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ABSTRACT This study was carried out to statistically evaluate the performance of the PHYGROW model in simulating the growth of corn and sorghum plants in different locations in the semi-arid region of Ceará State, Brazi...

Deep learning models are widely used in traffic forecasting and have achieved state-of-the-art prediction accuracy. However, their black-box nature presents challenges for interpretability and usability, particularly whe...

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...

To overcome the limitations of traditional models to simulate discrete environmental variables, this study introduces a novel, integrated simulation framework: the Spatio-Temporal Integrated Geographic Generative Adversa...

Abstract In the world of the Internet of Things (IoT), wireless sensor networks (WSNs) play a vital role in enabling seamless communication between connected devices. In a WSN data prediction system based, clustering and...

The Global Flood Awareness System (GloFAS) is a promising flood-modelling tool available for most river basins worldwide. However, it contains inherent biases, notably linked to its spatial resolution. This study propose...

Accurate, efficient, and rapid traffic forecasting is essential for intelligent transportation systems and plays a pivotal role in urban traffic planning, management, and control. While existing spatiotemporal transforme...

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 trajectory forecasting is essential for enabling autonomous vehicles to navigate safely in complex traffic environments. Current models typically assume that predictions are latency-free, an idealistic simplific...

Manual inventory processes at PT Borneo Sejahtera Medika resulted in an 18.2% stock discrepancy rate, frequent expired items, and delayed procurement decisions. This study develops and empirically evaluates a web-based i...

ObjectiveA hybrid model based on bidirectional short term memory （BiLSTM） and Transformer was constructed to predict the population behavior of Listeria monocytogenes under different environmental conditions.MethodsI...

Abstract The precise forecasting of the Remaining Useful Life (RUL, expressed in hours) of aircraft engine-like systems using a synthetic dataset designed to mimic real engine degradation patterns is a key factor in sett...

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...

We review the theory and evidence on IPO activity and underpricing focusing on the Warsaw Stock Exchange and confirm that many IPO phenomena in Poland are not stationary. Focusing on the behavioural reasons for underpr...

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...

Pilot Reports (PIREPs) are an important source of information that aids, other pilots, air traffic control, and operational aviation meteorologists in terms of forecasting and updating weather advisories such as SIGMETs....

The global aviation industry plays a critical role in economic development and international connectivity. However, it also contributes significantly to environmental challenges, particularly through fuel consumption and...

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...

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 ...

This investigation delves into the significance of precise earnings forecasts for publicly traded companies in achieving investment success. It emphasises the importance of this aspect, particularly in markets with limit...