Forecasting MDPI

16/10/2025

📢 in

"Forecasting Convective Storms Trajectory and Intensity by Neural Networks"

by Niccolò Borghi, Giorgio Guariso, and Matteo Sangiorgio

🔗 https://brnw.ch/21wWFSM

16/10/2025

📢 in ForecastingMDPI

"Projecting Climate Change Impacts on Channel Depletion in the Sacramento–San Joaquin Delta of California in the 21st Century"

✍️ By Sohrab Salehi, Seyed Ali Akbar Salehi Neyshabouri, Andrew Schwarz and Minxue He

🔗https://brnw.ch/21wWFPa

15/10/2025

📘 article in

"Data-Centric Benchmarking of Neural Network Architectures for the Univariate Time Series Forecasting Task"

Discover the latest insights and advancements in time series forecasting!

🔗 Read here: https://brnw.ch/21wWDWK

Time series forecasting has witnessed a rapid proliferation of novel neural network approaches in recent times. However, performances in terms of benchmarking results are generally not consistent, and it is complicated to determine in which cases one approach fits better than another. Therefore, we ...

15/10/2025

📘 in :

"An In-Depth Look at Rising Temperatures: Forecasting with Advanced Time Series Models in Major US Regions"

🔗 https://brnw.ch/21wWDWJ

With growing concerns over climate change, accurately predicting temperature trends is crucial for informed decision-making and policy development. In this study, we perform a comprehensive comparative analysis of four advanced time series forecasting models—Autoregressive Integrated Moving Averag...

14/10/2025

📘 Open Access Article in MDPI Forecasting

"A Data-Driven Multi-Step Flood Inundation Forecast System"

This study presents a novel forecasting approach designed to improve flood risk prediction and management through multi-step inundation modeling.

🔗 Read the full article here: https://brnw.ch/21wWBMP

Inundation maps that show water depths that occur in the event of a flood are essential for protection. Especially information on timings is crucial. Creating a dynamic inundation map with depth data in temporal resolution is a major challenge and is not possible with physical models, as these are t...

14/10/2025

📘 article in :

"Time-Series Interval Forecasting with Dual-Output Monte Carlo Dropout: A Case Study on Durian Exports"

Explore advanced forecasting methods for agricultural trade.

🔗 https://brnw.ch/21wWBMp

Deep neural networks (DNNs) are prominent in predictive analytics for accurately forecasting target variables. However, inherent uncertainties necessitate constructing prediction intervals for reliability. The existing literature often lacks practical methodologies for creating predictive intervals,...

13/10/2025

📘 article in !

📖 A Delphi–Fuzzy Delphi Study on SDGs 9 and 12 after COVID-19: Case Study in Brazil

This study explores expert perspectives on post-COVID challenges and opportunities for achieving Sustainable Development Goals 9 (Industry, Innovation, and Infrastructure) and 12 (Responsible Consumption and Production) in Brazil.

🔗 Read the full article: https://brnw.ch/21wWA43

The COVID-19 pandemic has affected all Sustainable Development Goals (SDGs), leading to setbacks in various Latin American countries. In Brazil, progress in technological development and the adoption of sustainable practices by organizations has been significantly hindered. Yet, there remains a limi...

13/10/2025

📘 article in !

📖 A Markov Switching Autoregressive Model with Time-Varying Parameters

Explore advanced forecasting techniques with this insightful study.

🔗 Read it here: https://brnw.ch/21wWzZd

This study showcased the Markov switching autoregressive model with time-varying parameters (MSAR-TVP) for modeling nonlinear time series with structural changes. This model enhances the MSAR framework by allowing dynamic parameter adjustments over time. Parameter estimation uses maximum likelihood ...

13/10/2025

🌍📅 October 13 – International Day for Disaster Risk Reduction

Today, we join the global community in raising awareness about the importance of reducing disaster risks and building more resilient societies. Effective disaster risk reduction saves lives, protects livelihoods, and strengthens communities worldwide.

Together, we can make a difference.

10/10/2025

📘 article in MDPI Forecasting!

"Machine Learning-Enhanced Pairs Trading"

This study explores how machine learning can improve the performance of pairs trading strategies — a must-read for those in quantitative finance and algorithmic trading.

🔗 Read the full article: https://brnw.ch/21wWvYn

Forecasting returns in financial markets is notoriously challenging due to the resemblance of price changes to white noise. In this paper, we propose novel methods to address this challenge. Employing high-frequency Brazilian stock market data at one-minute granularity over a full year, we apply var...

10/10/2025

📘 article in MDPI Forecasting!

"An Alternative Proof of Minimum Trace Reconciliation"

Discover fresh insights into reconciliation methods in forecasting research.

🔗 Read the full article here: https://brnw.ch/21wWvYj

Minimum trace reconciliation, developed by Wickramasuriya et al., 2019, is an innovation in the literature on forecast reconciliation. The proof, however, has a gap, and the idea is not easy to extend to more general situations. This paper fills the gap by providing an alternative proof based on the...

09/10/2025

📘 article in !

"Modeling CO2 Emission Forecasting in Energy Consumption of the Industrial Building Sector under Sustainability Policy in Thailand: Enhancing the LISREL-LGM Model"

Explore the latest insights here:

🔗 https://brnw.ch/21wWu3D

This research aims to study and develop a model to demonstrate the causal relationships of factors used to forecast CO2 emissions from energy consumption in the industrial building sector and to make predictions for the next 10 years (2024–2033). This aligns with Thailand’s goals for sustainabil...