Producing predictions of the probabilistic risks of operating materials for given lengths of time at stated operating conditions requires the assimilation of existing deterministic creep life prediction models (that only predict the average failure t...
In a geophysical survey, one of the main challenges is to estimate the physical parameter using limited geophysical field data with noise. Geophysical datasets are measured with sparse sampling in a survey. However, the limited data constrain the geo...
Photovoltaic (PV) technology allows large-scale investments in a renewable power-generating system at a competitive levelized cost of electricity (LCOE) and with a low environmental impact. Large-scale PV installations operate in a highly competitive...
A multichannel speech enhancement system usually consists of spatial filters such as adaptive beamformers followed by postfilters, which suppress remaining noise. Accurate estimation of the power spectral density (PSD) of the residual noise is crucia...
The statistical retrieval of atmospheric parameters will be greatly affected by the accuracy of the simulated brightness temperatures (BTs) derived from the radiative transfer model. However, it is challenging to further improve a physical-based radi...
Remotely sensed data-based models used in operational forest inventory usually give precise and accurate predictions on average, but they often suffer from systematic under- or over-estimation of extreme attribute values resulting in too narrow or sk...
In this study, statistical distribution model (SDM) is used to predict the health index (HI) of transformers by utilizing the condition parameters data from dissolved gas analysis (DGA), oil quality analysis (OQA), and furanic compound analysis (FCA)...
This review paper looks briefly at conventional approaches and examines the intelligent means for fault diagnosis (FD) and condition monitoring (CM) of electrical drives in detail, especially the ones that are common in Industry 4.0. After giving an...
The European Space Agency (ESA) defines Earth observation (EO) Level 2 information product the stack of: (i) a single-date multi-spectral (MS) image, radiometrically corrected for atmospheric, adjacency and topographic effects, with (ii) its data-der...
Predictive models play a crucial role in RBMs to analyze performance indicator results to manage unexpected events and make timely decisions to resolve them. Their use in Mexico is deficient, and monitoring and evaluation are among the weakest pillar...
According to literature and despite their commercial success, state-of-the-art two-stage non-iterative geographic object-based image analysis (GEOBIA) systems and three-stage iterative geographic object-oriented image analysis (GEOOIA) systems, where...
According to existing literature and despite their commercial success, state-of-the-art two-stage non-iterative geographic object-based image analysis (GEOBIA) systems and three-stage iterative geographic object-oriented image analysis (GEOOIA) syste...
The modeling and analysis of sea clutter are of great significance in radar target detection studies in marine environments. Sea clutter typically exhibits non-Gaussian characteristics and spatiotemporal correlations, posing challenges for modeling,...
Snapping Shrimps (SSs) live in a warm ocean except the North and South Poles, and they are characterized by generating strong shock waves underwater using large claws. Shock waves generated by these SSs are used for marine noise research as a signal...
In the present study, various shapes of laboratory consolidation curves were numerically reproduced using a four-parametric sigmoid function. Sixteen consolidation curves were selected based on one-dimensional oedometer tests to statistically evaluat...
An upgrade is presented of a recently published model for the calculation of statistical averages of turbulent flow variables. Instead of empirical constructions, important parts of the model are based on general principles of statistical turbulence...
A reliability assessment is an important tool used for processing plants, since the facility consists of many loops and instruments attached and operated based on other availability; thus, a statistical model is needed to visualize the reliability of...
The current seepage prediction model of the sluice gate is rarely used. To solve the problem, this paper selects the bidirectional long and short-term neural network (BiLSTM) with high information integration and accuracy, which can well understand a...
The ever-increasing deployment of autonomous Cyber-Physical Systems (CPSs) (e.g., autonomous cars, UAV) exacerbates the need for efficient formal verification methods. In this setting, the main obstacle to overcome is the huge number of scenarios to...
This research introduces a new model to predict the roll force during hot rolling of steel, based on a statistical analysis of approximately 38,980 sets of measurements in a commercial mill with five finishing stands. The study includes ten different...
The vast increase in the available computational capability has allowed the application of Particle-Filter (PF)-based approaches for monocular 3D-model-based tracking. These filters depend on the computation of a likelihood function that is usually u...
A deep understanding of multipath characteristics is essential to design signal simulators and receivers in global navigation satellite system applications. As a new constellation is deployed and more applications occur in the urban environment, the...
A projective network model is a model that enables predictions to be made based on a subsample of the network data, with the predictions remaining unchanged if a larger sample is taken into consideration. An exchangeable model is a model that does no...
The number of wind-generating resources has increased considerably, owing to concerns over the environmental impact of fossil-fuel combustion. Therefore, wind power forecasting is becoming an important issue for large-scale wind power grid integratio...
Spike-and-wave discharge (SWD) pattern detection in electroencephalography (EEG) is a crucial signal processing problem in epilepsy applications. It is particularly important for overcoming time-consuming, difficult, and error-prone manual analysis o...
World-wide, political polarization continues unabated, undermining collective decision-making ability. In this issue, we have examined polarization dynamics using a (mean-field) model borrowed from statistical physics, assuming that each individual i...
To study the energy evolution law and damage constitutive behavior of high-strength concrete based on the conventional triaxial compression tests of C60 and C70 high-strength concrete subjected to five different confining pressures, the failure chara...
Vehicle motion trajectory prediction is the basis of vehicle collision early warning or vehicle conflict resolution. In order to improve the accuracy of trajectory prediction, a vehicle trajectory prediction method based on “current” stat...
This paper proposes an innovative Mixture Statistical Distribution Based Multiple Component (MSDMC) model for target detection in high spatial resolution Synthetic Aperture Radar (SAR) images. Traditional detection algorithms usually ignore the spati...
This paper presents a framework for photovoltaic (PV) fault detection based on statistical, supervised, and unsupervised machine learning (ML) approaches. The research is motivated by a need to develop a cost-effective solution that detects the fault...
In today’s diversified development model, the combination of modeling and business decision development is particularly important. The advanced theoretical business model established by modeling enables more efficient and accurate financial ana...
Ramie is an important cash crop in China, and ramie fiber is an important raw material for the textile industry. As a shrub plant, the spatial distribution of the ramie plant is different from that of herbaceous crops, and its plant spacing and row s...
Increasing our capacity to predict extreme storm surges is one of the key issues in terms of coastal flood risk prevention and adaptation. Dynamically forecasting storm surges is computationally expensive. Here, we focus on an alternative data-driven...
A statistical damage model (SDM) of fully-graded concrete was created using statistical damage theory, based on the mechanical properties of axial tension and axial compression of the material. The SDM considers two damage modes, fracture and yield,...
This study estimates the equivalent continuous sound pressure level (Leq) during peak daily periods (‘rush hour’) along the New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia, using a land use regression (LUR) model based on machine learning,...
With the development of modern power systems (smart grid), energy consumption prediction becomes an essential aspect of resource planning and operations. In the last few decades, industrial and commercial buildings have thoroughly been investigated f...
When considering the contradictions between river management and protection in a typical plain river network, it is always confirmed that the river area has usually been encroached upon due to the development of human society. Based on the analysis o...
The registration between images is a crucial part of the 3-D tooth reconstruction model. In this paper, we introduce a registration method using our proposed statistical randomization-based particle swarm optimization (SR-PSO) algorithm with the iter...
Predictions are presented of mean values of statistical variables of large-scale turbulent flow of the widely used basic k-
Automatic heart disease prediction is a major global health concern. Effective cardiac treatment requires an accurate heart disease prognosis. Therefore, this paper proposes a new heart disease classification model based on the support vector machine...
Unsaturated soil exhibits extremely complex engineering mechanical properties under the coupling effect of moistening and stress fields. Firstly, the effective stress principle and limit equilibrium conditions of unsaturated soil under the coupling e...
Emission of air pollutants constitutes one of the major hazards to human health and life. Particulate matter and harmful gases emitted by residential heating, especially, occupy a significant position among the sources of air pollution. This paper pr...
In recent years, climate change has demonstrated the volatility of unexpected events such as typhoons, flooding, and tsunamis that affect people, ecosystems and economies. As a result, the importance of predicting future climate has become even direr...
Asphaltenes, as the most complex and strongly polar component among the four components of asphalt, have a significant impact on the macroscopic physicochemical properties of asphalt. Currently, the vast variety of molecular structures used to charac...
Thermally induced deformation is a major source of dimensional error in end-milling, especially under high-speed or high-load conditions. Direct measurement of workpiece deformation during machining is impractical, while temperature signals can be ob...
As an important component of water conservancy infrastructure, canals help improve the uneven distribution of regional water resources. However, in their construction and operation processes, which are affected by a variety of complex factors, canal...
In the digital education system, the increasing demand for measuring lexical and semantic text similarity has led to the need for developing scalable and intelligent automated grading systems. Traditional assessment methods used for short-answer grad...
Among other methods, UWB-based multi-anchor localization systems have been established for industrial indoor localization systems. However, multi-anchor systems have high costs and installation effort. By exploiting the multipath propagation of the U...
Physics-based correction terms in reduced-order models are often motivated by statistically detectable structure in model residuals, but statistical detectability does not guarantee out-of-sample predictive value. Here, statistical detectability mean...
The prediction of asphalt mixture dynamic modulus (E*) was investigated based on 1128 E* measurements, using three regression and thirteen machine learning models. Asphalt binder properties and mixture volumetrics were characterized using the same fe...
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