48 Results Found

This study proposes an RBF-PSO hybrid framework for efficient inversion analysis of hydration heat parameters in mass concrete temperature fields, addressing the computational inefficiency and accuracy limitations of traditional methods. By integrati...

To satisfy the requirement of real-time and accurate control of the system, a time-delay prediction control system based on the PSO-RBF neural network model is established to solve the effect of time delay on the control system’s performance. F...

We propose a joint optimization algorithm that combines the optimal shape parameter–Gaussian radial basis function (G-RBF) surrogate model with global and local optimization techniques to improve accuracy and reduce costs. We analyze factors th...

The paper proposes an adaptive selection method for the shape parameter in the multi-quadratic radial basis function (MQ-RBF) interpolation of two-dimensional (2D) scattered data and achieves good performance in solving integral equations (O-MQRBF)....

With the rapid development of new technologies, such as big data, the Internet of Things (IoT) and intelligent sensing, the traditional asphalt pavement construction quality evaluation method has been unable to meet the needs of road digital construc...

In recent years, safety issues respecting polar ship navigation in the presence of ice have become a research hotspot. The accurate prediction of propulsion power plays an important role in ensuring safe ship navigation and evaluating ship navigation...

In this paper, a radial basis function neural network (RBFNN) surrogate model optimized by an improved particle swarm optimization (PSO) algorithm is developed to reduce the computation cost of traditional antenna design methods which rely on high-fi...

The Internet of Things (IoT) is a rapidly growing network that shares information over the Internet via interconnected devices. In addition, this network has led to new security challenges in recent years. One of the biggest challenges is the impact...

A strategy was proposed to determine the optimal operating point for the proportional-integral-derivative (PID) controller of a wind turbine, and identify the stability regions in the parameter space. The proposed approach combined particle swarm opt...

In this study, vibration sensors were used to measure blast-induced ground vibration (PPV). Different evolutionary algorithms were assessed for predicting PPV, including the particle swarm optimization (PSO) algorithm, genetic algorithm (GA), imperia...

Dust is one of the components causing heavy environmental pollution in open-pit mines, especially PM₁₀. Some pathologies related to the lung, respiratory system, and occupational diseases have been identified due to the effects of PM₁₀ in open-pit mi...

A neural network model based on a chaotic particle swarm optimization (CPSO) radial basis function-back propagation (RBF-BP) neural network was suggested to improve the accuracy of reactor temperature prediction. The training efficiency of the RBF-BP...

This study addresses the critical challenge of insufficient classification accuracy for different defect signals in rail magnetic flux leakage (MFL) detection by proposing an enhanced intelligent classification framework based on particle swarm optim...

Sewage treatment plants face significant problems as a result of the annual growth in urban sewage discharge. Substandard sewage discharge can also be caused by rising sewage treatment expenses and unpredictable procedures. The most widely used sewag...

A tunnel excavation model with weak interlayers is established to analyze the effect of different angles and thicknesses on the displacement of the surrounding rock. Based on catastrophe theory, a stability criterion for surrounding rock displacement...

Aiming to address the frequent design conflicts arising during multi-disciplinary collaboration in the detailed design phase of large cruise ships, coupled with the inadequacy of traditional methods in detecting unknown constraints, this paper propos...

Microarray gene expression-based detection and classification of medical conditions have been prominent in research studies over the past few decades. However, extracting relevant data from the high-volume microarray gene expression with inherent non...

After rolling, TP2 copper tubes exhibit defects such as sawtooth marks, cracks, and uneven wall thickness after joint drawing, which severely affects the quality of the finished copper tubes. To study the effect of drawing process parameters on wall...

Coal mine safety is vital not only for maintaining production operations but also for ensuring the industry’s sustainable development. The threat posed by mine water hazards is especially severe, growing more critical as mining activities becom...

To address the inefficiencies of traditional numerical simulations and the high cost of experimental validation in the aerodynamic–stealth integrated design of S-shaped inlets for aero-engines, this study proposes a novel parameter prediction m...

The thermal error modeling technology of computer numerical control (CNC) machine tools is the core of thermal error compensation, and the machining accuracy of CNC machine tools can be improved effectively by the high-precision prediction model of t...

Diabetes is a life-threatening, non-communicable disease. Diabetes mellitus is a prevalent chronic disease with a significant global impact. The timely detection of diabetes in patients is necessary for an effective treatment. The primary objective o...

As the core component in intelligent manufacturing systems, the precise control of the welding clamp’s electrode pressure plays a decisive role in ensuring the quality of spot welding. This paper proposes a novel pressure control strategy for r...

Background/Objectives: Photoplethysmography (PPG) signals, which measure blood volume changes through light absorption, are increasingly used for non-invasive cardiovascular disease (CVD) detection. Analyzing PPG signals can help identify irregular h...

High-precision forecasting of short-term wind power (WP) is integral for wind farms, the safe dispatch of power systems, and the stable operation of the power grid. Currently, the data related to the operation and maintenance of wind farms mainly com...

Laser–arc composite additive manufacturing holds significant potential for a wide range of industrial applications, and the control of morphological dimensions in the deposited layer is a critical aspect of this technology. The width and height...

With the growing emphasis on eco-friendly and sustainable development concepts, new energy vehicles (NEVs) have emerged as a popular alternative to traditional fuel vehicles (FVs). Due to the absence of an internal combustion engine, electric vehicle...

The fast and accurate classification of surrounding rock mass is the basis for tunnel design and construction and has significant value in engineering applications. Therefore, this paper proposes a method for classifying and predicting surrounding ro...

The real-life signals captured by different measurement systems (such as modern maritime transport characterized by challenging and varying operating conditions) are often subject to various types of noise and other external factors in the data colle...

Titanium alloys have become an indispensable material for all walks of life because of their excellent strength and corrosion resistance. However, grinding titanium alloy is exceedingly challenging due to its pronounced material characteristics. Ther...

This paper reviews technological advances in precision fertilizer application from 2020 to 2025, addressing the need for a systematic synthesis of recent innovations to support agricultural sustainability. With precision fertilization critical for ef...

The combustion of fossil fuels from the input of oil refineries, power plants, and the venting or flaring of produced gases in oil fields leads to greenhouse gas emissions. Economic usage of greenhouse and flue gases in conventional and unconventiona...

Carbon dioxide-based enhanced oil-recovery (CO₂-EOR) processes have gained considerable interest among other EOR methods. In this paper, based on the molecular weight of paraffins (n-alkanes), pressure, and temperature, the magnitude of CO₂–n-alkanes...

It is very important to keep structures and constructional elements in service during and after exposure to elevated temperatures. Investigation of the structural behaviour of different components and structures at elevated temperatures is an approac...

As a high performance-cost ratio solution for differential pressure measurement, piezo-resistive differential pressure sensors are widely used in engineering processes. However, their performance is severely affected by the environmental temperature...

Assessing the quality of corn seeds necessitates evaluating their water, fat, protein, and starch content. This study integrates hyperspectral imaging technology with chemometric analysis techniques to achieve non-invasive and rapid detection of mult...

As is well known, the correct diagnosis for cancer is critical to save patients’ lives. Support vector machine (SVM) has already made an important contribution to the field of cancer classification. However, different kernel function configurat...

The recent advancements in sensor, big data, and artificial intelligence (AI) have introduced digital transformation in the manufacturing industry. Machine maintenance has been one of the central subjects in digital transformation in the manufacturin...

With the advancement of the Internet, social media platforms have gradually become powerful in spreading crisis-related content. Identifying informative tweets associated with natural disasters is beneficial for the rescue operation. When faced with...

Multi-kernel learning methods are essential kernel learning methods. Still, the base kernel functions in most multi-kernel learning methods only with select kernel functions with shallow structures, which are weak for large-scale uneven data. We prop...

With the improvement of UAV performance and intelligence in recent years, it is particularly important for unmanned aerial vehicles (UAVs) to improve the ability of autonomous air combat. Aiming to solve the problem of how to improve the autonomous a...

In this paper, a model predictive control (MPC) method optimized by an adaptive particle swarm optimization (APSO) algorithm is proposed. Combined with non-singular terminal sliding mode control (NTSMC), the inner and outer double-closed-loop control...

The development of a battery-type loader is an important research direction in the field of industrial mining equipment. In the energy system, the battery will inevitably encounter the problem of heat dissipation when using high-power electricity. In...

Driving Decision-making Mechanism (DDM) is identified as the key technology to ensure the driving safety of autonomous vehicle, which is mainly influenced by vehicle states and road conditions. However, previous studies have seldom considered road co...

Asphaltenes deposition is considered a serious production problem. The literature does not include enough comprehensive studies on adsorption phenomenon involved in asphaltenes deposition utilizing inhibitors. In addition, effective protocols on hand...

Amid concerns about environmental degradation and the consumption of non-renewable energy, the development of electric vehicles (EVs) has accelerated, with increasing focus on safety. On the road, battery packs are exposed to potential risks from unf...

Gasoline is the primary fuel used in small cars, and the exhaust emissions from gasoline combustion have a significant impact on the atmosphere. Efforts to clean up gasoline have therefore focused primarily on reducing the olefin and sulfur content o...

As an environmentally responsible alternative to conventional concrete, geopolymer concrete recycles previously used resources to prepare the cementitious component of the product. The challenging issue with employing geopolymer concrete in the build...