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Abstract. The evaluation of forecast accuracy is one of the key instruments for assessing the reliability and practical value of analytical models applied by various institutions in the field of macroeconomic forecasting...

Abstract Background Historical and recent literature disagree on whether a higher PO 131I dosage, compared to IV or SC routes, is required for successful resolution of spontaneous hyperthyroidism in cats, necessitating i...

Abstract The Broad Learning System (BLS) provides an effective framework for nonlinear mapping, offering advantages over traditional deep neural networks through its expanded input node architecture. While BLS has demons...

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...

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 ...

Airport planning depends to a large extent on the levels of activity that are anticipated. To plan the facilities and infrastructures of an airport system and to be able to satisfy future needs, it is essential to predic...

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...

The management and operation of the power system would be significantly enhanced if accurate prior knowledge of power exchanges were provided, which could provide valuable insights into the system and help predict the re...

ABSTRACT The objective of this study was to assess behavior patterns in Brazilian farm milk prices. We employed a structural time series techniques model, the Unobserved Component Model (UCM), which is part of the family...

Accurate estimation of signal-to-noise ratio (SNR) in Scanning Electron Microscopy (SEM) is crucial because it evaluates the image quality. SEM images faced a challenge whereby Gaussian noise commonly appears in the imag...

Objective To characterise temporal trends in antiretroviral therapy (ART) utilisation and forecast short-term changes in regimen distribution within a provincial HIV treatment programme.Design Population-level longitudin...

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...

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...

Abstract Air pollution, particularly Nitrogen Dioxide ( $$\text {NO}_2$$ ) and ground-level ozone ( $$\text {O}_3$$ ), poses major risks to human health and the environment, making accurate forecasting essential for effe...

Urban wastewater treatment processes exhibit complex characteristics such as uncertainty, nonlinearity,and time delay, which pose significant challenges to water quality control and energy consumption optimization. To ad...

Ethylene is an important raw material, and ethylene cracking furnaces (ECFs) are the core equipment sources of ethylene plants. The quality of the operation of the ECF directly affects the overall economic benefits of th...

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...

The present study focuses on proposing various statistical models, such as linear regression (LR), nonlinear regression (NLR), and artificial neural network (ANN), to forecast the compressive strength of environmentally ...

Abstract BackgroundMainstays of pharmacoepidemiology are large, representative, behavioral surveys, which focus on many drugs with few detailed behaviors. Smaller, targeted studies measure drug-specific patte...