Objective: In this paper, we propose a Sine chaos mapping-based improved sparrow search algorithm (SSA) to optimize the BP neural network for trajectory prediction of inland river vessels because of the problems of poor accuracy and easy trapping in...
To optimize sparse rectangular planar array antennas under multiple constraints, including array aperture, number of elements, and minimum element spacing, an improved sparrow search algorithm (ISSA) is proposed. Initially, a position distribution ma...
Mildew of maize seeds may affect their germination rates and reduce crop quality. It is crucial to classify maize seeds efficiently and without destroying their original structure. This study aimed to establish hyperspectral datasets using hyperspect...
Artificial intelligence (AI) has become an instrument used in all domains with good results. The water resources management field is not an exception. Therefore, in this article, we propose two machine learning (ML) techniques—an echo state net...
We propose a novel fault-diagnosis approach for rolling bearings by integrating variational mode decomposition (VMD), refined composite multiscale dispersion entropy (RCMDE), and support vector machine (SVM) optimized by a sparrow search algorithm (S...
In the context of dam deformation monitoring, the prediction task is essentially a time series prediction problem that involves non-stationarity and complex influencing factors. To enhance the accuracy of predictions and address the challenges posed...
Inter-turn short circuits (ITSCs) in permanent magnet synchronous motors (PMSMs) pose significant risks due to their subtle early symptoms and rapid degradation. To address this, we propose an online real-time diagnostic method for assessing the degr...
It is difficult to determine unknown solar cell and photovoltaic (PV) module parameters owing to the nonlinearity of the characteristic current–voltage (I-V) curve. Despite this, precise parameter estimation is necessary due to the substantial...
Land subsidence is a prevalent geological issue that poses significant challenges to construction projects. Consequently, the accurate prediction of land subsidence has emerged as a focal point of research among scholars and experts. Traditional math...
As an industrial waste, slag powder can be processed and incorporated into cement-based materials as an additive, significantly improving the engineering properties of cement–soil. The strength of slag–cement-stabilized soil is subject to...
To solve the problems of the original sparrow search algorithm’s poor ability to jump out of local extremes and its insufficient ability to achieve global optimization, this paper simulates the different learning forms of students in each ranki...
Rapid urbanization has exacerbated traffic congestion and associated vehicle emissions, making real-time air quality index (AQI) prediction crucial for urban environmental management. Transportation emissions, including exhaust gases and particulate...
This study addresses speed sensor aging and electrical parameter variations caused by prolonged operation and environmental factors in flywheel energy storage systems (FESSs). A model reference adaptive system (MRAS) flywheel speed observer with para...
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...
In high-elevation or high-latitude permafrost areas, persistent subzero temperatures significantly impact the freeze–thaw durability of concrete structures. Traditional methods for studying the frost resistance of concrete in permafrost regions...
Intelligent workshop UAV inspection path planning is a typical indoor UAV path planning technology. The UAV can conduct intelligent inspection on each work area of the workshop to solve or provide timely feedback on problems in the work area. The spa...
In view of the difficulty in obtaining the membrane bioreactor (MBR) membrane flux in real time, considering the disadvantage of the back propagation (BP) network in predicting MBR membrane flux, such as the local minimum value and poor generalizatio...
Addressing real-time optimization problems becomes increasingly challenging as their complexity continues to escalate over time. So bio-optimization algorithms (BoAs) come into the picture to solve such problems due to their global search capability,...
Aiming at the shortcomings of the traditional sparrow search algorithm (SSA) in path planning, such as its high time-consumption, long path length, it being easy to collide with static obstacles and its inability to avoid dynamic obstacles, this pape...
The sparrow search algorithm (SSA) is a metaheuristic algorithm developed based on the foraging and anti-predatory behavior of sparrow populations. Compared with other metaheuristic algorithms, SSA also suffers from poor population diversity, has wea...
In the face of fire in buildings, people need to quickly plan their escape routes. Intelligent optimization algorithms can achieve this goal, including the sparrow search algorithm (SSA). Despite the powerful search ability of the SSA, there are stil...
To address the problems of limited population diversity and a tendency to converge prematurely to local optima in the original sparrow search algorithm (SSA), an improved sparrow search algorithm (ISSA) based on multi-strategy collaborative optimizat...
The prediction accuracy of 4D (four-dimensional) trajectory is crucial for aviation safety and air traffic management. Firstly, the sine chaotic mapping is employed to enhance the sparrow search algorithm (Sine-SSA). This enhanced algorithm optimizes...
Springback is an unavoidable problem in cold-forming processes and affects the efficiency and quality of the processing of outer sheets for ships. Therefore, effective control and prediction of sheet-forming springback is particularly important in th...
Industrial robots can cause servo system instability during operation due to friction between joints and changes in end loads, which results in jittering of the robotic arm. Therefore, this paper proposes a hybrid sparrow search algorithm (HSSA) meth...
Accurate power load forecasting has an important impact on power systems. In order to improve the load forecasting accuracy, a new load forecasting model, VMD–CISSA–LSSVM, is proposed. The model combines the variational modal decompositio...
Aiming at the problems of slow convergence and low accuracy of the traditional sparrow search algorithm (SSA), a multi-strategy improved sparrow search algorithm (ISSA) was proposed. Firstly, the golden sine algorithm was introduced in the location u...
Nowadays, fossil energy continues to dominate China’s energy usage; its inefficient use and large crude emissions of coal and fuel oil in its end-consumption have brought about great pressure to reduce emissions. Electrical power substitution a...
Aiming at the problem of the limited application range and low accuracy of existing radar calibration methods, this paper studies the radar calibration method based on cooperative targets, and establishes the integrated radar measurement error model....
Whether an unmanned aerial vehicle (UAV) can complete its mission successfully is determined by trajectory planning. Reasonable and efficient UAV trajectory planning in 3D environments is a complex global optimization problem, in which numerous const...
A landslide is a type of natural disaster that has the highest frequency, the widest distribution and the heaviest losses worldwide; landslides seriously threaten human life and property and major engineering facilities. Therefore, it is important to...
Nuclear power is a type of clean and green energy; however, there is a risk of radioactive material leakage when accidents occur. When radioactive material leaks from nuclear power plants, it has a great impact on the environment and personnel safety...
Blast furnace (BF) ironmaking is a key process in iron and steel production. Because BF ironmaking is a dynamic time series process, it is more appropriate to use a recurrent neural network for modeling. The long short-term memory (LSTM) network is c...
In the geophysical exploration field, the sonic log (DT) and shear sonic log (DTS) are frequently used as quick and affordable procedures for reservoir evaluation. Due to the high acquisition costs, DTS is only accessible in a few wells within an oil...
There is an important significance for human health in predicting atmospheric concentration precisely. However, due to the complexity and influence of contingency, atmospheric concentration prediction is a challenging topic. In this paper, we propose...
To improve the accuracy of coal and gas prominence prediction, an improved sparrow search algorithm (ISSA) and an optimized support vector machine (SVM) based on the Markov chain Monte Carlo (MCMC) filling algorithm prediction model were proposed. Th...
In order to solve the problem of low voltage caused by unbalanced load in the distribution network, a transformer loss intelligent prediction model under unbalanced load is proposed. Firstly, the mathematical model of a transformer with an unbalanced...
The reasonable and efficient use of the abundant biomass resources in rural areas has not been realized. Therefore, the concept of a combined cooling, heating, and power (CCHP) microgrid system, considering biomass pyrolysis and gasification, has bee...
The Sparrow Search Algorithm (SSA), a metaheuristic renowned for rapid convergence, good stability, and high search accuracy in continuous optimization, faces inherent limitations when applied to discrete multi-variable combinatorial optimization pro...
Aiming at the multi-parameter identification problem of an electro-hydraulic servo system, a multi-parameter identification method based on a penalty mechanism reverse nonlinear sparrow search algorithm (PRN-SSA) is proposed, which transforms the ide...
Given the non-stationarity, nonlinearity, and high complexity of polysilicon prices in the photovoltaic (PV) industry chain, this paper introduces upstream and downstream material prices of the PV industry chain and macroeconomic indicators as influe...
An accurate battery model is of great importance for battery state estimation. This study considers the parameter identification of a fractional-order model (FOM) of the battery, which can more realistically describe the reaction process of the cell...
Wire sawing is an important process in the cutting of NdFeB magnets and the sawed surface topography and surface roughness (SR) are important indicators for assessing surface quality. This paper analyzed the effects of process parameters on the sawed...
At present, establishing a multidimensional characteristic model of a boiler combustion system plays an important role in realizing its dynamic optimization and real-time control, so as to achieve the purpose of reducing environmental pollution and s...
At present, iris recognition has been widely used as a biometrics-based security enhancement technology. However, in some application scenarios where a long-distance camera is used, due to the limitations of equipment and environment, the collected i...
The internal temperature of the pigsty has a great impact on the pigs. Keeping the temperature in the pigsty within a certain range is a pressing problem in environmental control. The current pigsty temperature regulation method is based mainly on ma...
The density-based spatial clustering of applications with noise (DBSCAN) is able to cluster arbitrarily structured datasets. However, the clustering result of this algorithm is exceptionally sensitive to the neighborhood radius (Eps) and noise points...
The Ultra-Wideband (UWB) indoor positioning method is widely used in areas where no satellite signals are available. However, during the measurement process of UWB, the collected data contain random errors. To alleviate the effect of random errors on...
The “Curse of Dimensionality” induced by the rapid development of information science might have a negative impact when dealing with big datasets, and it also makes the problems of symmetry and asymmetry increasingly prominent. Feature se...
The accurate identification of a driver’s braking intention is crucial to the formulation of regenerative braking control strategies for electric vehicles. In this paper, a braking intention recognition model based on the sample entropy of the...
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