Although proposed more than half a century ago, the Nelder–Mead simplex search algorithm is still widely used. Four numeric constants define the operations and behavior of the algorithm. The algorithm with the original constant values performs...
This study presents an integrated modeling and optimization framework for laser transmission welding (LTW) of transparent polymethyl methacrylate (PMMA) joints using single- and multi-core copper wires as energy absorbers. The highly nonlinear relati...
Hyperspectral images (HSIs) with abundant spectra and high spatial resolution can satisfy the demand for the classification of adjacent homogeneous regions and accurately determine their specific land-cover classes. Due to the potentially large varia...
Properly configuring Evolutionary Algorithms (EAs) is a challenging task made difficult by many different details that affect EAs’ performance, such as the properties of the fitness function, time and computational constraints, and many others....
Optimization methods are of great importance for the efficient training of neural networks. There are many articles in the literature that propose particular variants of existing optimizers. In our article, we propose the use of the combination of tw...
This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heu...
This paper presents a comprehensive survey of the meta-heuristic optimization algorithms on the text clustering applications and highlights its main procedures. These Artificial Intelligence (AI) algorithms are recognized as promising swarm intellige...
This paper introduces a novel population-based bio-inspired meta-heuristic optimization algorithm, called Blood Coagulation Algorithm (BCA). BCA derives inspiration from the process of blood coagulation in the human body. The underlying concepts and...
This paper proposes a novel image tone-mapping framework that incorporates meta-learning, a psychophysical model, Bayesian optimization, and light-field virtual diffraction. First, we formalize the virtual diffraction process as a mathematical operat...
This study examines the use of meta-heuristic algorithms, specifically particle swarm optimization and genetic algorithms, for optimizing thermal systems, addressing a research gap on their efficacy in larger systems. Utilizing MATLAB’s Simulin...
Shunt Adaptive Power Filter (SAPF) is widely used in the performance of power quality improvement activities in the power supply industry for processing industries or civil power sources in the world today based on its simplicity, transparency, high...
Unmanned Aerial Vehicles (UAVs), a subset of aerial robots, play crucial roles in various domains, such as disaster management, agriculture, and healthcare. Their application proves invaluable in situations where human intervention poses risks or inv...
Combined heat and power (CHP) plants are known as efficient technologies to reduce environmental emissions, balance energy costs, and increase total energy efficiency. To obtain a more efficient system, various optimization methods have been employed...
Control in multi-agent decision-making systems is an important issue with a wide variety of existing approaches. In this work, we offer a new comprehensive framework for distributed control. The main contributions of this paper are summarized as foll...
Schottky barrier diodes (SBD) are crucial in the electronics sector. The electronic properties of SBD are characterized by three basic electrical parameters as the ideality factor (n), barrier height (ΦSB) and series resistance (RS). These parame...
A60 class bulkhead penetration piece is a fire-resistance apparatus installed on bulkhead compartments to protect lives and to prevent flame diffusion in case of fire accident in ships and offshore plants. In this study, approximate optimization with...
This paper introduces the election optimization algorithm (EOA), a meta-heuristic approach for engineering optimization problems. Inspired by the democratic electoral system, focusing on the presidential election, EOA emulates the complete election p...
In the proposed article, we present a nature-inspired optimization algorithm, which we called Polar Bear Optimization Algorithm (PBO). The inspiration to develop the algorithm comes from the way polar bears hunt to survive in harsh arctic conditions....
The decision-making of sustainable supply chain network (SSCN) design is a strategy capacity for configuring network facility and product flow. When optimizing conflicting economic, environmental, and social performance objectives, it is difficult to...
Global optimization, especially on a large scale, is challenging to solve due to its nonlinearity and multimodality. In this paper, in order to enhance the global searching ability of the firefly algorithm (FA) inspired by bionics, a novel hybrid met...
Background: Waste collection is a critical logistical challenge in urban management, and while Internet of Things (IoT) technologies are increasingly used to optimize collection routes, a systematic, quantitative synthesis of their impact is lacking....
29 December 2021
PM2.5 pollution in China is becoming increasingly severe, threatening public health. The major goal of this study is to evaluate the mortality rate attributed to PM2.5 pollution and design pollution mitigation schemes in a southern district of China...
This paper reviews a majority of the nature-inspired algorithms, including heuristic and meta-heuristic bio-inspired and non-bio-inspired algorithms, focusing on their source of inspiration and studying their potential applications in drones. About 3...
In the first section, five major attempts to solve the problem of induction and their failures are discussed. In the second section, an account of meta-induction is introduced. It offers a novel solution to the problem of induction, based on mathemat...
Personal Identification Numbers (PIN) and unlock patterns are two of the most often used smartphone authentication mechanisms. Because PINs have just four or six characters, they are subject to shoulder-surfing attacks and are not as secure as other...
This paper presents a comparative study that explores the performance of various meta-heuristics employed for Optimal Signal Design, specifically focusing on estimating parameters in nonlinear systems. The study introduces the Robust Sub-Optimal Exci...
In this paper, a new Modified Meta-Heuristic algorithm is proposed. This method contains some modifications to improve the performance of the simulated-annealing algorithm (SA). Most authors who deal with improving the SA algorithm presented some imp...
Nowadays, recommender systems are vital in lessening the information overload by filtering out unnecessary information, thus increasing comfort and quality of life. Matrix factorization (MF) is a well-known recommender system algorithm that offers go...
Recently, piracy and copyright violations of digital content have become major concerns as computer science has advanced. In order to prevent unauthorized usage of content, digital watermarking is usually employed. This work proposes a new approach t...
This paper proposes a new meta-heuristic optimization algorithm, the crown growth optimizer (CGO), inspired by the tree crown growth process. CGO innovatively combines global search and local optimization strategies by simulating the growing, sprouti...
Traffic signal control is an integral component of an intelligent transportation system (ITS) that play a vital role in alleviating traffic congestion. Poor traffic management and inefficient operations at signalized intersections cause numerous prob...
Meta-few-shot learning algorithms, such as Model-Agnostic Meta-Learning (MAML) and Almost No Inner Loop (ANIL), enable machines to learn complex tasks quickly with limited data and based on previous experience. By maintaining the inner loop head of t...
Recent technologies such as artificial intelligence, machine learning, and big data are essential for supporting healthcare monitoring systems, particularly for monitoring Monkeypox confirmed cases. Infected and uninfected cases around the world have...
Much research on adversarial attacks has proved that deep neural networks have certain security vulnerabilities. Among potential attacks, black-box adversarial attacks are considered the most realistic based on the the natural hidden nature of deep n...
Lipoaspirate has become the preferred source for regenerative cells. The mechanical processing of lipoaspirate has advantages over enzymatic processing but has a lower yield of regenerative cells. A review of the literature shows different techniques...
It is very common for natural or synthetic materials to be characterized by a periodic or quasi-periodic micro-structure. This micro-structure, under the different loading conditions may play an important role on the apparent, macroscopic behaviour o...
Ultra-high-performance concrete (UHPC) is a recently developed material which has attracted considerable attention in the field of civil engineering because of its outstanding characteristics. One of the key factors in concrete design is the compress...
The purpose of this research is to investigate different milling parameters for optimization to achieve the maximum rate of material removal with the minimum tool wear and surface roughness. In this study, a tool wear factor is specified to investiga...
The rapid development of sixth-generation mobile communication systems has brought about significant advancements in both Quality of Service (QoS) and Quality of Experience (QoE) for users, largely due to the extremely high data rates and a diverse r...
In this paper, we explore the behavior of several optimization methods for reducing coating Brownian noise in the mirrors of gravitational wave detectors. We will refer to cryogenic operating temperatures, where the low refractive index material has...
This paper introduces a novel unsupervised domain adaptation (UDA) method, MeTa Discriminative Class-Wise MMD (MCWMMD), which combines meta-learning with a Class-Wise Maximum Mean Discrepancy (MMD) approach to enhance domain adaptation. Traditional M...
The performance of deep learning is heavily influenced by the size of the learning samples, whose labeling process is time consuming and laborious. Deep learning algorithms typically assume that the training and prediction data are independent and un...
To overcome the limitations of single-objective optimization in permanent magnet synchronous motor (PMSM) performance enhancement, this study proposes an adaptive moving least squares (AMLS) for a 12-pole/36-slot built-in PMSM. Through comprehensive...
This paper investigates the optimization of cylindrical metasurface meta-covers designed to enable beamforming capabilities in single linear antennas. This study focuses on the development and application of advanced optimization tools to tailor the...
Numerous network cyberattacks have been launched due to inherent weaknesses. Network intrusion detection is a crucial foundation of the cybersecurity field. Intrusion detection systems (IDSs) are a type of machine learning (ML) software proposed for...
Software maintenance and release management demand proper identification of bug dependencies since priority violations or unresolved dependent issues can often lead to a chain of failures. However, dependency annotations in bug reports are extremely...
It is paramount to optimize the performance of a chemical process in order to maximize its yield and productivity and to minimize the production cost and the environmental impact. The various objectives in optimization are often in conflict, and one...
Solar radiation prediction plays a crucial role in renewable energy management, impacting various decision-making processes aimed at optimizing the utilization of solar resources and promoting sustainability. Ensemble regression methods, notably Voti...
Speech emotion recognition (SER) is widely applicable today, benefiting areas such as entertainment, robotics, and healthcare. This emotional understanding enhances user-machine interaction, making systems more responsive and providing more natural e...
Microwave-assisted mechanical rock breaking represents an innovative technology in the realm of mining excavation. The intricate and variable characteristics of geological formations necessitate a comprehensive understanding of the interplay between...
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