This study proposes an improved vector-weighted averaging algorithm (IDEINFO) for the optimization of different problems. The original vector-weighted optimization algorithm (INFO) uses weighted averaging for entity structures and uses three core pro...
We first study the error performances of the Vector Weak Rescaled Pure Greedy Algorithm for simultaneous approximation with respect to a dictionary
In this work, we give provable sieving algorithms for the Shortest Vector Problem (SVP) and the Closest Vector Problem (CVP) on lattices in
The opportunities provided by new information technologies, object-oriented programming tools, and modern operating systems for solving boundary value problems in CFD described by partial differential equations are discussed. An approach to organizin...
The geomagnetic matching aided positioning system based on Iterative Closest Contour Point (ICCP) algorithm can suppress the accumulation error of the inertial navigation system and achieve the accurate positioning of the vehicle. Aiming at the probl...
An enhanced affine projection algorithm (APA) is proposed to improve the filter performance in aspects of convergence rate and steady-state estimation error, since the adjustment of the input-vector number can be an effective way to increase the conv...
In recent years, data mining technology has become increasingly popular, evolving into an independent discipline as research deepens. This study constructs and optimizes an association rule algorithm based on the Boolean vector (BV) inner product and...
Bending control is one of the main methods of shape control for the hot rolled plate. However, the existing bending force setting models based on traditional mathematical methods are complex and have low control accuracy, which leads to poor strip ex...
The arithmetic optimization algorithm (AOA) is a new metaheuristic algorithm inspired by arithmetic operators (addition, subtraction, multiplication, and division) to solve arithmetic problems. The algorithm is characterized by simple principles, few...
Accurate prediction of photovoltaic power is conducive to the application of clean energy and sustainable development. An improved whale algorithm is proposed to optimize the Support Vector Machine model. The characteristic of the model is that it ne...
Quantum computing is suggested as a new tool to deal with large data set for machine learning applications. However, many quantum algorithms are too expensive to fit into the small-scale quantum hardware available today and the loading of big classic...
Backlight power-saving algorithms can reduce the power consumption of the display by adjusting the frame pixels with optimal clipping points under some tradeoff criteria. However, the computation for the selected clipping points can be complex. In th...
Strapdown airborne gravimetry is an efficient way to obtain gravity field data. A new method has been developed to improve the accuracy of airborne vector gravimetry. The method introduces a backward strapdown navigation algorithm into the strapdown...
Quasi-continuous metasurfaces are widely used in various optical systems and their subwavelength structures invalidate traditional design methods based on scalar diffraction theory. Here, a novel vector iterative Fourier transform algorithm (IFTA) is...
Depositional microfacies identification plays a key role in the exploration and development of oil and gas reservoirs. Conventionally, depositional microfacies are manually identified by geologists based on the observation of core samples. This conve...
Attitude errors, accelerometer bias, the gravity disturbance vector, and their coupling are the primary factors obstructing strapdown airborne vector gravimetry. This paper takes the geocentric inertial frame as a reference and solves the kinematic e...
In this paper, a mixed sources dimension reduction Multiple Signal Classification (MUSIC) localization algorithm suitable for Micro-Electro-Mechanical System (MEMS) vector hydrophone linear arrays is proposed, which reduces the two-dimensional search...
There are a number of factors that can affect the quality of cementing, and they constrain each other. Current cementing quality prediction methods are still in the stage of development, and it is difficult to establish an analytical model for cement...
Anomaly in geoacoustic emission is an important earthquake precursor. Current geoacoustic anomaly detection methods are limited by their low signal-to-noise ratio, low intensity, sample imbalance, and low accuracy. Therefore, this paper proposes a cl...
The determination of a ship’s safe trajectory in collision situations at sea is one of the basic functions in autonomous navigation of ships. While planning a collision avoiding manoeuvre in open waters, the navigator has to take into account the shi...
To enhance the accuracy and efficiency of reliability analyses for an aero-engine vectoring exhaust nozzle (VEN), a dual-stochastic extreme response surface method based on the genetic algorithm (DSERSM-GA) is developed by integrating the genetic alg...
Accurate electricity forecasting is still the critical issue in many energy management fields. The applications of hybrid novel algorithms with support vector regression (SVR) models to overcome the premature convergence problem and improve forecasti...
To simulate the anisotropic hysteresis characteristics of soft magnetic composite (SMC) materials accurately, an improved vector hysteresis model was proposed and utilized to adjust the shape of hysteresis curves by introducing two parameters. These...
The calorific value of coal gangue is a critical index for coal waste recycling and the energy industry. To establish an accurate and efficient calorific value forecasting model, a method based on hybrid kernel function–support vector regression and...
In Pareto-based many-objective evolutionary algorithms, performance usually degrades drastically as the number of objectives increases due to the poor discriminability of Pareto optimality. Although some relaxed Pareto domination relations have been...
An algorithm based on a support vector machine (SVM) is proposed for hydrometeor classification. The training phase is driven by the output of a fuzzy logic hydrometeor classification algorithm, i.e., the most popular approach for hydrometer classifi...
The three-dimensional model of geographic elements serves as the primary medium for digital visualization. However, the original point cloud model is often vast and includes considerable redundant data, resulting in inefficiencies during the three-di...
Methane, known as a flammable and explosion hazard gas, is the main component of marsh gas, firedamp, and rock gas. Therefore, it is important to be able to detect methane concentration safely and effectively. At present, many models have been propos...
Electric buses have many significant advantages, such as zero emissions and low noise and energy consumption, making them play an important role in saving the operation cost of bus companies and reducing urban traffic pollution emissions. Therefore,...
High-precision direction of arrival (DOA) of wideband signals is a very important technology in the field of radar and communication. In this work, we propose an efficient support vector regression (SVR) architecture via a genetic algorithm (GA) for...
The fuel cell engine mechanism model is used to research fault diagnosis based on a data-driven method to identify the failure of proton exchange membrane fuel cells in the process of operation, which leads to the degradation of system performance an...
To predict the natural gas hydrate formation conditions quickly and accurately, a novel hybrid genetic algorithm–support vector machine (GA-SVM) model was developed. The input variables of the model are the relative molecular weight of the natu...
In array signal processing systems, the direction of arrival (DOA) and polarization of signals based on uniform linear or rectangular sensor arrays are generally obtained by rotational invariance techniques (ESPRIT). However, since the ESPRIT algorit...
In view of the inconsistency of guided wave energy in distributed acoustic sensing coal mine maps and the difficulty in distinguishing the vibration levels of coal mines, which leads to the poor sensitivity and accuracy of microseism detection, a coa...
Owing to their high performance and high-efficiency controllability, surface-mounted permanent magnet synchronous motors (SPMSMs) have been widely considered for various robotic systems. The conventional three-vector-based model predictive torque con...
Military uniforms serve as an essential symbol for servicemen and an important image of national and military dignity. The current military uniform size system in Taiwan, which features various types of military uniforms based on the body sizes of se...
To increase the accuracy of indoor visible light positioning, a novel indoor visible light localization technique based on the marine predator algorithm-optimized least squares support vector machine (MPA-LSSVM) is suggested. The light signals of eac...
The accuracy of annual electric load forecasting plays an important role in the economic and social benefits of electric power systems. The least squares support vector machine (LSSVM) has been proven to offer strong potential in forecasting issues,...
This paper proposes a modeling method to establish a parametric-conducted emission model of a switching model power supply (SMPS) chip through a developed vector fitting algorithm. A common SMPS chip LTM8025 was taken as an example to explain the mod...
To address the problems of grid connection and power dispatching caused by non-stationary wind power output, an improved Jellyfish Search algorithm optimization support vector regression (IJS-SVR) model was proposed in this study to achieve high-prec...
10 February 2020
Background: Abdominal adiposity is an important risk factor of chronic cardiovascular diseases, thus the prediction of abdominal adiposity and obesity can reduce the risks of contracting such diseases. However, the current prediction models display l...
In order to overcome the disadvantages of some existing autonomous underwater vehicles (AUVs), such as actuator extraposition and degree-of-freedom (DOF) redundancy, a 2-DOF vector propeller propulsion system with built-in actuator based on the defic...
Landslides are one of the most frequent and important natural disasters in the world. The purpose of this study is to evaluate the landslide susceptibility in Zhenping County using a hybrid of support vector regression (SVR) with grey wolf optimizer...
The use of intelligent algorithms for global solar prediction is an ideal tool for research focused on the use of solar energy. Forecasting solar radiation supports different applications focused on the generation and transport of energy in places wh...
Short-term power load forecasting is an important basis for the operation of integrated energy system, and the accuracy of load forecasting directly affects the economy of system operation. To improve the forecasting accuracy, this paper proposes a l...
This study proposes an adaptive Support Vector Machine (SVM) classification method based on an enhanced Starfish Optimization Algorithm (SFOAE-SVM) for hyperspectral image (HSI) classification. HSI classification remains a critical challenge in remot...
Icing on power transmission lines is a serious threat to the security and stability of the power grid, and it is necessary to establish a forecasting model to make accurate predictions of icing thickness. In order to improve the forecasting accuracy...
In the energy crisis and post-epidemic era, the new energy industry is thriving, encompassing new energy vehicles exclusively powered by lithium-ion batteries. Within the battery management system of these new energy vehicles, the state of charge (SO...
The state of health (SOH) prediction of lithium-ion batteries is a pivotal function within the battery management system (BMS), and achieving accurate SOH predictions is crucial for ensuring system safety and prolonging battery lifespan. To enhance p...
Travel mode identification is one of the essential steps in travel information detection with Global Positioning System (GPS) survey data. This paper presents a Support Vector Classification (SVC) model for travel mode identification with GPS data....
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