The radial basis function (RBF) is a class of approximation functions commonly used in interpolation and least squares. The RBF is especially suitable for scattered data approximation and high dimensional function approximation. The smoothness and ap...
A novel approach to solve optimal control problems dealing simultaneously with fractional differential equations and time delay is proposed in this work. More precisely, a set of global radial basis functions are firstly used to approximate the state...
Inverse problems have numerous important applications in science, engineering, medicine, and other disciplines. In this study, we present a numerical solution for a one-dimensional parabolic inverse problem with energy overspecification at a fixed sp...
Due to the volatility of natural resources, the power fluctuations of photovoltaic (PV) generation have serious negative impacts on the power quality. This paper reports a novel approach to resolve this problem in a combined cascade hydro-PV-pumped s...
In the present paper non-convex multi-objective parameter optimization problems are considered which are governed by elliptic parametrized partial differential equations (PDEs). To solve these problems numerically the Pascoletti-Serafini scalarizatio...
To optimize performances such as continuous curvature, safety, and satisfying curvature constraints of the initial planning path for driverless vehicles in parallel parking, a novel method is proposed to train control points of the Bézier curve using...
This paper investigates the adequacy of radial basis function (RBF)-based models as surrogates in uncertainty quantification (UQ) and CFD shape optimization; for the latter, problems with and without uncertainties are considered. In UQ, these are use...
Electrical impedance tomography (EIT) is a non-invasive, radiation-free imaging technique with a lot of promise in clinical monitoring. However, since EIT image reconstruction is a non-linear, pathological, and ill-posed issue, the quality of the rec...
The purpose of this work is to construct a robust numerical scheme for a class of nonlinear free boundary identification problems. First, a shape optimization problem is constructed based on a least square functional. Schauder’s fixed point the...
To investigate hanger force during the construction phase of large-span steel box tie arch bridges, the challenge of low accuracy in force identification due to multifactor coupling was addressed. An energy method was employed to derive formulas for...
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...
Function interpolation and approximation are classical problems of vital importance in many science/engineering areas and communities. In this paper, we propose a powerful methodology for the optimal placement of centers, when approximating or interp...
The rapid evolution of smart building technologies has transformed the hotel industry, necessitating structured methodologies for evaluating building intelligence. This research, dedicated to engineering problems, proposes an integrated decision-maki...
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...
Basis functions are key in constructing interpolation equations in hull surface modification based on radial basis functions (RBF) interpolation. However, few have studied the selection of basis functions in depth. By comparing several typical basis...
The purpose of this article is to solve the problem of determining the cost of a water resource for the participants of the water-economic complex (WEC) on the basis of the optimal control of hydro power plants’ (HPP) functioning, taking into a...
The application rate for sprinkler irrigation of water–fertilizer integration machines is an important technical parameter for efficient operation. If the value is too large, the equipment will produce runoff; if it is too small, the equipment...
This paper presents a method for optimizing wavy plate-fin heat exchangers accurately and efficiently. It combines CFD simulation, Radical Basis Functions (RBF) with multi-objective optimization to improve the performance. The optimization of the Col...
The linear combination of atomic orbitals (LCAO) method is advantageous for calculating important bulk and surface properties of crystals and defects in/on them. Compared to plane wave calculations and contrary to common assumptions, hybrid density f...
The axle bridge plays a crucial role in the bogie of low-floor light rail vehicles, impacting operational efficiency and fuel economy. To minimize the total cost of the structure and turning of axle bridges, an optimization model of structural and tu...
Multi-objective optimization problems are often accompanied by complex black-box functions which not only increases the difficulty of solving, but also increases the solving time. In order to reduce the computational cost of solving such multi-object...
In this study, a manipulator calibration algorithm is suggested to decrease the positional errors of an industrial robotic manipulator using a genetic algorithm to select optimal measurement poses. First, a genetic algorithm based on the observabilit...
This paper proposes an optimal tracking control scheme through adaptive dynamic programming (ADP) for a class of partially unknown discrete-time (DT) nonlinear systems based on a radial basis function neural network (RBF-NN). In order to acquire the...
Radial basis function neural networks are a widely used type of artificial neural network. The number and centers of basis functions directly affect the accuracy and speed of radial basis function neural networks. Many studies use supervised learning...
In this paper, the Ant-based Radial Basis Function Network (ARBFN) is proposed to determine the optimal daily dispatch of ice-storage air-conditioning systems. ARBFN is a novel algorithm that is integrated into the Ant Colony Optimization and Radial...
To address the insufficient global search efficiency of the original Whale Optimization Algorithm (WOA), this paper proposes an enhanced variant (ImWOA) integrating three strategies. First, a dynamic cluster center-guided search mechanism based on K-...
An adaptive and efficient particle swarm optimization (PSO)-based learning algorithm to determine neuron centers in the hidden layer of a radial basis neural network (RBNN) is developed in the present work for regression problems. The proposed PSO&nd...
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...
This paper proposes a hybrid algorithm to solve the optimal energy dispatch of an ice storage air-conditioning system. Based on a real air-conditioning system, the data, including the return temperature of chilled water, the supply temperature of chi...
In this study, the concept of grounding systems is related to the voltage tolerance of the human body (human body voltage tolerance safety value). The maximum touch voltage target and grounding resistance values are calculated in order to compute the...
To establish the complex functional relationship between the stator bar end structure and the maximum electric field strength, and to optimize the anti-corona structure, an optimization model for the stator bar end based on the Seahorse Optimization...
A reinforcement learning algorithm is proposed to improve the accuracy of short-term load forecasting (STLF) in this article. The proposed model integrates radial basis function neural network (RBFNN), support vector regression (SVR), and adaptive an...
This study aimed to present the design methodology of microjet heat sinks with unequal jet spacing, using a machine learning technique which alleviates hot spots in heat sinks with non-uniform heat flux conditions. Latin hypercube sampling was used t...
Regarding the case of complicated structural shape optimization, there are cases where there are partial shapes such as holes and irregularities inside the structure. Concerning the complex structural optimization shape, the relationship between the...
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 order to improve the hydraulic efficiency and internal flow pattern of a multi-stage pump under multiple flow conditions, an intelligent optimization design was proposed for its hydraulic components. Sensitivity analysis was used to select the key...
This paper introduces a novel methodology that integrates 6G wireless Federated Edge Learning (FEEL) frameworks with MAC to PHY cross layer optimization strategies. In the context of mobile edge computing, typically ensuring robust channel estimation...
The increase in urban construction in China has been accompanied by increasing concrete output, which has reached 2250 million m3 in recent years, ranked as the highest in the world. Consequentially, its environmental burden is significant in terms o...
Designing Low Earth Orbit (LEO) constellations for the continuous, collaborative observation of space objects in MEO/GEO is a complex optimization task, frequently limited by prohibitive computational costs. This study introduces an efficient surroga...
We present a local trust region descent algorithm for unconstrained and convexly constrained multiobjective optimization problems. It is targeted at heterogeneous and expensive problems, i.e., problems that have at least one objective function that i...
Normal bases are widely used in applications of Galois fields and Galois rings in areas such as coding, encryption symmetric algorithms (block cipher), signal processing, and so on. In this paper, we study the normal bases for Galois ring extension
Inertial Navigation System (INS) is often combined with Global Navigation Satellite System (GNSS) to increase the positioning accuracy and continuity. In complex urban environments, GNSS/INS integrated systems suffer not only from dynamical model err...
This paper explores the application of transform-domain sparsification and compressed sensing (CS) techniques to improve the efficiency and quality of magnetic resonance imaging (MRI). We implement and evaluate three sparsifying methods—discret...
It is proposed to use a brain emotional learning control (BELC) system that is based on radial basis function (RBF) in order to enhance the performance of the speed control system of a permanent magnet synchronous motor (PMSM) and its capacity to rem...
In order to solve issues concerning performance induction and in-cylinder heat accumulation of a certain heavy-duty diesel engine in a plateau environment, working state parameters and performance indexes of diesel engine are calculated and optimized...
To overcome the limitations of Orthonormal Basis Function (OBF) methods in magnetic anomaly detection, including high false alarm rates and ambiguous target localization due to background noise, this paper introduces a high-confidence detection algor...
High penetration of wind power in the electricity system provides many challenges to power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecast...
Aerodynamic performances of ground vehicle continuously improve and a lot of both wind tunnel measurements and Computational Fluid Dynamics (CFD) investigations contribute in the identification of local zones where shape deformation can lead to drag...
To enhance the aerodynamic performance of organic Rankine cycle (ORC) turbines under increasing energy demands, surrogate-based optimization was applied to a 100 kW ORC turbine rotor. Four representative surrogate models—a radial basis neural n...
Computational fluid dynamics (CFD) is an effective tool for ship resistance prediction and hull form optimization. A three-dimensional volume mesh is essential for CFD simulation, and mesh generation requires much time and effort. Mesh deformation ca...
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