The challenging idea of using drones in last-mile delivery systems of logistics addresses a new routing problem referred to as the traveling salesman problem with drone (TSP-D). TSP-D aims to construct a route to deliver parcels to a set of customers...
In this paper, a tactical Production-Distribution Planning (PDP) has been handled in a fuzzy and stochastic environment for supply chain systems (SCS) which has four echelons (suppliers, plants, warehouses, retailers) with multi-products, multi-trans...
For the purpose of tackling ultra-wideband (UWB) indoor positioning with signal interference, a binary classifier for signal interference discrimination and positioning errors compensation model combining genetic algorithm (GA) and extreme learning m...
With this study, we address the optimal phase balancing problem in three-phase networks with asymmetric loads in reference to a mixed-integer quadratic convex (MIQC) model. The objective function considers the minimization of the sum of the square cu...
This research introduces a hybrid approach combining bio- and nature-inspired metaheuristic algorithms to enhance scheduling efficiency and minimize energy consumption in Underwater Acoustic Sensor Networks (UASNs). Five hybridized algorithms are des...
Hydro-thermal-wind generation scheduling (HTWGS) with economic and environmental factors is a multi-objective complex nonlinear power system optimization problem with many equality and inequality constraints. The objective of the problem is to genera...
Recently, evolutionary algorithms that can efficiently solve decomposable binary optimization problems have been developed. They are so-called model-based evolutionary algorithms, which build a model for generating solution candidates by applying a m...
Feature selection plays an important role in medical classification, particularly when datasets contain high-dimensional and redundant information. At the same time, the performance of a Random Weight Network (RWN) depends on its configuration, makin...
This study presents a novel method, termed RBAVO-DE (Relief Binary African Vultures Optimization based on Differential Evolution), aimed at addressing the Gene Selection (GS) challenge in high-dimensional RNA-Seq data, specifically the rnaseqv2 llumi...
Hyperspectral imaging technology is a promising technique for nondestructive quality evaluation of dried products. In order to realize real-time, online inspection of quality of dried products, it is necessary to determine a few important wavelengths...
In genome-wide association studies (GWAS), efficient incorporation of linkage disequilibria (LD) among densely typed genetic variants into association analysis is a critical yet challenging problem. Functional linear models (FLM), which impose a smoo...
Traditional power grid and its demand-side management (DSM) techniques are centralized and mainly focus on industrial consumers. The ignorance of residential and commercial sectors in DSM activities degrades the overall performance of a conventional...
The drastic increase of websites is one of the causes behind the recent information overload on the internet. A recommender system (RS) has been developed for helping users filter information. However, the cold-start and sparsity problems lead to low...
This study introduces a two-stage optimization method for designing an ultrawideband polarization conversion metasurface. By integrating topology and shape optimization techniques, the proposed method expands the design space to achieve enhanced pola...
In this paper, a low-profile HF (high-frequency) meandered dipole antenna with a ferrite-loaded artificial magnetic conductor (AMC) is proposed. To operate in the HF band while retaining a compact size, ferrite with high permeability is applied to th...
The sensitivity of cold atom gravimeters is strongly governed by the spatial uniformity of their internal bias magnetic field. This paper presents an engineering-constrained optimization framework based on a mixed-encoding genetic algorithm for desig...
The inclusion of photovoltaics (PV) in electric power supply systems continues to be a significant factor in global interest. However, solar power exhibits intermittent uncertainty and is further unpredictable. Accurate solar generation prediction an...
Minimizing energy costs while maintaining consumer satisfaction is a very challenging task in a smart home. The contradictory nature of these two objective functions (cost of energy and satisfaction level) requires a multi-objective problem formulati...
Identification of coal and gangue is one of the important problems in the coal industry. To improve the accuracy of coal gangue identification in the coal mining process, a coal gangue identification method based on histogram of oriented gradient (HO...
Intrusion detection systems (IDS) are crucial for network security because they enable detection of and response to malicious traffic. However, as next-generation communications networks become increasingly diversified and interconnected, intrusion d...
Daily, monthly, and annual multi-product sales records are stored in databases, but due to the massive amounts of data, they are not used for decision-making when updating product catalogs. Meanwhile, the use of artificial intelligence in business is...
This paper focuses on minimizing the annual operative costs in monopolar DC distribution networks with the inclusion of solar photovoltaic (PV) generators while considering a planning period of 20 years. This problem is formulated through a mixed-int...
Texture classification is one of the machine learning methods that attempts to classify textures by evaluating samples. Extracting related features from the samples is necessary to successfully classify textures. It is a very difficult task to extrac...
Nature has evolved sophisticated optimization strategies over billions of years, yet computational algorithms inspired by plants remain remarkably underexplored. We present a comprehensive systematic review following PRISMA 2020 guidelines, analyzing...
The neurobiological mechanisms underlying Autism Spectrum Disorders (ASD) remains controversial. One factor contributing to this debate is the phenotypic heterogeneity observed in ASD, which suggests that multiple system disruptions may contribute to...
Breast cancer represents a significant public health concern in both Western countries and Asia. Accurate and early detection is critical to improving long-term patient survival. For physicians to understand the classification and decision rules and...
Single-path transmission optimization is a core task for resource scheduling and operation of complex networks, which requires coordinated optimization of transmission cost and flow. Classical algorithms bear heavy computational loads in high-dimensi...
In smart homes, heavy reliance on appliance automation has increased, along with the energy demand in developing urban areas, making efficient energy management an important factor. To address the scheduling of appliances under Demand-Side Management...
Recently, texture features have been widely used for historical document image analysis. However, few studies have focused exclusively on feature selection algorithms for historical document image analysis. Indeed, an important need has emerged to us...
Outdoor mobile spraying robots are increasingly being used for precision plant protection and vector-borne disease control. Coverage planning in unstructured environments remains difficult because spray models are computationally costly, chassis moti...
Despite significant advances in gene discovery, the molecular basis of many rare genetic disorders remains poorly understood. The concept of disease modules, clusters of functionally related genes whose disruption leads to overlapping phenotypes, off...
A high-pressure hydraulically adjusted servomotor is an electromechanical–hydraulic integrated system centered on a servo valve that plays a crucial role in ensuring the safe and stable operation of steam turbines. To address the issues of diff...
The need for longer lasting and wider wireless coverage has driven the transition from a single drone to drone swarms. Unlike the single drone, drone swarms can collaboratively achieve full coverage over a target area. However, the existing literatur...
Antennas with multifunctional capabilities integrated into a single device that demonstrates a high performance are in demand, and microstrip antennas with quadband coverage are very useful for a wide range of mm-wave applications. Antennas and propa...
This study focuses on exploring the indication and importance of selenium (Se) and tellurium (Te) in distinguishing different genetic types of ore deposits. Traditional views suggest that dispersed elements are unable to form independent deposits, bu...
Pure electric public transport management optimization can promote the electrification evolution from conventional diesel emission to low/zero carbon transport revolution. However, emerging electric vehicle scheduling (EVS) takes into account battery...
Microwave electromagnetic devices have been used for many applications in tropospheric communication, navigation, radar systems, and measurement. The development of the signal preprocessing units including frequency-selective devices (bandpass filter...
Incorporating demand-side management (DSM) into residential energy guarantees dynamic electricity management in the residential domain by allowing consumers to make early-informed decisions about their energy consumption. As a result, power companies...
A circular sector-shaped dipole antenna with meandered arms based on an artificial magnetic conductor (AMC) is proposed in this study. A compact unit cell of the AMC operating within 19–485 MHz is designed using a ferrite material, which exhibi...
Because of the introduction and spread of the second generation of the Digital Video Broadcasting—Terrestrial standard (DVB-T2), already active television broadcasters and new broadcasters that have entered in the market will be required to (re...
Hybridized algorithms are commonly employed to improve the performance of any existing method. However, an optimal learning algorithm composed of evolutionary and swarm intelligence can radically improve the quality of the final neuron states and has...
Classification is an important task of machine learning for solving a wide range of problems in conforming patterns. In the literature, machine learning algorithms dealing with non-conforming patterns are rarely proposed. In this regard, a cellular a...
Microarrays have been proven to be beneficial for understanding the genetics of disease. They are used to assess many different types of cancers. Machine learning algorithms, like the artificial neural network (ANN), can be trained to determine wheth...
The proliferation of Internet of Things (IoT) devices challenges deep learning (DL) deployment due to their limited computational power, while cloud offloading introduces high latency and network strain. Fog computing provides a viable middle ground....
With the increasing sophistication of electromagnetic environments in modern combat platforms, joint sensing and communication (JSAC) technology has emerged as a critical research frontier. Among these, JSAC waveform design plays a crucial role, as i...
The combination and convergence of energy-intensive industries developed by ecological factors based on energy clusters is discussed in this paper. Here, a few models for the prediction of greenhouse effects are used as a single type of modeling. In...
The smart grid (SG) has emerged as a key enabling technology facilitating the integration of variable energy resources with the objective of load management and reduced carbon-dioxide (CO
In order to solve the problem of optimal dispatching of photovoltaic power for local consumption to the greatest degree in a photovoltaic greenhouse, this paper proposes a multiform energy optimal dispatching model and a solution algorithm. First, an...
In order to enhance consumers’ experience of online shopping and to reduce their unnecessary car trips for offline shopping, a new mode, namely, establishing the virtual-shopping-experience store, is proposed in this paper. A bi-level programmi...
Cooperative jamming task allocation for UAV swarms must jointly consider radar priority, the effectiveness of different jamming modes, and heterogeneous resource limits. This paper establishes a radar threat assessment model from radar operating para...
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