Stochastic computing (SC) has the characteristics of low complexity and is expected to solve the bottleneck problem of conventional binary computing. Stochastic normalization units are widely used in stochastic decoding and stochastic signal detectio...
Commercial prototype building models were developed by the United States Department of Energy (DOE) to analyze the energy savings of the ASHRAE 90.1 standard. However, in the DOE models, occupant behavior inputs were deterministic and the stochastici...
Grid integration of renewable resources such as solar and wind energy can significantly raise the level of uncertainty in power systems, making the scheduled operation of generating units difficult. Therefore, the importance of operating reserves is...
Deep neural networks (DNNs) have achieved remarkable progress across various domains, yet they remain highly vulnerable to adversarial attacks, which significantly hinder their deployment in safety-critical applications. While stochastic defenses hav...
This paper develops a finite-horizon stochastic optimal harvesting model that links constrained Hamilton-Jacobi-Bellman (HJB) control with a nonlinear Feynman-Kac/BSDE representation. Harvesting effort is bounded, yielding a projected feedback policy...
The manuscript proposes a novel bounded proportional autoregressive (PAR) process based on the quasi-Lindley half-logistic unit (QHU) distribution, termed the QHU-PAR(1) process. Fundamental probabilistic properties of the process are established, in...
Carbon-neutral industrial parks require large consumers, such as data centers, to balance low-carbon operation and service reliability. This paper proposes a resilience-constrained stochastic dispatch framework for a data-center virtual power plant (...
The article analytically summarizes the idea of applying Shannon’s principle of entropy maximization to sets that represent the results of observations of the “input” and “output” entities of the stochastic model for eva...
This paper presents a stochastic analysis of a two-unit cold standby system incorporating imperfect switching mechanisms. Each unit operates in one of three states: normal, partial failure, or total failure. Employing Markov processes, the study eval...
In light of the dissemination of renewable energy connected to the power grid, it has become necessary to consider the uncertainty in the generation of renewable energy as a unit commitment (UC) problem. A methodology for solving the UC problem is pr...
In distributed operation, each unit is operated by its local controller instead of using a centralized controller, which allows the action to be based on local information rather than global information. Most of the distributed solutions have impleme...
Various GNSS applications require low-cost, small-scale, lightweight and power-saving GNSS devices and require high precision in terms of low noise for carrier phase and code observations. Applications vary from navigation approaches to positioning i...
The Unit Inverse Maxwell–Boltzmann (UIMB) distribution is introduced as a novel single-parameter model for data constrained within the unit interval (
Stochastic streamflow synthesis has long been the cornerstone of water resource planning, enabling the generation of extended hydrological sequences that reflect natural variability beyond the limitations of observed records. This paper presents a co...
The normalized difference vegetation index (NDVI) is an important indicator for evaluating vegetation change, monitoring land surface fluxes or predicting crop models. Due to the great availability of images provided by different satellites in recent...
To address the escalating demand for power grid load regulation, pumped storage power stations must frequently switch between operational modes. As a key component of such stations, the pump turbine has seen extensive research on its steady-state flo...
To address the frequency stability challenges arising from the high penetration of renewable energy, this study proposes a coordinated frequency regulation strategy for wind-power–hydrogen coupled systems, considering the Equivalent State of Ch...
High-resolution weather data is essential for studies related to fruit production, building sciences and other mathematical modelling. Most of the historical weather data prior to 1980 was mainly daily. The introduction of automatic weather stations...
Discrete production planning under integer constrained resource framework is a challenging issue which requires simultaneous consideration of output maximization, resource efficiency, and balanced resource. This research focuses on simulation of an i...
In an era of high penetration of renewable energy, accurate photovoltaic (PV) power forecasting is crucial for balancing and scheduling power systems. However, PV power output has uncertainty since it depends on stochastic weather conditions. In this...
Forecasting of forest dynamics at a large scale is essential for land use management, global climate change and biogeochemistry modeling. We develop time series models of the forest dynamics in the conterminous United States based on forest inventory...
At the beginning of the COVID-19 pandemic, the entire world was waiting for a medical solution (for example, vaccines) in order to return to normality. Sanitary restrictions changed our consumption behaviors and feelings. Therefore, this paper analyz...
The United States has experienced an even longer and more intense wildfire season than normal in recent years, largely resulting from drought conditions and a buildup of flammable vegetation. The derived stochastic dynamic model in this study was uti...
Digital infrastructure expansion in Europe raises a spatial planning problem: early-stage screening needs to compare regional conditions while also checking whether rankings remain stable when decision priorities change. This study evaluates 24 Europ...
There exists a temporal and spatial coupling effect among the hydropower units in cascade hydropower stations which constitutes a complex planning problem. Researching the multi-objective optimization scheduling of cascade hydropower stations under v...
This paper investigates the precision and stochastic error propagation of navigation solutions obtained from a low-cost microelectromechanical system inertial measurement unit (MEMS-IMU) under static conditions. A modern smartphone equipped with an M...
The standardized hydrological index (SHI) is the standardized but not normalized (normal probability variate) value of the streamflow used to characterize a hydrological drought, akin to the standardized precipitation index (SPI, which is both standa...
The spatial uncertainty of soil mechanical parameters remains a major challenge in physical models for the prediction of rainfall landslides. Currently, the widely adopted stochastic methods for parameter selection disregard the lithological variatio...
As the core sensor of inertial measurement units, the reliability of Micro-Electro-Mechanical Systems (MEMS) gyroscopes is critical for long-term navigation and motion control applications. To bridge the mechanism-data gap in MEMS multi-mechanism deg...
Crop yield is an important factor for evaluating production processes and determining the profitability of growing coffee. Frequently, the total number of coffee beans per area unit is estimated manually by physically counting the coffee cherries, th...
Modern industrial units collect large amounts of process data based on which advanced process monitoring algorithms continuously assess the status of operations. As an integral part of the development of such algorithms, a reference dataset represent...
High photovoltaic (PV) penetration introduces rapid variability, voltage deviations, and increased real-power losses in distribution networks, necessitating control strategies that remain effective under forecast uncertainty. This paper presents a un...
The estimation of the uncertainty of random variables or the entropy of stochastic processes has attracted considerable attention in many studies. In this study, we focus on obtaining estimators for the Shannon, Rényi, Tsallis, and Havrda&ndas...
Compared to widely examined topics in the related literature, such as financial crises/difficulties in accurate prediction, studies on corporate performance forecasting are quite scarce. To fill the research gap, this study introduces an advanced dec...
With the increasing integration of photovoltaic (PV) generation, short-term scheduling of hydro–PV–battery energy storage systems (HPBS) faces growing challenges due to the stochastic variability of PV output, the temporal coupling of hyd...
With the increasing penetration of electric vehicles (EVs), multi-virtual power plant (multi-VPP) systems face growing challenges in coordinating heterogeneous flexible resources, managing stochastic EV charging and discharging behaviors, and maintai...
We propose a novel photonic accelerator architecture based on a broadcast-and-weight approach for a deep neural network through a photonic integrated cross-connect. The single neuron and the complete neural network operation are numerically simulated...
Introduction: Widespread adoption of AI for medical decision-making is still hindered due to ethical and safety-related concerns. For AI-based decision support systems in healthcare settings, it is paramount to be reliable and trustworthy. Common dee...
Environmental protection and the reduction of carbon dioxide (CO2) emissions are central priorities within European climate policy. This study analyses and forecasts annual CO2 emissions in Greece using a univariate time-series framework. Annual data...
Bounded continuous data arise in many areas of applied probability and statistics, particularly when the underlying variable is restricted to a finite interval and the density is expected to vanish at the endpoints. This paper studies a parsimonious...
In the context of the clean and low-carbon transformation of power systems, addressing the challenge of day-ahead electricity market price prediction issues triggered by the strong stochastic volatility of power supply output due to high-penetration...
The global pasta industry is increasingly challenged to reconcile consumer demand for convenience with the need to reduce environmental impacts across the food supply chain. This study presents a cradle-to-grave Product Environmental Footprint (PEF)...
The accelerated deployment of electric vehicles requires planning tools able to quantify how much charging infrastructure can be integrated into distribution systems without violating operational constraints. This paper proposes a multi-scenario opti...
A method of reference-free speckle spectroscopy based on the statistical analysis of intensity spatial fluctuations of the spectrally-selected multiple-scattered fluorescence radiation is examined in the case of the finite-band spectral selection of...
Phosphorus (P) is an essential macronutrient crucial for both plant growth and crop production, playing a pivotal role in agriculture since the early 20th century. The symbiotic relationship between AMF and plants serves as a classic illustration. Th...
Cancers can manifest large variations in tumor phenotypes due to genetic and microenvironmental factors, which has motivated the development of quantitative radiomics-based image analysis with the aim to robustly classify tumor phenotypes in vivo. Po...