Montuori,
  • Matteo Diez and
  • Maria Carmela Di Piazza

This paper introduces Neighborhood-Constrained Decomposition-based Prediction (NCD-Pred), the first system to leverage Neighborhood-Constrained Variational Mode Decomposition (NCVMD) for multichannel forecasting by integrating time series decompositi...

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Forecasting - ISSN 2571-9394