Well-separated pair decomposition (WSPD) is a well known geometric decomposition used for encoding distances, introduced in a seminal paper by Paul B. Callahan and S. Rao Kosaraju in 1995. WSPD compresses
Micromilling is an extremely important advanced manufacturing technology in the micromanufacturing industry. Compared with the traditional milling process, micromilling has stricter requirements on the surface roughness of the workpiece, and the roug...
In this work, the exact and approximate solution for generalized linear, nonlinear, and coupled systems of fractional singular M-dimensional pseudo-hyperbolic equations are examined by using the multi-dimensional Laplace Adomian decomposition method...
The paper explores the changes in the determinants of interprovincial inequality in China during the period of 2000 to 2017 by way of bi-dimensional decomposition method. The method integrates two inequality decompositions by both regional groups and...
Accurate temperature measurement in coal-fired power plants is crucial for optimizing combustion and achieving deep load regulation. While acoustic temperature measurement is an efficient and stable method, its practical application is limited to two...
In this article, a new analytical technique based on an innovative transformation is used to solve (2+time fractional-order) dimensional physical models. The proposed method is the hybrid methodology of Shehu transformation along with Adomian decompo...
Evolutionary algorithms have been widely applied for solving multi-objective optimization problems, while the feature selection in classification can also be treated as a discrete bi-objective optimization problem if attempting to minimize both the c...
To address the core challenges of multivariate nonlinear coupling and long-term temporal dependency in 4D UAV trajectory prediction, this study proposes an innovative model named KAN-Former. On a 21-dimensional multimodal UAV dataset, KAN-Former achi...
Three-dimensional elliptical vibration cutting (3D-EVC) is one of the machining methods with the most potential in ultra-precision machining; its unique characteristics of intermittent cutting, friction reversal, and ease of chip removal can improve...
The external electric field (E-field), which is an important stimulus, can change the decomposition mechanism and sensitivity of energetic materials. As a result, understanding the response of energetic materials to external E-fields is critical for...
Excitation-emission matrix (EEM) fluorescence spectroscopy is a noninvasive method for tissue diagnosis and has become important in clinical use. However, the intrinsic characterization of EEM fluorescence remains unclear. Photobleaching and the comp...
To address the limitations of traditional methods in adapting to complex operating conditions, this paper proposes a fault diagnosis approach combining multi-scale empirical mode decomposition (MS-EMD) and a one-dimensional convolutional neural netwo...
Though the proper orthogonal decomposition (POD) method has been widely adopted in flow analysis, few publications have systematically studied the influence of different POD processing methods on the POD results. This paper investigates the effects o...
Constrained by cost, measuring conditions and excessive calculation, it is difficult to reconstruct a 3D real-time temperature field. For the purpose of solving these problems, a three-dimensional temperature distribution reconstruction algorithm bas...
The human functional connectome (FC) is a representation of the functional couplings between brain regions derived from blood oxygen level-dependent (BOLD) signals. Over the past decade, studies related to FC fingerprinting have sought to uncover fun...
Proper orthogonal decomposition (POD) is a widely used linear dimensionality reduction technique, but it often fails to capture critical features in complex nonlinear flows. In contrast, clustering methods are effective for nonlinear feature extracti...
The problem of QR decomposition is considered one of the fundamental problems commonly encountered in both scientific research and engineering applications. In this paper, the QR decomposition for complex-valued time-varying matrices is analyzed and...
For the purpose of solving the large temperature field reconstruction error caused by different measuring point arrangements and the problem that the prior dataset cannot be built due to data loss or distortion in actual measurement, a three-dimensio...
In the present work we introduced a new method and name it the conformable double Laplace decomposition method to solve one dimensional regular and singular conformable functional Burger’s equation. We studied the existence condition for the co...
The multisource data fusion technique has been proven to perform better in crop classification. However, traditional fusion methods simply stack the original source data and their corresponding features, which can be only regarded as a superficial fu...
In this work, we investigate the solutions of fractional singular m-dimensional pseudo-hyperbolic equations. To address these equations effectively, we generalise the Natural transform to the multi-dimensional case and examine several of its essentia...
The COVID-19 pandemic has exerted an enormous impact on the Indonesian economy. In 2020, the country’s economy contracted by 2.7%. However, the impact has been spatially heterogeneous. Based on provincial GDP across industrial sectors, this stu...
Simultaneous localization and mapping (SLAM) faces significant challenges due to high computational costs, low accuracy, and instability, which are particularly problematic because SLAM systems often operate in real-time environments where timely and...
For the high-dimensional covariance estimation problem, when
Rotating machinery is widely used in industrial applications. With the trend towards more precise and more critical operating conditions, mechanical failures may easily occur. Condition monitoring and fault diagnosis (CMFD) technology is an effective...
In this paper, a novel technique called the Elzaki decomposition method has been using to solve fractional-order multi-dimensional dispersive partial differential equations. Elzaki decomposition method results for both integer and fractional orders a...
Terrain classification is an important research direction in the field of remote sensing. Hyperspectral remote sensing image data contain a large amount of rich ground object information. However, such data have the characteristics of high spatial di...
This paper presents an Enhanced Multilinear Principal Component Analysis (EMPCA) algorithm, an improved variant of the traditional Multilinear Principal Component Analysis (MPCA) tailored for efficient dimensionality reduction in high-dimensional dat...
In this paper, the disbond-type defect presented on glass fiber reinforced plastic material is analyzed by refining the guided Lamb wave signals. A segment of wind turbine blade is considered as a test sample. The low-frequency ultrasonic measurement...
Partitioning rectangular and rectilinear shapes in n-dimensional binary images into the smallest set of axis-aligned n-cuboids is a fundamental problem in image analysis, pattern recognition, and computational geometry, with applications in object de...
The fault detection time identified by relying on the over-voltage criterion of zero-sequence voltage often lags behind the actual occurrence time of ground faults, which may cause fault protection methods based on transient quantity principles to mi...
This paper proposes a new method for calculating the quaternion discrete Fourier transform for one-dimensional data. Although the computational complexity of the proposed method still belongs to the
Clustering electric load curves is an important part of the load data mining process. In this paper, we propose a clustering algorithm by combining singular value decomposition and KICIC clustering algorithm (SVD-KICIC) for analyzing the characterist...
There are several complex and unpredictable aspects that affect the power grid. To make short-term power load forecasting more accurate, a short-term power load forecasting model that utilizes the VMD-Crossformer is suggested in this paper. First, th...
Multi-wavelength ghost imaging usually involves extensive data processing and faces challenges such as poor reconstructed image quality. In this paper, we propose a multi-wavelength computational ghost imaging method based on feature dimensionality r...
The Buzhaoba open-pit mine is an important lignite production base in Yunnan Province, China. As mining activities have continued to progress, varying degrees of deformation have occurred in different areas of the Buzhaoba open-pit mine, threatening...
(1) Background: Coal mining operations caused severe land subsidence and altered the distributions of soil nutrients that influenced by multiple environmental factors at different scales. However, the prediction performances for soil nutrients based...
The enormous amount of data that are generated by hyperspectral remote sensing images (HSI) combined with the spatial channel’s limited and fragile bandwidth creates serious transmission, storage, and application challenges. HSI reconstruction...
This research article introduces the four-dimensional natural transform Adomian decomposition method (FNADM) for solving the (3+1)-dimensional time-singular fractional coupled Burgers’ equation, along with its associated initial conditions. The...
Investigating flow separation regions on the surfaces of three-dimensional bluff bodies in turbulent flows is important because these regions can induce significant aerodynamic loads. Separation bubbles can generate extreme pressures, making the roof...
The demand for small-size multi-stage hydraulic turbines is experiencing rapid growth due to the ongoing efforts towards energy conservation and emission reduction. On account of their compact structural design, these turbines feature a more intricat...
Higher education evaluation presents itself as a worldwide trend. It aims to improve performance due to its importance for economic and personal growth. Graduate activities are essential for Brazilian research and innovation systems. However, previou...
Rolling mill multi-row bearings are subjected to axial loads, which cause damage of rolling elements and cages, so the axial vibration signal contains rich fault character information. The vertical shock caused by the failure is weakened because mult...
Control chart pattern recognition was initially focused on single patterns with the assumption of normal, independent, and identical distribution. In practice, though, these assumptions are rarely valid in manufacturing processes, due to numerous inf...
In the intelligent fault diagnosis of rotating machinery, it is difficult to extract early weak fault impact features of rotating machinery under the interference of strong background noise, which makes the accuracy of fault identification low. In or...
Surface subsidence hazards in mining areas are common geological disasters involving issues such as vegetation degradation and ground collapse during the mining process, which also raise safety concerns. To address the accuracy issues of traditional...
Long-time-series climate prediction is of great significance for mitigating disasters; promoting ecological civilization; identifying climate change patterns and preventing floods, drought and typhoons. However, the general public often struggles wit...
Automatic plant phenotype measurement technology based on the rapid and accurate reconstruction of maize structures at the seedling stage is essential for the early variety selection, cultivation, and scientific management of maize. Manual measuremen...
The essential goal of this work is to suggest applying the multi-dimensional Sumdu generalized Laplace transform decomposition for solving pseudo-parabolic equations. This method is a combination of the multi-dimensional Sumudu transform, the general...
Short-term load forecasting (STLF) has a significant role in reliable operation and efficient scheduling of power systems. However, it is still a major challenge to accurately predict power load due to social and natural factors, such as temperature,...
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