In this study, we investigate the application of the direct sampling method (DSM) to identify small dielectric objects in a limited-aperture inverse scattering problem. Unlike previous studies, we consider the bistatic measurement configuration corre...
Cover crops provide a range of well-documented benefits to growers and the environment. However, no single species can deliver all of these benefits, and hence planting mixtures is gaining increasing attention. To the best of our knowledge, there is...
Multi-label learning is dedicated to learning functions so that each sample is labeled with a true label set. With the increase of data knowledge, the feature dimensionality is increasing. However, high-dimensional information may contain noisy data,...
Robotic bin-picking performance has been gaining attention in recent years with the development of increasingly advanced camera and machine vision systems, collaborative and industrial robots, and sophisticated robotic grippers. In the random bin-pic...
The application of multiple-point statistics (MPS) in the mining industry is not yet widespread and there are very few applications so far. In this paper, we focus on the problem of algorithmic input parameter selection, which is required to perform...
3 November 2025
Different strategies to include structural mechanical aspects in the design process of hydraulic machines are compared. Therefore, an axial turbine’s runner blade is optimized using evolutionary algorithms. Four different setups with a scalar o...
This paper presents the planning of an experiment aimed at determining the scope of scientific research. It has been demonstrated in the conducted reliability investigations that main and auxiliary combustion engines, chosen as the objects of marine...
This tutorial and review of multi-objective optimization (MOO) gives a detailed explanation of the 5 steps to create, solve, and then select the optimum result. Unlike single-objective optimization, the fifth step of selection or ranking of solutions...
In this study, an unsupervised infrared object-detection approach based on spatial–temporal patch tensor and object selection is proposed to fully use effective temporal information and maintain a balance between object-detection performance an...
Permanent magnet synchronous motors (PMSMs) with rectangular coils in hairpin windings exhibit improved fill factor and reduced end turn of the coils, which in turn improve the efficiency and power density of PMSMs, making them ideal for e-mobility a...
This study introduces a novel approach to correlation-based feature selection and dimensionality reduction in high-dimensional data structures. To this end, a customized scoring function is proposed, designed as a dual-objective structure that simult...
Many lumped rainfall-runoff models are available but no single model can account for the uniqueness and variability of all catchments. While there has been progress in developing frameworks for optimal model selection, the process currently selects a...
Ocean thermal energy is a huge renewable and clean energy. For different applications of the Ocean Thermal Energy Conversion (OTEC) system, new objective functions are proposed and optimal CO2-based binary zeotropic mixtures for each objective functi...
This study proposes a multi-objective optimization model for capital allocation in an energy stock portfolio. The model integrates two financial objectives (maximizing return and minimizing value-at-risk) and four environmental objectives (minimizing...
Process-based models are widely used to investigate nutrient dynamics for water management purposes. Simulating nutrient transport and transformation processes from agricultural land into water bodies at the catchment scale are particularly relevant...
Sensor selection is a vital part of Wireless Sensor Network (WSN) management. This becomes of increased importance when considering the use of low-cost, bearing-only sensor nodes for the tracking of Unmanned Aerial Vehicles (UAVs). However, tradition...
A new optimization technique is proposed for solving optimization problems having single and multiple objectives, with objective functions such as generation cost, loss, and severity value. This algorithm was developed to satisfy the constraints, suc...
The article is devoted to the control of multichannel objects by the method of numerical optimization. In this area, there are several not entirely accurate, but deeply rooted, ideas and approaches that we would like to analyze. This analysis is pres...
This paper introduces a novel method that enables robots to identify objects based on user gaze, tracked via eye-tracking glasses. This is achieved without prior knowledge of the objects’ categories or their locations and without external marke...
In this communication, we investigate the performance of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) in many-objective optimization scenarios pertaining to joint radar and communication functionality. We introduce five objectives relevan...
Based on the model of irreversible single resonance energy-selective electron heat engine established in the previous literature, this paper applies finite-time thermodynamic theory and NSGA-II algorithm to perform multi-objective optimization. Singl...
This paper proposes a multi-objective decision-making model for underwater countermeasures based on a multi-objective decision theory and solves it using the multi-objective discrete particle swarm optimization (MODPSO) algorithm. Existing decision-m...
As applied sciences grow by leaps and bounds, semiparametric regression analyses have broad applications in various fields, such as engineering, finance, medicine, and public health. Single-index varying-coefficient model is a common class of semipar...
This study addresses the challenge of selecting outstanding students at higher education institutions under multiple constraints. We propose a novel integer programming solution to manage this process, formulating it as a constrained assignment probl...
While most patients with degenerative rotator cuff tears respond to conservative treatment, a minority progress to surgery. To anticipate these cases under class imbalance, we propose a sensitivity-constrained evolutionary feature selection framework...
As exact algorithms are unfeasible to solve real optimization problems, due to their computational complexity, meta-heuristics are usually used to solve them. However, choosing a meta-heuristic to solve a particular optimization problem is a non-triv...
This paper presents a novel semi-supervised joint dictionary learning (S2JDL) algorithm for hyperspectral image classification. The algorithm jointly minimizes the reconstruction and classification error by optimizing a semi-supervised dictionary lea...
With the advent of novel quantum computing technologies and the new possibilities thereby offered, a prime opportunity has presented itself to investigate the practical application of quantum computing. This work investigates the feasibility of using...
When single-phase three-level neutral-point-clamped (NPC) converters operate, there are two main control objectives that need to be met for correct operation. First, the ac source current must be controlled to be sinusoidal. Second, the dc capacitor...
Climate change poses significant challenges to energy efficiency and occupant comfort in residential buildings. This study introduces a simulation-based multi-objective optimization approach for architectural design, aimed at addressing these challen...
Objectives: Atypical eating habits frequently characterize people with Autism Spectrum Disorder (ASD) from early infancy. Food selectivity, defined as a narrow variety of food intake and reticence to new food, is the most frequent feeding disorder in...
Submersible pumps are now in high demand due to the sporadic occurrence of recent torrential rains. The current study was carried out to investigate the hydraulic characteristics of a submersible axial-flow pump with a swept impeller and to optimize...
The overlap function is an important class of aggregation function that is closely related to the continuous triangular norm. It has important applications in information fusion, image processing, information classification, intelligent decision-maki...
This study addresses the foundational step of developing a classification and taxonomy of agent objective functions as a prerequisite for analyzing stability and forming robust production schedules in distributed manufacturing systems. The research i...
Multiple-object tracking is affected by various sources of distortion, such as occlusion, illumination variations and motion changes. Overcoming these distortions by tracking on RGB frames, such as shifting, has limitations because of material distor...
Minimizing energy consumption remains a critical challenge in wireless sensor networks (WSNs) because of their reliance on nonrechargeable batteries. Clustering-based hierarchical communication has been widely adopted to address this issue by improvi...
The solution to constrained multi-objective optimization problems (CMOPs) requires optimizing the objective functions while satisfying the constraint conditions. To effectively address CMOPs, algorithms must balance objectives and constraints. Howeve...
A novel multi-objective robust optimization model of an integrated energy system with hydrogen storage (HIES) considering source–load uncertainty is proposed to promote the low-carbon economy operation of the integrated energy system of a park....
To perform indicator selection and verification for the on-orbit fault reconstruction of a giant satellite swarm, a hybrid multi-objective fault reconstruction algorithm is proposed and then verified by Monte Carlo analysis. First, according to the o...
Aimed at the optimization design of the parameters of the commutation circuit of a hybrid DC-current-limiting circuit breaker (HDCCLCB), a parameter selection model considering the short-time withstand of the thyristor and the volume of the commutati...
In rubber bumper design, the most important mechanical property of the product is the force–displacement curve under compression and its fulfillment requires an iterative design method. Design engineers can handle this task with the modificatio...
Compressive sensing (CS) of the signal ambiguity function (AF) and enforcing the sparsity constraint on the resulting signal time-frequency distribution (TFD) has been shown to be an efficient method for time-frequency signal processing. This paper p...
This paper proposes an efficiency-optimized multi-parameter collaborative non-dimensional selection method for industrial fans. Based on fan similarity theory, selection parameters are transformed into non-dimensional forms. The fan’s best work...
Fuzzy portfolio selection has resulted in many researchers to focus on this field. Based on the risk attitudes, this study discusses the risk attitudes in a decision group for portfolio selection. Therefore, we adopt the risk attitudes to describe th...
The general context of this proposal is represented by the energy-efficient smart home that integrates renewable energy sources such as photovoltaic panels. The objective of this article is to minimize the amount of energy consumed from the national...
Background: Prehabilitation is a strategy used aiming to reduce the risk factors and complications of surgery procedures, but there is no consensus on the effectiveness of supervised physical exercise and its optimal prescription during this phase. O...
Cement-slag concrete has become one of the most widely used building materials considering its economical advantage and satisfying uniaxial compressive strength (UCS). In this study, an AI-based method for cement-slag concrete design was developed ba...
A difficulty in encoding spatial information in an egocentric (i.e., body-to-object) and especially allocentric (i.e., object-to-object) manner, and impairments in executive function (EF) are typical in amnestic mild cognitive impairment (aMCI) and A...
One of the challenging tasks in systems biology is to understand how molecular networks give rise to emergent functionality and whether universal design principles apply to molecular networks. To achieve this, the biophysical, evolutionary and physio...
This paper presents a finite control-set model predictive control (FCS-MPC) based technique to reduce the switching loss and frequency of the on-grid PV inverter by incorporating a switching frequency term in the cost function of the model predictive...
of 110