The accurate prediction of Li-ion battery capacity is important because it ensures mission and personnel safety during operations. However, the phenomenon of capacity recovery (CR) may impede the progress of improving battery capacity prediction perf...
Metal-organic frameworks (MOFs) have been widely researched as drug delivery systems due to their intrinsic porous structures. Herein, machine learning (ML) technologies were applied for the screening of MOFs with high drug loading capacity. To achie...
Regional coordinated development is an important policy to promote socio-economic development, especially in the Yangtze River Delta, Greater Bay Area and others, which is one of the guidelines of the 14th Five-Year Plan for economic development. The...
The rapid development of urbanization, population growth, and unreasonable use of land resources have made the contradiction between human beings and land increasingly prominent, and the carrying capacity of land resources has become an important fac...
Recently, a number of similarity-based methods have been proposed for link prediction of complex networks. Among these indices, the resource-allocation-based prediction methods perform very well considering the amount of resources in the information...
Battery technology plays an increasingly vital role in portable electronic devices, electric vehicles, and renewable energy storage. During operation, batteries undergo performance degradation, which not only reduces device efficiency, but may also p...
Using different fast charging strategies for lithium-ion batteries can affect the degradation rate of the batteries. In this case, predicting the capacity fade curve can facilitate the application of new batteries. Considering the impact of fast char...
The integration of vehicle-to-grid (V2G) technology into smart energy management systems represents a significant advancement in the field of energy suppliers for Industry 4.0. V2G systems enable a bidirectional flow of energy between electric vehicl...
The burgeoning utilization of lithium-ion batteries within electric vehicles and renewable energy storage systems has catapulted the capacity prediction of such batteries to a pivotal research frontier in the energy storage domain. Precise capacity p...
Future capacity prediction of lithium-ion batteries is a highly researched topic in the field of battery management systems, owing to the gradual degradation of battery capacity over time due to various factors such as chemical changes within the bat...
To address the existing challenges of lacking a unified and reliable shear capacity prediction model for fiber-reinforced polymer (FRP)-strengthened reinforced concrete beams (FRP-SRCB) and the excessive experimental workload, this study establishes...
Lithium-ion batteries (LIBs) have been widely used for electric vehicles owing to their high energy density, light weight, and no memory effect. However, their health management problems remain unsolved in actual application. Therefore, this paper fo...
The accurate prediction of lithium-ion battery capacity is crucial for the safe and efficient operation of battery systems. Although data-driven approaches have demonstrated effectiveness in lifetime prediction, the acquisition of lifecycle data for...
In this study, ensemble learning (EL) models are designed to enhance the accuracy and efficiency in predicting the flexural ultimate capacity of reinforced ultra-high-performance concrete (UHPC) beams with the aim of providing a more reliable and eff...
Given the stochastic nature of wind, wind power grid-connected capacity prediction plays an essential role in coping with the challenge of balancing supply and demand. Accurate forecasting methods make enormous contribution to mapping wind power stra...
Energy storage is recognized as a key technology for enabling the transition to a low-carbon, sustainable future. Energy storage requires careful management, and capacity prediction of a lithium-ion battery (LIB) is an essential indicator in a batter...
Predicting the cooling capacity of converter valves is crucial for maintaining the stability and efficiency of high-voltage direct current (HVDC) systems. This task involves handling complex, multi-dimensional time-series data with strong inter-varia...
The strengthening of reinforced concrete (RC) beams with aluminum alloy was typically implemented in a symmetrical configuration. To evaluate the flexural performance of strengthened beams, four machine learning (ML)-based models, namely Random Fores...
The yield of photovoltaic hydrogen production systems is influenced by a number of factors, including weather conditions, the cleanliness of photovoltaic modules, and operational efficiency. Temporal variations in weather conditions have been shown t...
Accurate remaining capacity prediction (RCP) of lithium-ion batteries (LIBs) is crucial for ensuring their safety, reliability, and performance, particularly amidst the growing energy crisis and environmental concerns. However, the complex aging proc...
In the selection and design of ionic liquids (ILs) for various applications, including heat transfer fluids, thermal energy storage materials, fuel cells, and solvents for chemical processes, heat capacity is a key thermodynamic property. While sever...
In this paper, a method of capacity trajectory prediction for lead-acid battery, based on the steep drop curve of discharge voltage and improved Gaussian process regression model, is proposed by analyzing the relationship between the current availabl...
Machine learning methods have demonstrated significant advantages in predicting the shear mechanical performance of concrete connectors. However, the application to nailed connections in wood structures remains limited. Accurate prediction of the she...
Lithium–ion battery development necessitates predicting capacity fading using early cycle data to minimize testing time and costs. This study introduces a hybrid physics–guided data–driven approach to address this challenge by accur...
It is crucial to study the axial compression behavior of concrete-filled steel tubular (CFST) columns to ensure the safe operation of engineering structures. The restriction between steel tubular and core concrete in CFSTs is complex and the relation...
The adsorption of Fe(III) onto the surface of microplastics (MPs) enhances their toxicity and mobility in aquatic environments, posing a serious threat to human health and ecosystem balance. This study investigated the adsorption mechanism and influe...
This study proposes a novel deep learning framework for predicting the shear capacity of slender reinforced concrete (RC) beams without shear reinforcement. The proposed approach employs convolutional neural networks and autoencoders to transform str...
High temperatures can enhance the chloride diffusion coefficient and this poses a threat to reinforced concrete (RC) piles. This study intends to propose predictive models that can evaluate the service life and lateral bearing behaviour of reinforced...
Concrete filled steel tubes (CFSTs) show advantageous applications in the field of construction, especially for a high axial load capacity. The challenge in using such structure lies in the selection of many parameters constituting CFST, which necess...
The development of self-compacting concrete-filled thin-walled steel tubular columns is a potential strategy to ease the challenge of conserving resources in society, which are largely consumed by the quickly developing civil industry. However, the a...
The problem of water resources damage caused by coal mining has restricted the sustainable development of Yu-Shen mining area. Illustrating the relationship between mining and water resources carrying capacity is of great significance to solve this p...
Prediction of rock fracturing capacity demands particular requirements for the exploitation of mineral resources, especially for the parameter design of conical pick performance for hard rock fragmentation, which must take into account differences in...
Rapid and accurate prediction of the maximum remaining life of lithium-ion batteries is a critical technical challenge for enhancing battery management system reliability and enabling the efficient secondary utilization of retired batteries. Traditio...
Machine learning models are now capable of delivering coveted digital soil mapping (DSM) benefits (e.g., field capacity (FC) prediction); therefore, determining the optimal sample sites and sample size is essential to maximize the training efficacy....
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...
Machine learning has emerged as a promising tool to accelerate the screening of lithium–ion battery electrode materials. Gravimetric capacity, a critical performance indicator governing electrode energy density, is intrinsically related to lith...
Water environmental carrying capacity (WECC) is an important support for social and economic development and is closely related to regional production and consumption patterns. Exploring the level of WECC and its evolution trend is very urgent for th...
Vehicle-to-grid (V2G) technology is emerging as an innovative paradigm for improving the electricity grid in terms of stabilization and demand response, through the integration of electric vehicles (EVs). A cornerstone in this field is the estimation...
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Global heating is subjecting more of the planet to longer periods of higher heat stress categories commonly employed to determine safe work durations. This study compared predicted worker heat strain and labour capacity for a recent normal climate (1...
Accurately predicting the remaining useful life (RUL) of lithium-ion batteries (LIBs) is important for electronic equipment. A new algorithm is proposed to aim at the nonlinear degradation caused by capacity regeneration and random fluctuations. Firs...
Terminal airspace is the convergence area of air traffic flow, which is the bottleneck of air traffic management. With the rapid growth of air traffic volume, the impact of convective weather on flight operations is becoming more and more serious. To...
This paper presents the application of simulation to assess and predict the influence of random factors of pedestrian flow and its continuity on the traffic capacity of a signal-controlled intersection during a right turn. The data were collected fro...
Accurate prediction of lithium-ion battery capacity degradation under dynamic loads is crucial yet challenging due to limited data availability and high cell-to-cell variability. This study proposes a Latent Gaussian Process (GP) model to forecast th...
Prediction of pile bearing capacity has been considered an unsolved problem for years. This study presents a practical solution for the preparation and maximization of pile bearing capacity, considering the effects of time after the end of pile drivi...
SARS-CoV-2 infection might cause a critical disease, and patients’ follow-up is based on multiple parameters. Oxidative stress is one of the key factors in the pathogenesis of COVID-19 suggesting that its level could be a prognostic marker. The...
Ventilatory pump failure is a common cause of death for patients with neuromuscular diseases. The vital capacity plateau value (VCPLAT) is an important indicator to judge the status of ventilatory pump failure for patients with congenital myopathy, D...
In recent years, the information requirements of pumping stations have become higher and higher. The prediction of overflow capacity can provide important reference for flood carrying capacity, water resource scheduling and water safety. In order to...
Prediction of Remaining Useful Life (RUL) of lithium-ion batteries plays a significant role in battery health management. Battery capacity is often chosen as the Health Indicator (HI) in research on lithium-ion battery RUL prediction. In the rest tim...
This paper describes CAREUP, a novel older adult healthy aging support platform based on Intrinsic Capacity (IC) monitoring. Besides standard functionalities like storing health measurement data or providing users with personalized recommendations, t...
The Air Traffic Control (ATC) system suffers from an ever-increasing demand for aircraft, leading to capacity issues. For this reason, airspace is regulated by limiting the entry of aircraft into the airspace. Knowledge of these regulations before th...
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