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The growth of variable renewable energy sources has increased the occurrence of curtailment in power systems, particularly in regions affected by transmission constraints and limited operational flexibility. Reliable for...

Multivariate time series forecasting is pivotal in real-world applications, ranging from energy consumption management and financial market trend analysis to traffic flow prediction and climate monitoring. Yet, it is cri...

Predicting electrical power loads in industrial parks is challenging due to the uncertainty and variance in model construction. This paper proposes an interval forecasting approach based on a residual-form CNN-BiLSTM, wh...

Strategic planning for the construction materials industry development in conjunction with forecasting business processes has been studied. In an unstable external environment influenced by exogenous and endogenous facto...

Satellite-based crop forecasting in major exporting regions can trigger production shifts in the opposite hemisphere by leveraging seasonal disparities between the Northern and Southern Hemispheres to stabilize global cr...

IntroductionThe escalating frequency of infectious disease outbreaks underscores the urgent need for reliable forecasting systems to support timely public health interventions. Existing approaches—ranging from statisti...

Short-term wind speed forecasting remains challenging due to the inherent nonstationarity and multiscale variability of atmospheric processes. This study proposes a hybrid multiscale forecasting framework combining four-...

Abstract The increase in vehicle ownership and urban population puts a strain on roads and increases traffic congestion within developed and developing nations. Congestion affects an individual’s time and increases an ...

In the face of socioeconomic challenges, this paper develops and empirically demonstrates the Gondauri Index (GI) as a reproducible, diagnostics-first composite framework for benchmarking macro-financial resilience acros...

Abstract Traffic flow prediction is a fundamental building block for Intelligent Transportation Systems (ITS), enabling proactive congestion mitigation, adaptive traffic signal control, and reliable route guidance. Howev...

Abstract This research proposes an innovative Arabic financial forecasting model that integrates linguistic relation extraction with advanced deep learning and machine learning techniques. The framework combines Arabic O...

This study examines whether active learning activities based on time series forecasting for engineering students yield statistically significant improvements with respect to performance and engagement. In this context, a...

Abstract Achieving sustainable economic growth in resource-dependent economies is vital to balancing competitiveness, attracting investment, and improving environmental performance. This study examines the asymmetric eff...

Options trading is a type of financial trading that can offer significant profit opportunities depending on market conditions, but its profit and loss structure is complex. Traditional trading decisions are often made ba...

ABSTRACT: Background: Lip and oral cavity cancer (LOCC) remains a significant issue in Europe, with an uneven public health burden. While trends have shifted, regional and sex-specific disparities persist due to modifia...

Abstract To address the limitations of existing oil-well production forecasting models, particularly suboptimal hyperparameter selection, difficulties in fine-tuning, insufficient global search capability, and slow conve...

Abstract In response to the problems of large fluctuations in electricity prices and difficulty in long-term forecasting caused by the large-scale integration of new energy in the electricity market, this paper construct...

Accurate deformation forecasting is essential for concrete dam safety monitoring, yet real-world deformation series are often nonlinear, nonstationary, and contaminated by noise, missing values, and outliers, which limit...

Time-series forecasting is fundamental to decision-making across numerous domains; however, systematic temporal delays in predictions remain a largely overlooked or unrecognised phenomenon. This phenomenon occurs when fo...

Abstract This study examines the effect of financial literacy on the performance of small and medium-sized enterprises (SMEs) in Mogadishu, Somalia, a fragile and post-conflict economy. Grounded in Human Capital Theory, ...

Amid the convergence of technological, macroevolutionary, and demographic singularities, conventional approaches to analyzing and forecasting economic growth are increasingly losing relevance and predictive power. The su...

This study aims to systematically analyze the new characteristics, evolution trends, and causes of major extreme weather in China in the context of global climate change, and evaluate the current forecasting, early-warni...

Urban analytics has emerged as a transformative tool for addressing the challenges of urbanization and fostering sustainable smart cities. Despite its growing significance, a gap remains in the literature on integrating ...

The article contains a feasibility analysis of using big data of payment systems for building forecasting models for the dynamics of consumer demand as a core factor of the retail turnover. The relevance of this research...