The advances in computational fluid dynamics have made numerical modeling a reliable complementary tool to the traditional physical modeling in the study of the wave overtopping phenomenon. This paper addresses overtopping on a seawall by combining t...
The micro-interface slip damping mechanism is insensitive to temperature, making it suitable for applications where the operating environment makes viscoelastic polymers ineffective. Damping material systems that rely on micro-interface slip typicall...
The COVID-19 pandemic is a serious threat to all of us. It has caused an unprecedented shock to the world’s economy, and it has interrupted the lives and livelihood of millions of people. In the last two years, a large body of literature has at...
This paper studies the properties of the Preisach model and the play model, and compare their similarities. Both are history-dependent hysteresis models that are used to model magnetic hysteresis. They are described as discrete sums of simple hystere...
This review aims to provide a complete and comprehensive state of the art of the SCOSSA computer code, which is a one-dimensional nonlinear computer code used for the analysis of seismic site response and soil instability. Indeed, among the effects o...
Resonant column (RC) and the torsional simple shear (TOSS) tests have shown proven competency in acquiring precise and repeatable measurements regarding the shear modulus and damping ratio of soil. For most dynamic geotechnical problems, the shear mo...
In this paper, a high-temperature low-cycle fatigue life prediction model, based on the total strain energy density method, was established. Considering the influence of the Masing and non-Masing behavior of materials on life prediction, a new life p...
Accurate forecasting of local weather patterns is essential for climate resilience and sustainable planning. This study analysed 35 years (1990–2025) of hourly temperature and precipitation data from Thohoyandou, South Africa, to assess the imp...
This study investigates the application of several machine learning models using PyCaret to forecast the monthly demand for electricity consumption; we analyze historical data of monthly consumption readings for the Cuajone Mining Unit of the company...
Large language models (LLMs) and time-series foundation models have advanced traffic forecasting, but almost exclusively on freeway sensors at five-minute, aggregate-flow resolution; their behavior on minute-resolution, movement-level counts at signa...
Islamic literature has indicated that daily consumption of Ajwa dates heals a variety of chronic diseases and disorders. The current research investigates the neuroprotective effect of methanolic Ajwa seed extract (MASE) on lipopolysaccharide (LPS)-i...
This article investigates the efficiency of hybridizing composites with thin layers of martensitic shape memory alloys for improvement of damping. The non-linear damping behaviour of martensitic shape memory alloys is simulated using a modified versi...
To fulfil the goals of the circular economy, the treatment of textile wastewater should be focused on the recovery of valuable components. Monovalent anion-selective electrodialysis (MASED) was applied for the separation of reactive dyes from mineral...
Hierarchical retail forecasting requires predictions that are both accurate and coherent across multiple planning levels, from total demand to individual product–store series. Because these forecasts guide inventory, replenishment, storage, and...
This study investigates the effectiveness of Transformer-based models for retail demand forecasting. We evaluated vanilla Transformer, Informer, Autoformer, PatchTST, and temporal fusion Transformer (TFT) against traditional baselines like AutoARIMA...
In geotechnical engineering, dynamic soil models are used to predict soil behavior under different loading conditions. This is crucial for many dynamic geotechnical problems related to earthquakes, train loading and machine foundation design. Researc...
Accurate forecasting of energy consumption, renewable power output and utility expenditure is essential for sustainable planning of residential buildings and improving smart grid integration. This study presents several techniques such as random fore...
In this paper, torsional fatigue failure of 30CrMnSiNi2A steel which exhibited non-Masing behavior was studied under different constant shear strain amplitudes, using thin-walled tubular specimens. The relationship between shear fatigue and the evolu...
The aim of this study was to model the behavior of particles with aerodynamic diameter lower or equal to
Short-term forecasting of solar and wind power generation is critical for smart grid management but challenging due to non-stationarity and extreme generation events. This study addresses a multi-task learning problem: regression-based forecasting of...
This article presents a multi-indicator approach to forecasting the monthly workload of a military road freight transport system in support of operational planning. The empirical basis of the study consisted of real-world operational data from 2020 t...
Demand variability complicates workforce capacity planning in knowledge-intensive services, particularly when only short historical records are available. This study evaluates parsimonious benchmark models for forecasting translation-service demand a...
Accurate prediction of gas pipeline incidents through risk factor interdependencies is critical for proactive safety management. This study develops a hybrid SARIMA–association rule mining (ARM) framework integrating time-series forecasting wit...
Ecuador has experienced one of the fastest escalations of lethal violence in Latin America, with annual intentional homicides rising from about 1000 in 2014–2019 to 9283 in 2025. This study evaluates how well such patterns can be forecast, and...
The selection of an accurate performance metric is highly important to evaluate the quality of a forecasting method. This evaluation may help to select between different forecasting tools of forecasting outputs, and then support many decisions within...
Providing sustainable energy to rural communities is considered in Sustainable Development Goal 7. Off-grid renewable energy systems arise as an affordable solution due to their portability and the availability of renewable sources for rural communit...
Low cycle fatigue (LCF) behaviors of TC21 alloy with a bi-lamellar basketweave microstructure were investigated in this paper. The strain fatigue tests were carried out at total strain amplitudes of 1.4% to 2.0%. The cyclic stress response showed the...
Fatigue models using the strain-life method do not show exact conformity with the empirical results. Therefore, the use of the mean-stress correction approach is to be evaluated, with a particular focus on mild and higher-strength steel. The influenc...
Background: Retail inventories are heterogeneous, yet demand forecasting studies typically select one model for an entire portfolio, leaving open how forecasting effort should be allocated across inventory segments. Methods: Six models—ARIMA, S...
Retailers must have accurate sales forecasts to efficiently and effectively operate their businesses and remain competitive in the marketplace. Global forecasting models like RNNs can be a powerful tool for forecasting in retail settings, where multi...
Heating and cooling degree-days (HDDs and CDDs) link outdoor temperature to building heating and cooling demand and serve as inputs for building energy and emissions models. Existing data-driven forecasts cover a few stations or provinces within sing...
The development of a cost-effective and accurate model for predicting the fatigue life of materials is essential for designing thermal power plants and assessing their structural reliability under operational conditions. This paper reports a novel en...
The forecasting of univariate time series poses challenges in industrial applications if the seasonality varies. Typically, a non-varying seasonality of a time series is treated with a model based on Fourier theory or the aggregation of forecasts fro...
Vehicle trajectories are time series, and entropy is a powerful tool for testing or quantifying the complexity of a given series. Entropy tools are often applied to variables such as velocity, acceleration, space headway, and time headway, but the lo...
This empirical research endeavor seeks to enhance the accuracy of forecasting time series data in the banking sector by utilizing data from the Amman Stock Exchange (ASE). The study relied on daily closed price index data, spanning from October 2014...
Forecasting power consumption is essential for intelligent power management in IoT-enabled smart environments, where heterogeneous behaviors appear from diverse building usages. University campuses are considered environments that share similarities...
Financial markets are increasingly interlinked. Therefore, this study explores the complex relationships between the Tadawul All Share Index (TASI), West Texas Intermediate (WTI) crude oil prices, and Bitcoin (BTC) returns, which are pivotal to infor...
Accurate estimation of global horizontal irradiance (GHI) is relevant for characterizing solar resources in regions with limited measurement infrastructure. This study compared six machine learning models Polynomial Ridge Regression, Decision Tree, R...
National forest inventories in many countries combine expensive ground plot data with remotely-sensed information to improve precision in estimators of forest parameters. A simple post-stratified estimator is often the tool of choice because it has k...
Accurate seismic safety assessment of nuclear power plant (NPP) structures with pile foundations on soft soil sites requires consideration of soil nonlinearity and pile–soil–structure interaction (PSSI). This study develops an efficient p...
To address the insufficient fusion of electromechanical impedance (EMI) response features from multiple sensors and the limited characterization of spatial relationships between sensors and bolt nodes in four-bolt connection structures, this study pr...
Antibiotic-free (ABF) broiler production plays an important role in promoting sustainable and welfare-oriented poultry farming. However, this production system presents challenges, particularly an increased susceptibility to stress and mortality duri...
The cyclic performance of structural steels after exposure to various elevated temperatures and cooling-down methods was experimentally investigated in this paper. Four types of frequently used structural steels were tested including Chinese mild ste...
This study applies Gradient Boosting Machines (GBMs) and principal component regression (PCR) to forecast the closing price of the Johannesburg Stock Exchange (JSE) All-Share Index (ALSI), using daily data from 2009 to 2024, sourced from the Wall Str...
Accurate demand forecasting is essential for retail operations as it directly impacts supply chain efficiency, inventory management, and financial performance. However, forecasting retail time series presents significant challenges due to their irreg...
Nowadays, air quality is a major issue, especially in large cities. Apart from air pollution, particulate matter (PM), especially PM2.5, poses serious health risks to individuals with respiratory conditions. Accurate forecasting of PM levels is cruci...
In this study, the tensile properties, low-cycle fatigue behavior, and microscopic fatigue-failure mechanisms of 316H stainless steel in the temperature range of 600–800 °C were systematically investigated by means of tensile tests, high-te...
The shift towards renewable energy integration into smart grids has led to complex management processes, which require finer-grained energy and heat generation/ demand forecasting while considering data from monitoring devices and the integration of...
A variety of statistical techniques were assessed for their usefulness for analysing the pattern of geographical and temporal changes in groundwater levels in order to diagnose the water supply in Meoqui, Chihuahua, which is situated in dry North-Cen...
Drought is a complex threat where its propagation is not yet controllable, causing more environmental, social, and economic damage. This research assesses the effects of incessant warming and decrescent precipitation by calculating SPI and SPEI from...
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