In this paper, a traction load model parameter identification method based on the improved sparrow search algorithm (ISSA) is proposed. According to the load characteristics of the AC traction power supply system under transient disturbance, the mode...
Excavation load prediction is of great importance for the prior design and latter performance evaluation of tunnel boring machines (TBMs). In this paper, an improved load prediction model is developed based on classical Colorado school of mines model...
This article reflects the main sources of risks for metallurgical enterprises in Russia, presenting the implementation of an innovative approach to increasing the competitiveness of an industrial enterprise, which is a typical representative of large...
The effectiveness of implementing the total maximum daily load (TMDL) in the Gyeongan stream watershed was evaluated to assess its impact on water quality. The relationships between water quality and flow rate and load and water quality were reinterp...
The active distribution network has been fully developed because it can achieve efficient energy utilization through the effective control of distributed generation, electrical energy storage, and active loads. However, the research on the reliabilit...
To better utilize air-conditioning load in terms of demand side response potential and improve precision and speed, a control strategy of traditional temperature-control air conditioning, determining frequency load as the research object, and air con...
A wet clutch is the key component to realize power uninterrupted in agricultural machinery operation. To reduce impact of the system and improve engagement quality, this paper studies and establishes the dynamic load characteristics model of a wet cl...
During the load distribution of hydropower units, the frequent crossing of vibration zones as well as large output fluctuations affect the stability of the power station. A multi-objective double-layer intelligent nesting model that considers the con...
The nature of the fracture and fragmentation processes in concrete medium under blast loading is the transformation of the medium from continuum to discontinuity. Coupled with the significant rate correlation of concrete medium, its mechanical behavi...
To cope with the energy crisis and environmental pollution, the future development of the power system has to change towards a clean, low-carbon, flexible, and diversified direction. This paper proposes a decentralized power dispatching model based o...
Accurate electricity demand forecasting is crucial for ensuring the sustainability and reliability of power systems. Least square support vector machines (LSSVM) are well suited to handle complex non-linear power load series. However, the less optima...
The aim of this study is to address the limitations of fixed parameters and poor adaptability in traditional damage models for damage assessment of reinforced concrete (RC) columns under variable axial load. An improved damage model considering the i...
The gear drive generally operates in elastohydrodynamic lubrication (EHL) contacts, and the existence of oil film effectively reduces wear and improves transmission stability. However, little research has been devoted to studying the effect of lubric...
Improving the accuracy of power load forecasting is an important link in the optimization of power systems. Most of the existing studies in the short-term load forecasting task at present have the problem of insufficient extraction of multi-scale fea...
Load disaggregation is the process of identifying an individual appliance’s power demand within aggregate electrical load data. Virtually all recently proposed disaggregation methods are based on neural networks, thanks to their superior perfor...
The creep equation of the classical Burgers model was originally derived for constant stress. Although series-based solutions have extended this model to trapezoidal cyclic loading, they require truncation of the series, which introduces approximatio...
Power load prediction is fundamental for ensuring the reliability of power grid operation and the accuracy of power demand forecasting. However, the uncertainties stemming from power generation, such as wind speed and water flow, along with variation...
Energy prediction used for building heating has attracted particular attention because it is often required in the development of various strategies to improve the energy efficiency of buildings, especially those undergoing thermal improvements. The...
As short-term load forecasting is essential for the day-to-day operation planning of power systems, we built an ensemble learning model to perform such forecasting for Thai data. The proposed model uses voting regression (VR), producing forecasts wit...
Prediction of fatigue failure in concrete structures remains a major challenge due to progressive material degradation. Reliable prediction, therefore, requires modeling the 3D heterogeneous microstructure of concrete to explain the underlying mechan...
This paper suggests an innovative approach for the ideal placement and categorization of capacitors in radial distribution networks (RDNs) by applying symmetric fuzzy and improved bacterial foraging optimization algorithm (IBFOA) solutions. The react...
In a smart city environment, with increased demand for energy efficiency, information exchange and communication through wireless sensor networks (WSNs) plays an important role. In WSNs, the sensors are usually operating in clusters, and they are all...
Non-intrusive load monitoring is the main trend of green energy-saving electricity consumption at present, and load identification is a core part of non-invasive load monitoring. A support vector machine (SVM) is commonly used in load recognition, bu...
This paper presents a new, accurate load forecasting technique robust to fluctuations due to unusual load behavioral changes in buildings, i.e., the potential for small commercial buildings with heterogeneous stores. The proposed scheme is featured w...
Environmental loading, in particular from continental water storage changes, induces geodetic station displacements up to several centimeters for the vertical components. We investigate surface deformation due to loading processes in South America us...
Precision operation is one of the crucial means to reduce costs and consumption in the agricultural production process. To enhance the operational efficiency of machinery, combined operation machines are often used for tillage operations. A large unb...
With the rapid expansion of variable renewable energy, coal-fired units are increasingly operated at low load, where non-convex cost characteristics pose challenges for spot market clearing. This study reviews and improves existing low-load generatio...
To address the current difficulties and problems of short-term load forecasting (STLF), this paper proposes a combined forecasting method based on the improved sparrow search algorithm (ISSA), with fused Cauchy mutation and opposition-based learning...
Electricity loads are basic and important information for power generation facilities and traders, especially in terms of production plans, daily operations, unit commitments, and economic dispatches. Short-term load forecasting (STLF), which predict...
This paper proposes a hybrid forecasting method (VMD–KPCA–xLSTM–Informer) based on variational-mode decomposition (VMD), kernel principal component analysis (KPCA), extended long short-term memory network (xLSTM), and the Informer m...
Artificial intelligence algorithms (AIAs) have gained widespread adoption in air conditioning load prediction. However, their prediction accuracy is substantially influenced by the quality of training samples. To improve the prediction accuracy of ai...
Simple load forecasting and overload prediction models, such as LSTM and XGBoost, are unable to handle the increasing amount of data in power systems. Recently, various foundation models (FMs) for time series analysis have been proposed, which can be...
Short-term power load forecasting plays a key role in daily scheduling and ensuring stable power system operation. The problem of the volatility of the power load sequence and poor prediction accuracy is addressed. In this study, a learning model int...
In the context of global efforts toward energy conservation and emission reduction, accurate short-term electric load forecasting plays a crucial role in improving energy efficiency, enabling low-carbon dispatching, and supporting sustainable power s...
Energy pile technology integrates geothermal energy exploitation with pile foundation bearing, yet accurately evaluating its thermo-mechanical performance remains theoretically challenging. To address the limitations of traditional load-transfer meth...
The accuracy requirements for short-term power load forecasting have been increasing due to the rapid development of the electric power industry. Nevertheless, the short-term load exhibits both elasticity and instability characteristics, posing chall...
With the rapid global proliferation of electric vehicles (EVs), their integration as a significant load component within power systems increasingly influences the stable operation and planning of electrical grids. However, the high uncertainty and ra...
This paper is based on small-scale laboratory tests (1:10) of a rigid inclusion-improved soil under normal gravity. A low area improvement ratio (2.4%) under monotonic and cyclic loading was used. 3D numerical calculations are performed to model thes...
The collective impacts of rapid urbanization, poor pollution management practices and insufficient sanitation infrastructure have driven the water quality deterioration in Little Akaki River (LAR), Ethiopia. Water quality modeling using QUAL2Kw was c...
Accurate load forecasting is crucial to the stable operation of integrated energy systems (IES), which plays a significant role in advancing sustainable development. Addressing the challenge of insufficient prediction accuracy caused by the inherent...
Suspended sediment load (Qs) is an important parameter in the analysis of hydrological processes and management of water resources. Direct methods of measuring Qs are costly and require precise instruments, which makes their application limited, espe...
Chronic kidney disease (CKD) involves uremic toxin-driven tubular injury and systemic vascular dysfunction, in which mitochondrial impairment and apoptotic cell loss contribute to progressive tissue deterioration. Accordingly, a targeted EV platform...
Load forecasting is a research hotspot in academia; in the context of new power systems, the prediction and determination of load reserve capacity is also important. In order to adapt to new forms of power systems, a day-ahead automatic generation co...
Structures made of Roller Compacted Concrete (RCC) may be subjected to dynamic loads during their service life. Understanding the dynamic material properties of RCC and the performance of RCC structures is essential for better analysis and design of...
Integrated Energy Systems (IESs) are characterized by strong nonstationarity, seasonal heterogeneity, and stochastic fluctuations in electric, cooling, and heating loads, making accurate and reliable probabilistic forecasting challenging. To address...
Functional recovery following traumatic brain injury (TBI) is limited due to progressive neuronal damage resulting from secondary injury-associated neuroinflammation. Steroidal anti-inflammatory drugs, such as dexamethasone (DX), can reduce neuroinfl...
In this study, a two-stage stochastic programming (TSP) model was developed for supporting regional waste load(chemical oxygen demand (COD)and NH3-N) allocation in four main pollution departments (industry, municipal, livestock breeding, and agricult...
Pancreatic cancer (PC) represents an intriguing topic for researchers. To date, the prognosis of metastasized PC is poor with just 7% of patients exceeding a five-year survival period. Thus, molecular modifications of existing drugs should be develop...
Accurate power load forecasting plays an important role in smart grid analysis. To improve the accuracy of forecasting through the three-level “decomposition–optimization–prediction” innovation, this study proposes a predictio...
Reasonable fatigue load should be determined before bridge fatigue analysis. However, the design frequency calculation method of the standard vehicle does not always make sense when the standard vehicle load model that is provided by existing standar...
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