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ABSTRACT Background Tuberculosis (TB) remains a significant public health challenge, necessitating accurate forecasting methodologies to support effective control and prevention strategies. This paper explores the applic...

Carbon allowances constitute a foundational component of national carbon emission control frameworks, as they govern the equitable distribution of subsequent allocations and directly shape the overall effectiveness of gr...

Abstract Faculty hiring shapes the flow of ideas, resources, and opportunities in academia, influencing not only individual career trajectories but also broader patterns of institutional prestige and scientific progress....

Forecasting vaccine demand and determining inventory policies are critical challenges in healthcare supply chains, where uncertainty poses significant operational risks. This study proposes a two-step data-driven framewo...

INTRODUCTION: With the rapid growth of offshore wind power integration and increasing wind power penetration, accurate power forecasting has become essential for maintaining grid stability and supporting economic dispatc...

Abstract Financial time series forecasting is traditionally based on historical price patterns, often overlooking exogenous and behavioral variables that can significantly affect market movements. In this study, we enhan...

Abstract Carbon markets play a critical role in emission reduction and sustainable economic transition; however, carbon price series exhibit high volatility, nonlinear dynamics, and complex cross-feature interactions, ma...

The article considers strategic modeling of the competitive capabilities of tourism companies in a dynamic market. The purpose is to design an effective model for assessing competitiveness, using materials from the case ...

BackgroundThe COVID-19 pandemic has reshaped the global epidemiology of respiratory infectious diseases, posing new challenges for influenza forecasting. Existing studies are often limited by reliance on single data sour...

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...

Accurate traffic flow prediction is of great significance for urban planning and traffic management. Among existing methods, researchers have shown remarkable progress by utilizing spatiotemporal networks. Unfortunately,...

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...

Abstract River water quality forecasting on directed river networks requires jointly modeling temporal dynamics and directional spatial dependencies among monitoring sites. Existing spatio-temporal models often emphasize...

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-...

BackgroundInfluenza poses a significant global public health threat, with its pandemic potential and seasonal variability presenting formidable challenges to prediction accuracy. This study leverages high-quality weekly ...

Background: Latent tuberculosis infection (LTBI) remains a critical reservoir for the global tuberculosis (TB) epidemic, particularly in South Asia, where high population density and socioeconomic disparities amplify its...

INTRODUCTION: High renewable energy penetration introduces significant uncertainties in distribution networks, posing challenges for source-load power forecasting and voltage management. OBJECTIVES: This study aims to e...

Abstract Air-conditioning load forecasting is important for building energy scheduling and control. The task is difficult because load data show clear periodic patterns, and sudden changes caused by events such as holida...

Abstract Bunker fuel prices constitute a major component of maritime transport costs, representing 30–70% of total operating expenses and critically influencing competitiveness, planning, and regulatory compliance in g...

Presents corrections to the paper, (Demand Forecasting in Data-Scarce and Resource-Restricted Environments).

This research focuses on developing a neural network model in the Python programming language to solve the technological problem of forecasting potato yields with limited agroclimatic data. The developed program is consi...